The basis for limited specificity and MHC restriction in a T cell

ARTICLE
Received 22 Oct 2012 | Accepted 30 Apr 2013 | Published 5 Jun 2013
DOI: 10.1038/ncomms2948
The basis for limited specificity and MHC
restriction in a T cell receptor interface
Kurt H. Piepenbrink1,w, Sydney J. Blevins1, Daniel R. Scott1 & Brian M. Baker1,2
ab T cell receptors (TCRs) recognize peptides presented by major histocompatibility complex
(MHC) proteins using multiple complementarity-determining region (CDR) loops.
TCRs display an array of poorly understood recognition properties, including specificity,
crossreactivity and MHC restriction. Here we report a comprehensive thermodynamic
deconstruction of the interaction between the A6 TCR and the Tax peptide presented by the
class I MHC HLA-A*0201, uncovering the physical basis for the receptor’s recognition
properties. Broadly, our findings are in conflict with widely held generalities regarding TCR
recognition, such as the relative contributions of central and peripheral peptide residues and
the roles of the hypervariable and germline CDR loops in engaging peptide and MHC. Instead,
we find that the recognition properties of the receptor emerge from the need to engage the
composite peptide/MHC surface, with the receptor utilizing its CDR loops in a cooperative
fashion such that specificity, crossreactivity and MHC restriction are inextricably linked.
1 Department of Chemistry and Biochemistry, 251 Nieuwland Science Hall, University of Notre Dame, Notre Dame, Indiana 46556, USA. 2 The Harper Cancer
Research Institute, 251 Nieuwland Science Hall, University of Notre Dame, Notre Dame, Indiana 46556, USA. w Present address: Institute of Human Virology,
University of Maryland School of Medicine, 725 West Lombard Street, Room N557, Baltimore, Maryland 21201, USA. Correspondence and requests for
materials should be addressed to B.M.B. (email: brian-baker@nd.edu).
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ARTICLE
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R
ecognition of peptide antigens by the ab T cell receptor
(TCR) underlies cellular immunity. TCRs recognize peptides bound and presented by major histocompatibility
complex (MHC) proteins, using multiple complementaritydetermining region (CDR) loops to contact the composite
peptide-MHC surface (pMHC). A notable aspect of the TCR–
pMHC interaction is that the distribution of binding energy
within the interface has significant functional implications. The
immune response is directed towards the peptide, yet TCRs
invariably contact both peptide and MHC. It is commonly
expected that contacts between the TCR and peptide should be
stronger than those between TCR and MHC to ensure antigen
specificity. Within this framework, the various CDR loops have
often been ascribed ‘roles’ in TCR recognition, with weak
recognition of the MHC attributed to the germline-encoded
CDR1 and CDR2 loops and recognition of the peptide attributed
to the hypervariable CDR3 loops. While this view logically pairs
the diverse and genetically conserved regions of the TCR–pMHC
interface (peptide with CDR3; MHC with CDR1/CDR2), such
simplifying distinctions are rarely evident in TCR–pMHC
crystallographic structures1.
Several studies have attempted to address the energetic
contributions of different interfacial regions to TCR–pMHC
binding through mutagenesis, and alanine scans of both receptor
and ligand have been performed2–5. Varying conclusions from
these studies together with the growing number of TCR–pMHC
structures have indicated that the energetic contributions of
regions will likely vary among TCR–pMHC interfaces6. Thus,
alanine scans have been followed with more targeted
substitutions, aiming to identify trends that might yield insight
into phenomena such as MHC restriction, peptide specificity or
TCR crossreactivity.
However, while single mutagenesis is useful for examining
regions that influence binding and specificity, single mutations
cannot probe the strengths of pairwise interactions and provide
poor estimates of the contributions of sidechains to binding affinity.
These caveats have been reviewed in detail7, and in one case
resulted in incorrect conclusions regarding TCR specificity8. More
direct measurements of energetic contributions to binding are
obtainable from double-mutant cycles, which can account for both
structural and energetic responses to mutations and permit the
direct probing of the strengths of interactions between sidechains9.
Here, we utilize double-mutant cycles to dissect the interface
between the ab TCR A6 and its best studied ligand, the Tax
peptide presented by the class I MHC HLA-A*0201 (HLA-A2).
The significant amount of structural, biophysical and functional
data available for the A6 TCR provided context in which to
interpret the measurements. For comparison, select measurements are repeated with two additional TCR–pMHC pairs. Our
observations, several of which conflict with widely held generalities regarding TCR recognition, shed new light on the origin of
TCR-limited specificity and MHC restriction, two defining
features of TCR recognition for which a variety and sometimes
competing explanations have been offered. Conclusions applicable to TCR recognition in general relate to the role of
hypervariable loop flexibility in promoting limited rather than
tight specificity, and that TCR specificity and MHC restriction
can be inextricably linked, the latter reflecting the fact that the
TCR must engage a composite peptide/MHC ligand with tightly
coupled structural properties.
Results
Double-mutant cycles in the A6 TCR—Tax/HLA-A2 interface.
We began by identifying all interacting sidechains in the interface
between the A6 TCR and Tax/HLA-A2 (ref. 10). There are 21 such
2
pairs, involving 16 amino acids of the TCR, 10 of HLA-A2 and 3 of
the peptide. The interaction free energy (DG°int ) between each pair
was measured via double-mutant cycles. Including controls, 38
cycles in the A6-Tax/HLA-A2 interface were performed. Eight
additional cycles were performed in the interfaces between the B7
TCR and Tax/HLA-A2 and the DMF5 TCR and MART-126(27L)-35/
HLA-A2. The data were collected and analysed using a strategy in
which all four measurements of a cycle were performed in a single
surface plasmon resonance experiment and the data fit globally.
This approach substantially increased sensitivity and improved
accuracy and reproducibility compared with the traditional
approach in which cycles are constructed from independently
measured values.
A representative double-mutant cycle is shown in Fig. 1a, and the
results of all cycles are listed in Supplementary Tables S1 and S2.
Errors in the DG°int measurements ranged from ±0.1 to
±0.5 kcal mol 1, with an average error of ±0.1 kcal mol 1.
Reproducibility was excellent: each cycle included two replicates,
and seven cycles were performed at least two additional times. In all
but one case the DG°int values for repeated cycles were identical
within error, and in the single outlying case the values were weak.
In all but one easily rationalized case, cycles repeated with different
amino acids (for example, separate cycles with alanine and
phenylalanine substituted for pTyr5) yielded identical conclusions.
Control cycles performed between residues whose sidechain atoms
were far apart and not poised to interact yielded DG°int values of
zero within error. The average DG° for the interaction between
wild-type A6 and Tax/HLA-A2 was 7.6±0.1 kcal mol 1, in
excellent agreement with values determined previously11,12.
The DDG° values resulting from single mutations were poorly
correlated with the DG°int values involving the same sites (Fig. 1b).
Generally, the most destabilizing single mutations were
involved in the most favourable interactions, but quantitatively
the DDG° values from the single mutations were poor predictors
of the strengths of these interactions. We found several cases
where single mutations had significant effects on binding, yet
the mutated sites participated in interactions that were either
negligible or weakly unfavourable, or vice versa. Two examples
are highlighted in Fig. 1b: the hydrogen bond between Thr98a of
A6 and Arg65 of HLA-A2 is significantly stronger than predicted
by the DDG° of the T98aA mutation, and the van der Waals
interaction between Gln30a of A6 and Tyr159 of HLA-A2 is
almost negligible, despite the large DDG° for the Y159A
mutation.
Interactions at the periphery dominate peptide contributions.
In the A6-Tax/HLA-A2 structure, eight sidechains of the TCR
interact with three of the peptide. The majority of the interactions
are made with pTyr5, which lies at the centre of the interface and
is accommodated in a pocket formed by the TCR a and b chains
(Fig. 2a). Two hydrogen bonds are formed to the tyrosine
hydroxyl, one between Ser31 of CDR1a and one with Arg95 of
CDR3b. Only the hydrogen bond with Ser31a was significant
(DG°int of 0.9 kcal mol 1). The strength of the hydrogen bond
with Arg95b was negligible at 0.2 kcal mol 1, likely owing to
the entropic cost of ordering the flexible CDR3b loop13. The
remaining interactions with pTyr5 ranged from weakly
favourable to unfavourable. Summing the various DG°int values
leads to a negligible contribution of 0.1 kcal mol 1 for the
interactions with the tyrosine sidechain. The data thus indicate
that contacts to tyrosine 5 contribute a negligible amount to the
affinity of A6 towards Tax/HLA-A2, despite the position of the
sidechain in the centre of the interface. Note that summation of
the DG°int values assumes additivity between the double-mutant
cycles, an assumption subjected to caveats as described below.
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NATURE COMMUNICATIONS | DOI: 10.1038/ncomms2948
a
b
WT TCR – WT pMHC
1.0
1
T93αA TCR – WT pMHC
T93αA TCR – WT pMHC
ΔG° = –6.60 ± 0.03
0.6
WT TCR – pY5A pMHC
0.4
WT TCR – pY5A pMHC
ΔG° = –5.79 ± 0.02
0.2
T93αA TCR – pY5A pMHC
ΔG° = –4.53 ± 0.04
–1
ΔG°int= 0.3 ± 0.1 kcal mol
ΔG°int (kcal mol–1)
Fractional saturation
A6 Q30α – HLA-A2Y159
0.8
WT TCR – WT pMHC
ΔG° = –7.55 ± 0.03
–1
–2
–4
0
20
40
60
μM pMHC
80
A6 T98α
–3
T93αA TCR – pY5A pMHC
0.0
HLA-A2
Y159
0
100
A6 T98α – HLA-A2 R65
R 2 = 0.34
RMSD = 0.8 kcal mol–1
–1
0
1
2
ΔΔG° (kcal mol–1)
3
4
Figure 1 | Double-mutant cycles in the A6-Tax/HLA-A2 interface. (a) Data for all four interactions defining a double-mutant cycle (in this example, the A6
T98a—Tax/HLA-A2 pY5 interaction) were collected in one experiment, in which duplicate concentration series of wild-type or mutant pMHC were
injected over adjacent flow cells coupled with wild-type or mutant TCR. All eight data sets were fit globally to a model in which the surface activities for the
four data sets over the wild-type TCR surface (indicated with red) and the four data sets over the mutant TCR surface (indicated with blue) were shared
parameters. Construction of the double-mutant cycle and the resulting interaction free energy for the T98a—pY5 interaction are shown to the right
of the plot. (b) For cycles in the A6-Tax/HLA-A2 interface, plotting the free energy of interaction of each residue (DG°int ) versus the effect of its mutation on
the binding free energy (DDG°) showed that while the most destabilizing mutations were generally involved in the strongest interactions, the results
were poorly correlated. Two data points that illustrate the poor correlation are highlighted: the hydrogen bond between Thr98a of A6 and Arg65 of HLA-A2
is stronger than predicted by the DDG° of the T98aA mutation, and the van der Waals interaction between Gln30a of A6 and Tyr159 of HLA-A2 is
almost negligible, despite the large DDG° for the Y159A mutation. Error bars reflect standard parameter error from the global fits of eight data sets.
a
T93α
T93α
R95β
1β
1β
3α
3α
+0.3 –0.2
+0.3
P103β
S31α
–0.9
b
R95β
–0.9
1α
S100α
+0.7
Y5
L98β
–1.7
3β
–1.6
1α
Y5
3β
L98β
–1.7
–0.4
E30β
3β
P103β
S31α
3β
–0.4
E30β
–0.2
S100α
+0.7
Y8
–1.6
Y8
Figure 2 | Cross-eyed stereo views of the interactions between the position 5 and position 8 tyrosines of the Tax peptide and sidechains of
the A6 TCR. (a) Engagement of pTyr5 at the centre of the interface by sidechains of CDR1a, CDR3a and CDR3b contributes little to TCR affinity.
Interactions between sidechains are highlighted by red lines, and the free energies of each interaction are indicated in units of kcal mol 1. (b) In contrast
with pTyr5, engagement of pTyr8 by sidechains of CDR1b and CDR3b contributes significantly to TCR affinity.
However, the results explain the ability of T cells expressing A6 to
recognize targets presenting Tax variants with a wide range of
amino acids substituted for pTyr5, including alanine and bulky
non-natural amino acids14,15.
The sidechain of pLeu1 forms a single van der Waals
interaction with the sidechain of Gln30 of CDR1a. The Q30A
variant of the A6 a chain expressed poorly, prohibiting a cycle
with alanine at this position. However, substitutions with leucine
and valine could be made, both yielding an almost negligible
DG°int of þ 0.2 kcal mol 1. Consistent with this result, A6 T cells
are widely tolerant of substitutions to pLeu1 (ref. 14).
As opposed to pTyr5, pTyr8 is at the periphery of the interface
and only interacts with two sidechains of A6. A hydrogen bond is
formed between the pTyr8 hydroxyl and the sidechain of Glu30
of CDR1b, and van der Waals contacts are formed between the
tyrosine ring and the sidechain of Leu98 of CDR3b. Both
interactions were found to be unusually strong (Fig. 2b): the DG°int
for the pTyr8–Glu30b hydrogen bond was measured as
1.7 kcal mol 1, and the DG°int for the interactions with Leu98b
was measured as 1.6 kcal mol 1. The hydrogen bond measurement was repeated twice, first in the background of an
affinity-enhancing modification to the pTyr5 sidechain16, and
second with a phenylalanine substitution at position 8. Both
measurements yielded results identical within error to the first.
The strength of the hydrogen bond likely arises because both
pTyr8 and Glu30b remain solvent-exposed after forming the
TCR–pMHC complex, minimizing the desolvation penalty that
occurs upon hydrogen bond formation17.
Overall, the data indicate that the sidechain of pTyr8
dominates the peptide side contribution to TCR-binding affinity.
This dominance is reflected in functional measurements with A6
T cells, which tolerate substitutions to the sidechain of tyrosine 8
poorly14. Further, unlike interactions to the centre of the peptide,
the interactions between the TCR and pTyr8 are conserved
across all ten crystal structures of A6 bound to different peptide/
HLA-A2 complexes10,12,13,15,16,18,19.
Interactions with CDR3a dominate a1 helix contributions.
Five sidechains of the A6 CDR1a and CDR3a loops interact with
a range of sidechains across the HLA–A2 a1 helix. The DG°int
values were dominated by extremely favourable interactions
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ARTICLE
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a
3α
3α
Q30α
Q30α
1α
D99α
W101α
–0.7
+0.6
–2.8
D99α
W101α
D26α
–2.9
+0.5
–0.5
A69 R65
1α
T98α
T98α
–0.7
–2.8
+0.6
D26α
–2.9
+0.5
–0.5
R65
A69
K66
K66
E58
E58
b
3β
HV4α
2α
P103β
3β
Y50α
1α
1α
–0.7
–0.7
R27α
–0.6
Q155
HV4α
2α
P103β
Y50α
Q30α
K68α
–0.9
+0.1
+0.5
N52α
–0.7
T163
+1.0
–0.6
Q155
R27α
Q30α
K68α
–0.9
–1.1
+0.1
E166
+0.5
–0.7
N52α
+1.0
–1.1
T163
E166
R170
R170
W167
W167
Y159
Y159
Figure 3 | Cross-eyed stereo views of the interactions between sidechains of the HLA-A2 a1 and a2 helices and those of the A6 TCR. (a) Recognition of
the HLA-A2 a1 helix by sidechains of CDR1a and CDR3a is dominated by interactions between Arg65 and the sidechains of Thr98a and Asp99a of the
CDR3a loop. The remainder of the interactions range from moderately unfavourable to moderately favourable. Interactions between sidechains are
highlighted by red lines, and the free energies of each interaction are indicated in units of kcal mol 1. (b) Recognition of the HLA-A2 a2 helix by sidechains
of CDR1a, CDR2a, CDR3b and HV4a proceeds via a range of moderately favourable to moderately unfavourable interactions.
between the sidechains of Thr98 and Asp99 of CDR3a and
Arg65 of the HLA-A2 a1 helix (Fig. 3a). The strength of the
hydrogen bond between Thr98a and Arg65 was measured as
2.8 kcal mol 1. The salt bridge between Asp99a and Arg65
was even stronger, with two independent DG°int measurements of
3.4 and 3.0 kcal mol 1. These measurements could only be
made with the aid of affinity-enhancing substitutions in CDR3b
(ref. 20). However, a cycle could be performed without using an
altered CDR3b by mutating position 99 to an asparagine rather
than alanine. In that case, the DG°int value was still an
exceptionally strong 2.5 kcal mol 1. Engagement of Arg65
thus contributes a remarkable degree of favourable binding free
energy: assuming additivity between the cycles, the total DG°int
amounts to 5 to 6 kcal mol 1. The interactions between
Arg65 and residues of the hypervariable CDR3a loop account for
the largest energetic contributions measured in the A6-Tax/HLAA2 interface. The substantial contributions may reflect an optimal
electrostatic environment together with the reduced desolvation
penalty required for burial of an arginine21.
The remaining interactions between the TCR and the a1 helix
of HLA-A2 ranged from moderately favourable to weakly
unfavourable. The two interactions between the germline CDR1a
loop and the a1 helix were unfavourable, with DG°int values of
þ 0.5 kcal mol 1 (Asp26a—Glu58) and þ 0.6 kcal mol 1
(Gln30a—Lys66).
Interactions with the a2 helix are at best moderate. Six sidechains of the A6 TCR, including those from CDR1a, CDR2a,
HV4a and CDR3b, interact with eight sidechains across the
4
HLA–A2 a2 helix (Fig. 3b). Unlike the interactions with the
peptide or the a1 helix, the interactions between the TCR and the
a2 helix were not dominated by highly favourable interactions,
but rather had DG°int values distributed between moderately
favourable and moderately unfavourable. The interactions
between sidechains of CDR1a and the a2 helix were all
unfavourable, with DG°int values of þ 0.1, þ 0.5 and
þ 1.0 kcal mol 1. These repulsive interactions were balanced by
favourable interactions between sidechains of CDR2a and the a2
helix, consisting of hydrogen bonds with strengths of 1.0 and
0.7 kcal mol 1.
The interaction between Tyr50 of CDR2a and Gln155 of the
a2 helix is of interest given descriptions of conserved interactions
occurring between germline loops of TCRs and the a helices of
MHC proteins22,23. The A6 TCR shares the Va 12-2 domain with
two other TCRs that have been crystallized with peptide/HLA-A2
complexes24,25. Although there are no conserved contacts
between the TCRs and HLA-A2 in these structures, there is a
shared pattern of interactions involving Tyr50 of CDR2a and
Gln155 (ref. 24). The interaction between Tyr50a and Gln155 in
the A6-Tax/HLA-A2 was indeed favourable, although only
moderately so, with a DG°int of 0.6 kcal mol 1. The adjacent
hydrogen bond between Asn52 of CDR2a and Glu166 of the
HLA-A2 a2 helix was more favourable at 1.1 kcal mol 1,
but this hydrogen bond is not conserved in the three Va 12-2
TCR-peptide/HLA-A2 interfaces24.
The interactions between the HV4a loop and HLA-A2,
involving electrostatic interactions between Lys68a and Thr163
and Glu166, were moderate, with interaction free energies of
0.9 and 0.7 kcal mol 1, respectively. The sole interaction
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between CDR3b and the a2 helix, between Pro103b and Gln155,
was also moderate, with a DG°int of 0.7 kcal mol 1.
Contributions tabulated by interface component. The DG°int
values from the double-mutant cycles in the A6-Tax/HLA-A2
interface are arranged according to CDR loop in Fig. 4. The
extremely favourable interactions between sidechains of CDR3a
and the HLA-A2 a1 helix are especially clear, as are the favourable interactions between sidechains of the two CDR1 loops and
the peptide. Also of interest are the opposing interactions between
the peptide and CDR3a (unfavourable), and the peptide and
CDR3b (favourable). Note that the summation in Fig. 4 assumes
additivity with caveats as discussed below. However, as noted
earlier the results explain a wealth of functional data, and the
distribution in Fig. 4 agrees well with computational calculations
on the distribution of energy in the A6-Tax/HLA-A2 interface26.
In addition to global effects, including changes in flexibility
that propagate away from the binding sites27 and the loss in
rotational/translational entropy that occurs upon binding
(estimated at 4–6 kcal mol 1)28,29, a notable component
missing from our analysis is interactions with backbone atoms,
which cannot be probed by double-mutant cycles. Within the
A6-Tax/HLA-A2 interface there are three backbone-mediated
hydrogen bonds, all to the peptide (Fig. 4c). Two are between the
carbonyl oxygen of pGly4 and Ser100 of CDR3a. The third is
between the carbonyl oxygen of pLeu2 and Gln30 of CDR1a. The
majority of hydrogen bonds within protein structures have been
found to be modestly favourable (a recent analysis of doublemutant cycles found an average strength of 0.5 kcal mol 1
(ref. 30)). Our analysis thus likely underestimates the favourable
contributions of CDR1a and CDR3a to recognition of the Tax
peptide, but not to an extent that would alter our conclusions.
Shared interactions between Va 12-2 TCRs and HLA-A2 are weak.
As noted above, Tyr50 of CDR2a and Gln155 of HLA-A2 share a
pattern of interactions in three Va 12-2 TCR-peptide/HLA-A2
interfaces29,30. We therefore probed the interaction between
b
–4
CDR1α
–3
Analysis of the B7 TCR supports conclusions drawn from A6.
The B7 TCR also recognizes the Tax peptide presented by HLAA2, allowing us to ask to what extent observations made with A6
are shared with B7. As with A6, the B7 TCR accommodates the
pTyr5 sidechain in a pocket formed by the CDR3a and CDR3b
loops. However, the two pockets have opposing electrostatics: the
DMF5 TCR
Y50α
Y50α
2α
–0.6
N52α
Q155
N52α
Q155
–1.1
–0.3
E166
E166
Figure 5 | Comparison of CDR2a—HLA-A2 interactions conserved in two
Va 12-2 TCR interfaces. In the DMF5 interface, the interaction between
Tyr50 of CDR2a and Gln155 is weakly stabilizing, with a DG°int of
0.6 kcal mol 1. This is identical to the strength of the Y50a–Q155
interaction in the A6 interface. The interaction between Asn52 of CDR2a
and Glu166 is weak in the DMF5 interface, with a DG°int of 0.3 kcal mol 1.
The interaction is much stronger in the A6 interface, with a DG°int of
1.1 kcal mol 1.
α1 Helix
α2 Helix
Peptide
+1.1 ± 0.1
+1.6 ± 0.2
–0.7 ± 0.3*
CDR2α
CDR3α
A6 TCR
2α
–0.6
c
–1.7 ± 0.2
3α
–2
–7.0 ± 0.6
1α
+1.0 ± 0.1*
–1
S100α
p
0
p
HV4α
p
p
–1.6 ± 0.2
Y5
p p p p p
CDR1β
Q30α
–1.7 ± 0.4
2α
–7.5
P103 – Q155
L98 – pY8
P103 – pY5
E30 – pY8
HV4α 1β
R95 – pY5
K68 – T163
K68 – E166
W101 – A69
D99 – K66
3α
S100 – pY5
D99 – R65
T93 – pY5
T98 – R65
N52 – E166
S31 – pY5
Y50 – Q155
Q30 – pL1
1α
Q30 – Y159
R27 – R170
2
D26 – E58
1
R27 – W167
Interaction free energy (kcal mol–1)
a
Tyr50a and Gln155 in the interface between the Va 12-2 TCR
DMF5 and its MART-126(27L)-35/HLA-A2 ligand. The strength of
this interaction was identical to that measured in the A6 interface,
with a weak DG°int of 0.6 kcal mol 1 (Fig. 5). We also probed
the interaction between Asn52a and Glu166 in the DMF5
interface, as these sidechains also interact in both the A6 and
DMF5 interfaces, although the hydrogen bond is not present with
DMF5. Consistent with the structural differences, the strength of
the interaction was weaker in the DMF5 interface, with a DG°int of
only
0.3 kcal mol 1 with DMF5 (compared with
1.1 kcal mol 1 with A6).
CDR2β
L2
CDR3β
–0.7 ± 0.1
–2.4 ± 0.5
3β
0
+7.5
kcal mol–1
Figure 4 | Summary of the double-mutant cycle results for the A6 TCR and the contributions of various interfacial regions to binding. (a) Results of
each cycle grouped by CDR loop. Cycles involving a peptide sidechain are indicated with a ‘p’ in the graph. Error bars reflect standard parameter error
from the global fits of eight data sets. (b) Contributions to the overall binding free energy of the A6 TCR tabulated by interfacial region. As discussed in the
text and as indicated within an asterisk, the contributions of CDR1a and CDR3a are likely an underestimate due to the presence of hydrogen bonds from
residues of these loops to the backbone of the Tax peptide. In panels a and b, the interaction free energies are coloured according to the scale at the
bottom, with blue reflecting favourable interactions and red unfavourable. Errors in panel b reflect propagated error from values in panel a and
Supplementary Tables S1 and S2. (c) Hydrogen bonds involving backbone atoms in the interface between the A6 TCR and Tax/HLA-A2.
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a
b
c
1α
3β
3α
1α
Y104β
Y5
D30α
–0.2
–3.8
E30β
–0.8
R65
–1.6
E94α
–0.7
Y8
Figure 6 | Select interactions in the B7-Tax/HLA-A2 interface for comparison with similar interactions in the A6-Tax/HLA-A2 interface.
(a) Engagement of pTyr5 of the Tax peptide is more substantive with B7 than with A6, but this is not attributable to hydrogen bonding. A double-mutant
cycle between pTyr5 and Asp30 of CDR1a yielded an interaction free energy of 0.2 kcal mol 1 with phenylalanine substituted for pTyr5. However, a cycle
with alanine yielded a much more substantial value of 3.8 kcal mol 1. The interaction between pTyr5 and Tyr104 of CDR3b yielded a moderate
interaction free energy of 0.8 kcal mol 1. (b) The hydrogen bond between Glu30 of CDR1b and pTyr8 of the Tax peptide is strong in the B7 interface,
with an interaction free energy of 1.6 kcal mol 1. An identical interaction with the same strength is formed in the interface with A6 (Fig. 2b). (c) The
hydrogen bond between Arg65 of the a1 helix and Glu94 of CDR3a in the interface with the B7 TCR is moderate, with an interaction free energy of
0.7 kcal mol 1. Arg65 also makes a bifurcated hydrogen bond with the carbonyl oxygen of Glu94, which as discussed in the text is also predicted to be
stabilizing.
pocket is positively charged in A6, whereas in B7 it is negatively
charged owing to the presence of Asp30 of B7 the CDR1a loop.
The interaction between Asp30a of B7 and pTyr5 was found to
be very strong, with a DG°int of 3.8 kcal mol 1 for a doublemutant cycle using alanine at position 5 (Fig. 6a). However, this
cannot be attributable to the hydrogen bond to Asp30a, as a
cycle with phenylalanine yielded a weak DG°int of only
0.2 kcal mol 1. The interaction between Tyr104 of CDR3b
and pTyr5 was stronger, with a DG°int of 0.8 kcal mol 1.
Although these cycles do not probe the entirety of B7 contacts to
pTyr5, they are nonetheless instructive: engagement of pTyr5 by
A6 is negligible, whereas it seems very favourable with B7. As the
difference cannot be attributed to hydrogen bonds, it may arise
from differences in packing and flexibility between the two TCRs,
resulting in an entropic penalty with A6 not present with B7. This
interpretation is supported by the specificities of the two TCRs:
A6 tolerates a wide range of modifications to the centre of the
peptide, yet B7 will only recognize targets with a tyrosine or a
phenylalanine at position 5 (ref. 14).
The B7 TCR utilizes the same Vb 13-2 gene segment as A6,
and the A6 and B7 CDR1b loops are positioned similarly over the
peptide carboxy terminal end31. A double-mutant cycle between
pTyr8 and Glu30b of B7 yielded a DG°int of 1.6 kcal mol 1,
identical within error to that measured between pTyr8 and
Glu30b of A6 (Fig. 6b). Unlike the A6 TCR, the B7 CDR3b loop
does not interact with pTyr8, which may explain the greater
tolerance of B7 T cells to substitutions at position 8 (ref. 14).
Nonetheless, the presence of a strongly favourable hydrogen bond
from CDR1b to pTyr8 in both interfaces indicates that both TCRs
arrive at the same germline loop-driven solution for optimizing
electrostatic interactions with the peptide.
Lastly, we examined engagement of Arg65 on the HLA-A2 a1
helix by B7. In the B7 complex, Arg65 forms a salt bridge with
Glu94 of CDR3a, mimicking somewhat the salt bridge formed
between Arg65 and Asp99 of the A6 CDR3a loop. However,
compared with the highly favourable interaction formed in the
A6 complex, the strength of the salt bridge with B7 was more
modest, with a DG°int of only 0.7 kcal mol 1. The differences
between A6 and B7 likely reflect the suboptimal arrangement
between the sidechains in the B7 interface (Fig. 6c). However,
with B7, Arg65 also forms two hydrogen bonds with the carbonyl
oxygen of Glu94a, which will likely provide additional favourable
free energy. The existence of a favourable interaction between
Arg65 and CDR3a of B7 is consistent with the observation that
the B7 TCR does not recognize Arg65 mutants in functional
6
assays5. Thus, both TCRs utilize CDR3a to productively engage
Arg65 of the HLA–A2 a1 helix.
Discussion
Owing to their usual location in the centre of the interface, the
central sidechains of a peptide are often assumed to be the focal
point in antigen-specific TCR recognition. This is not the case
with the A6 TCR: despite being accommodated in a central
pocket with multiple hydrogen bonds, engagement of the
sidechain of pTyr5 of the Tax peptide contributes little to
binding. This observation helps explain a key aspect of A6
crossreactivity: the receptor tolerates significant alterations at the
centre of the peptide14,15, with the CDR3b loop changing its
conformation significantly with different peptides13,15,16,18,19.
The high intrinsic flexibility of the A6 CDR3b loop13 likely
underlies the overall lack of stabilizing interactions between
CDR3b and the peptide centre, as the entropic cost of ordering
the loop will offset enthalpic gains from interatomic interactions.
Crossreactivity in the A6 TCR can thus be attributed to a
combination of flexibility and thermodynamic ambivalence (or
entropy/enthalpy compensation) at the centre of the interface.
This point is further established by the measurements with the B7
TCR: unlike A6, accommodation of pTyr5 by the B7 TCR is
favourable. Yet the B7 TCR is less accommodating to
substitutions at this position than A6 (ref. 14), and evidence
suggests that the B7 hypervariable loops are less flexible than
those of A6 (ref. 32).
Although flexibility and thermodynamic ambivalence at the
interface centre promotes A6 crossreactivity, this does not
exclude a role for the peptide centre and its interactions with
the TCR in defining some degree of specificity. A weak (or
neutral) interaction is better than an unfavourable interaction,
and the chemistry of the CDR3a/CDR3b loops and their
accessible conformations will limit what sidechains will be
tolerated. For example, A6 tolerates charged amino acids at
position 5 of the peptide poorly14. Flexibility and thermodynamic
ambivalence thus provides a mechanism for limited
crossreactivity (or equivalently, limited specificity), a hallmark
of T cell recognition. The TCR structural database indicates that
TCR CDR loop flexibility is concentrated in the hypervariable
loops33, indicating this strategy may be commonly utilized.
In contrast with the peptide centre, pTyr8 near the C-terminal
end dominates the peptide sidechain contributions to the binding
of A6, demonstrating the impact peripheral peptide residues
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NATURE COMMUNICATIONS | DOI: 10.1038/ncomms2948
can have in TCR recognition. The interactions between the TCR
and pTyr8 are a strong element of peptide specificity, as a tyrosine
at position 8 is conserved in all known A6 agonists, and the
interactions with the pTyr8 sidechain are among the few
TCR–peptide interactions that are conserved in all ten crystal
structures of A6 bound to a pMHC10,12–16,18,19. Comparing
positions 5 and 8, the picture that emerges is that from a
free-energy perspective, pTyr8 acts as a ‘lynchpin’ for binding
of the A6 TCR, whereas pTyr5 is more of a neutral chemical
‘dollop’ around which the TCR moulds. It is notable that a
significant amount of favourable energy resulting from engaging
pTyr8 comes from the germline-encoded CDR1b loop,
demonstrating the importance germline loops can have in
determining antigen specificity. The observation that the B7
TCR utilizes CDR1b to make a similar stabilizing interaction with
pTyr8 reinforces this point.
Another striking observation is the dominance of the
interactions between the A6 hypervariable CDR3a loop and the
HLA-A2 a1 helix. This finding demonstrates conclusively that
TCR hypervariable loops can have a significant influence on
MHC restriction. Yet given the strength of these interactions, how
is it that the A6 TCR maintains sufficient peptide specificity to
have escaped the filtering process of negative selection?
T98α
Crucially, the interactions between CDR3a and Arg65 cannot
be considered in isolation, as their formation is dependent upon
the peptide. In the bound state, the conformation the flexible A6
CDR3a loop adopts is dependent on the need to avoid steric
clashes with other sidechains of HLA-A2 (ref. 13). However, this
conformation can only be reached because of the glycine at
peptide position 4: owing to steric crowding, any other amino
acid would prevent CDR3a from adopting its bound
conformation and making the crucial interactions with Arg65
(Fig. 7). Indeed, A6 is intolerant of any amino acid other than
glycine at position 4 (ref. 14). The peptide and MHC specificity of
the A6 TCR are therefore inextricably linked. Although the extent
to which similar results apply to other TCRs is unknown, this
finding underscores the limitations of perspectives that consider
MHC and peptide specificity as arising through independent
mechanisms.
The co-dependency of peptide and MHC specificity in the A6
TCR relates to the observation that the interactions between the
germline-encoded loops and the MHC a1/a2 helices range from
only moderately favourable to moderately unfavourable. This
includes germline–MHC interactions that are shared in interfaces
formed with multiple Va 12-2 TCRs29,30. The extent to which
evolution has influenced interactions between TCR germline
CDR3α in bound A6
CDR3α in free A6
D99α
T98α
carbonyl
R65
Steric clash
Binding with CDR3α
conformational change
D99α
R65
T98α carbonyl
T98α
pG4
pG4
Binding prohibited
CDR3α in bound A6
D99α
R65
T98α
T98α carbonyl
Steric clash
P4 ≠ Gly
Figure 7 | The peptide and MHC specificity of the A6 TCR are inextricably linked. For TCR binding to proceed, the CDR3a loop must move from its
position in the unbound structure to its position in the bound13. The conformational change is driven in part by a steric clash that would occur between the
carbonyl oxygen of Thr98a and the sidechain of Arg65 (left panel). This conformational change permits formation of strongly stabilizing hydrogen
bonds from Thr98a and Asp99a to Arg65 (top right). However, if an amino acid other than glycine were present at peptide position 4, a steric clash would
occur between the Thr98a carboxyl and the position 4 b carbon (bottom right), preventing the loop from adopting its bound-state conformation and
interacting with Arg65. Thus, formation of the strong interactions between CDR3a and Arg65 is dependent on the presence of glycine at peptide position 4.
Glycine at position 4 is conserved in all known agonists for the A6 TCR.
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ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms2948
loops and MHC proteins is controversial34,35. As discussed above
though, weak interactions do not necessarily imply a lack of
specificity. One interpretation consistent with our data is that
rather than selecting for residues that will strongly stabilize the
interaction of a TCR with an MHC, evolution has selected for
sequences and conformations that can add some degree of
stabilization when germline loops are docked alongside the MHC
a helices, but can also ‘give’ when stronger interactions can be
made elsewhere35,36. An evolutionarily selected permissiveness
could explain not only the lack of strongly favourable germline–
MHC contacts in the interfaces explored here, but also
observations of non-canonical TCR-binding modes37, the
finding that changes to a peptide alone can alter receptorbinding geometry24, the impact different CDR3 loops can have on
TCR–MHC contacts38 and the observation that TCRs that have
not undergone selection can engage non-MHC targets39. It can
also explain functional consequences of CDR2a mutations40, as
these will perturb the energetic balance that leads to
permissiveness. Such permissiveness may be a strategy for
ensuring that any given TCR is able to best optimize its
interactions with the composite peptide/MHC surface, and
provided it is still able to engage with a conducive geometry22,
initiate T cell signalling.
Methods
Proteins and peptides. TCRs and MHC proteins were refolded from bacterially
expressed inclusion bodies according to established procedures11. TCRs utilized an
engineered disulphide bond across the constant domains to ensure stability41.
Amino acids targeted for mutations were identified from the TCR–pMHC
structures using a 4 Å cutoff. Mutations were generated from the wild-type
plasmids using PCR mutagenesis and confirmed by sequencing, or in some cases
were available from previous studies5,8,42. Peptides were either synthesized inhouse via solid-state synthesis using an ABI 433A instrument, or synthesized and
purified commercially (Genscript).
Double-mutant cycles. In a double-mutant cycle, the interaction free energy
between two amino-acid sidechains is determined via four measurements. The first
measures the DG° for the interaction between the two wild-type proteins. The
second measures the effect of a single mutation on binding free energy (DDG°1 ) and
the third measures the effect of a second mutation (DDG°2 ), typically at a position
that interacts with the site of the first. The fourth measurement measures the
effect of both mutations simultaneously (DDG°1;2 ). The measurements refer to a
cycle as shown in Fig. 1a. If there is no interaction (or coupling) between the two
mutated sites, then the consequences of both mutations simultaneously is equal to
the sum of the consequences of first and second mutations alone. Subject to the
caveats described below, the extent to which this relationship does not hold defines
the free energy of interaction between the two sidechains, that is:
DG°int ¼ DDG°1;2 DDG°1 DDG°2
ð1Þ
DG°int ¼ DG°1;2 DG°1 DG°2 þ DG°WT
ð2Þ
which simplifies to:
experiments, as it allows the determination of highly accurate DDG° and DG°int
values. Constraining the surface activities to values common to multiple data sets in
which one has higher affinity than the other greatly increases the affinity range of
surface plasmon resonance43, an advantage important for weak interactions
involving mutants. Global fitting of multiple data sets reduces the influence of data
set variation, enforces consistency and reduces parameter correlation44. Lastly,
when the same sensor surfaces and dilution series are utilized in a titration,
systematic errors such as instrumental noise and inaccuracies in protein
concentration cancel when differences in free energies (that is, DDG° and DG°int
values) are computed. This last point is crucial, as noise and concentration errors
contribute significantly to the error and uncertainty in low affinity measurements,
as they have a disproportionate impact on regions of a binding curve that
show large curvature. Note that because of this, in some cycles the measurements of
DDG° and DG°int may be more accurate than the individual DG° measurements
comprising it, a caveat that has no impact on our results.
In almost all cases, the mutations in each double-mutant cycle were to alanine.
As indicated in Supplementary Tables S1 and S2, exceptions were leucine and
valine for Q30a of A6 (as the Q30aA mutant expressed poorly), asparagine for
D99a of A6 (to verify the strength of the interaction with R65 as described below),
both alanine and phenylalanine for pY5 and pY8 (to investigate contacts to the
tyrosine hydroxyl versus contacts to the aromatic ring) and glycine for A69 of
HLA-A2. In addition, cycles involving K66 of HLA-A2 were performed in the
background of the E63Q mutation to avoid complications arising from the complex
electrostatic environment at this position8. In B7, both alanine and phenylalanine
were substituted for pY5 to explore hydrogen bonding versus packing. Also
with B7, we utilized asparagine for Asp30a, as the D30aA mutant expressed poorly.
With the A6 TCR, five cycles yielded data in which the affinity of one or more
interactions was too weak to yield an accurate value of DG°int (cycles in which
Asp99a was mutated to alanine and three of four cycles in which pPhe8 was
replaced with alanine or phenylalanine). These cycles were repeated with the highaffinity TCR variant A6 c134 (CDR3b: 99MSAE102)20 or the fluorinated highaffinity Tax peptide variant Y5FFF16. The Y5FFF substitution has been shown
previously to act independently of other substitutions in the interface, and select
cycles performed with and without the A6 c134 variant yielded the same
conclusions. Further, as shown in Supplementary Tables S1 and S2 and described
in the main text, the conclusions from the A6 D99a—HLA-A2 R65 and A6 E30b—
Tax pY8 cycles with the high-affinity variants were the same when performed in
the wild-type background but instead substituting asparagine for D99 and alanine
for pY8. The experiments with the DMF5 TCR utilized the high-affinity D26aY/
L98bW variant27.
In some instances (for example, Fig. 4b), we consider the effects of doublemutant cycles in groups, a consideration that implicitly assumes additivity between
the measurements. The extent to which additivity is permissible depends upon
how well the chief assumptions in double-mutant cycles hold, that is, that the
mutations are structurally independent and that any perturbations resulting from
mutations are the same in the two single-mutant interfaces and the double-mutant
interface9. While these necessarily limiting assumptions are unlikely to be valid in
every instance, they have been supported when explicitly explored45. Support here
can be found in the cases where very similar or even identical DG°int measurements
were obtained when cycles were repeated using different amino acids at a single
position (that is, Q30a-pL1, S31a-pY5, D99a-R65, E30b-pY8 and R95b-pY5
in the A6 interface). These measurements probed a range of environments,
including those with complex electrostatics (D99a-R65) and high intrinsic
flexibility (R95b-pY5).
Error propagation of DG°int values was performed using standard statistical
error propagation methods11. When multiple measurements were available, the
values in the text and figures were the averages of the multiple measurements.
where DG°1;2 is the double-mutant binding free energy, DG°1 the binding free energy
for the first single mutant, DG°2 the binding free energy for the second single
mutant and DG°WT the binding free energy for the wild-type proteins.
References
Surface plasmon resonance data collection and analysis. Double-mutant cycles
were performed with surface plasmon resonance utilizing a Biacore 3000 instrument. Each cycle was performed with a strategy in which all four measurements
(wild type, first single mutant, second single mutant and the double mutant) were
performed in one experiment and fit globally. Wild-type and mutant TCR were
coupled to adjacent flow cells. Coupling levels were between 400 and 1,200 RU.
Two identical concentration series of wild-type and mutant pMHC were then
simultaneously injected over both flow cells in succession, using concentrations as
high as 400 mM, resulting in eight data sets for each cycle. All binding experiments
were performed at 25 °C in 150 mM NaCl, 3 mM EDTA, 25 mM HEPES, 0.005%
P-20, pH 7.4 using a steady-state equilibrium approach11. Data were processed
with BiaEvaluation 4.1.
For data analysis, after subtraction of the signal from a third blank flowcell, the
eight data sets for each cycle were simultaneously fit to a model in which the four
DG° values and the surface activities of the two flow cells were fitted parameters.
Global fitting as was performed with custom scripts in OriginPro 7.5 or 9.0. This
strategy provides significant advantages over the traditional approach in which
individual measurements are made and each cycle constructed from independent
1. Burrows, S. R. et al. Hard wiring of T cell receptor specificity for the major
histocompatibility complex is underpinned by TCR adaptability. Proc. Natl
Acad. Sci. USA 107, 10608–10613 (2010).
2. Borg, N. A. et al. The CDR3 regions of an immunodominant T cell receptor
dictate the ’energetic landscape’ of peptide-MHC recognition. Nat. Immunol. 6,
171–180 (2005).
3. Manning, T. C. et al. Alanine scanning mutagenesis of an alphabeta T cell
receptor: mapping the energy of antigen recognition. Immunity 8, 413–425
(1998).
4. Liu, Y. C. et al. The energetic basis underpinning T-cell teceptor tecognition of
a super-bulged peptide bound to a major histocompatibility complex class I
molecule. J. Biol. Chem. 287, 12267–12276 (2012).
5. Baker, B. M., Turner, R. V., Gagnon, S. J., Wiley, D. C. & Biddison, W. E.
Identification of a crucial energetic footprint on the a1 helix of human
histocompatibility leukocyte antigen (HLA)-A2 that provides functional
interactions for recognition by tax peptide/HLA-A2-specific T cell receptors.
J. Exp. Med. 193, 551–562 (2001).
6. Kranz, D. M. T cell receptor CDRs: starring versus supporting roles. Nat.
Immunol. 6, 130–132 (2005).
8
NATURE COMMUNICATIONS | 4:1948 | DOI: 10.1038/ncomms2948 | www.nature.com/naturecommunications
& 2013 Macmillan Publishers Limited. All rights reserved.
ARTICLE
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms2948
7. DeLano, W. L. Unraveling hot spots in binding interfaces: progress and
challenges. Curr. Opin. Struct. Biol. 12, 14–20 (2002).
8. Gagnon, S. J. et al. Unraveling a hotspot for TCR recognition on HLA-A2:
evidence against the existence of peptide-independent TCR binding
determinants. J. Mol. Biol. 353, 556 (2005).
9. Horovitz, A. Double-mutant cycles: a powerful tool for analyzing protein
structure and function. Folding Des. 1, R121–R126 (1996).
10. Garboczi, D. N. et al. Structure of the complex between human T-cell receptor,
viral peptide and HLA-A2. Nature 384, 134–141 (1996).
11. Davis-Harrison, R. L., Armstrong, K. M. & Baker, B. M. Two different T cell
receptors use different thermodynamic strategies to recognize the same peptide/
MHC ligand. J. Mol. Biol. 346, 533–550 (2005).
12. Ding, Y. H., Baker, B. M., Garboczi, D. N., Biddison, W. E. & Wiley, D. C. Four
A6-TCR/peptide/HLA-A2 structures that generate very different T cell signals
are nearly identical. Immunity 11, 45–56 (1999).
13. Scott, D. R., Borbulevych, O. Y., Piepenbrink, K. H., Corcelli, S. A. & Baker, B.
M. Disparate degrees of hypervariable loop flexibility control T-cell receptor
cross-reactivity, specificity, and binding mechanism. J. Mol. Biol. 414, 385–400
(2011).
14. Hausmann, S. et al. Peptide recognition by two HLA-A2/Tax11-19-specific T
cell clones in relationship to their MHC/peptide/TCR crystal structures.
J. Immunol. 162, 5389–5397 (1999).
15. Gagnon, S. J. et al. T cell receptor recognition via cooperative conformational
plasticity. J. Mol. Biol. 363, 228–243 (2006).
16. Piepenbrink, K. H. et al. Fluorine substitutions in an antigenic peptide
selectively modulate T-cell receptor binding in a minimally perturbing manner.
Biochem. J. 423, 353–361 (2009).
17. Honig, B. & Nicholls, A. Classical electrostatics in biology and chemistry.
Science 268, 1144–1149 (1995).
18. Borbulevych, O. Y., Piepenbrink, K. H. & Baker, B. M. Conformational melding
permits a conserved binding geometry in TCR recognition of foreign and self
molecular mimics. J. Immunol. 186, 2950–2958 (2011).
19. Borbulevych, O. Y. et al. T cell receptor cross-reactivity directed by antigendependent tuning of peptide-MHC molecular flexibility. Immunity 31, 885–896
(2009).
20. Laugel, B. et al. Design of soluble recombinant T cell receptors for antigen
targeting and T cell inhibition. J. Biol. Chem. 280, 1882–1892 (2005).
21. Mason, P. E., Neilson, G. W., Dempsey, C. E., Barnes, A. C. & Cruickshank, J.
M. The hydration structure of guanidinium and thiocyanate ions: implications
for protein stability in aqueous solution. Proc. Natl Acad. Sci. USA 100,
4557–4561 (2003).
22. Adams, J. J. et al. T cell receptor signaling is limited by docking geometry to
peptide-major histocompatibility complex. Immunity 35, 681–693 (2011).
23. Feng, D., Bond, C. J., Ely, L. K., Maynard, J. & Garcia, K. C. Structural evidence
for a germline-encoded T cell receptor-major histocompatibility complex
interaction ‘codon’. Nat. Immunol. 8, 975–983 (2007).
24. Borbulevych, O. Y., Santhanagopolan, S. M., Hossain, M. & Baker, B. M. TCRs
used in cancer gene therapy cross-react with MART-1/Melan-A tumor antigens
via distinct mechanisms. J. Immunol. 187, 2453–2463 (2011).
25. Cole, D. K. et al. Germline-governed recognition of a cancer epitope by an
immunodominant human T-cell receptor. J. Biol. Chem. 284, 27281–27289
(2009).
26. Cuendet, M. A., Zoete, V. & Michielin, O. How T cell receptors interact with
peptide-MHCs: A multiple steered molecular dynamics study. Proteins 79,
3007–3024 (2011).
27. Hawse, W. F. et al. Cutting edge: evidence for a dynamically driven T cell
signaling mechanism. J. Immunol. 188, 5819–5823 (2012).
28. Brady, G. P. & Sharp, K. A. Entropy in protein folding and in protein--protein
interactions. Curr. Opin. Struct. Biol. 7, 215–221 (1997).
29. Zhou, H. X. & Gilson, M. K. Theory of free energy and entropy in noncovalent
binding. Chem. Rev. 109, 4092–4107 (2009).
30. James, U. B. Membrane protein folding: how important are hydrogen bonds?
Curr. Opin. Struct. Biol. 21, 42–49 (2011).
31. Ding, Y. H. et al. Two human T cell receptors bind in a similar diagonal mode
to the HLA- A2/Tax peptide complex using different TCR amino acids.
Immunity 8, 403–411 (1998).
32. Davis-Harrison, R. L., Insaidoo, F. K. & Baker, B. M. T cell receptor binding
transition states and recognition of peptide/MHC. Biochemistry 46, 1840–1850
(2007).
33. Armstrong, K. M., Piepenbrink, K. H. & Baker, B. M. Conformational changes
and flexibility in T-cell receptor recognition of peptide-MHC complexes.
Biochem. J. 415, 183–196 (2008).
34. Collins, E. & Riddle, D. TCR-MHC docking orientation: natural selection, or
thymic selection? Immunol. Res. 41, 267–294 (2008).
35. Garcia, K. C., Adams, J. J., Feng, D. & Ely, L. K. The molecular basis of TCR
germline bias for MHC is surprisingly simple. Nat. Immunol. 10, 143–147
(2009).
36. Baker, B. M., Scott, D. R., Blevins, S. J. & Hawse, W. F. Structural and dynamic
control of T-cell receptor specificity, cross-reactivity, and binding mechanism.
Immunol. Rev. 250, 10–31 (2012).
37. Wucherpfennig, K. W., Call, M. J., Deng, L. & Mariuzza, R. Structural
alterations in peptide-MHC recognition by self-reactive T cell receptors. Curr.
Opin. Immunol. 21, 590–595 (2009).
38. Deng, L., Langley, R. J., Wang, Q., Topalian, S. L. & Mariuzza, R. A. Structural
insights into the editing of germ-line–encoded interactions between T-cell
receptor and MHC class II by Va CDR3. Proc. Natl Acad. Sci. USA 109,
14960–14965 (2012).
39. Tikhonova, A. N. et al. ab T cell receptors that do not undergo major
histocompatibility complex-specific thymic selection possess antibody-like
recognition specificities. Immunity 36, 79–91 (2012).
40. Scott-Browne, J. P., White, J., Kappler, J. W., Gapin, L. & Marrack, P. Germlineencoded amino acids in the [agr][bgr] T-cell receptor control thymic selection.
Nature 458, 1043–1046 (2009).
41. Boulter, J. M. et al. Stable, soluble T-cell receptor molecules for crystallization
and therapeutics. Protein. Eng. 16, 707–711 (2003).
42. Baxter, T. K. et al. Strategic mutations in the class I MHC HLA-A2
independently affect both peptide binding and T cell receptor recognition.
J. Biol. Chem. 279, 29175–29184 (2004).
43. Piepenbrink, K. H., Gloor, B. E., Armstrong, K. M. & Baker, B. M. Methods for
quantifying T cell receptor binding affinities and thermodynamics. Methods
Enzymol. 466, 359–381 (2009).
44. Beechem, J. M. Global analysis of biochemical and biophysical data. Methods
Enzymol. 210, 37–54 (1992).
45. Vaughan, C. K., Harryson, P., Buckle, A. M. & Fersht, A. R. A structural
double-mutant cycle: estimating the strength of a buried salt bridge in barnase.
Acta Crystallographica Sec. D 58, 591–600 (2002).
Acknowledgements
Supported by grants GM067079 and GM075762 from NIGMS, NIH. We thank Cynthia
Piepenbrink for outstanding technical assistance.
Author contributions
K.H.P. and S.J.B. performed all experiments. Experimental design, data analysis and
interpretation were performed by K.H.P., S.J.B. and B.M.B. D.R.S. assisted in data
interpretation. The paper was written by K.H.P. and B.M.B. with input and editing
performed by all authors.
Additional information
Supplementary Information accompanies this paper at http://www.nature.com/
naturecommunications
Competing financial interests: The authors declare no competing financial interests.
Reprints and permission information is available online at http://npg.nature.com/
reprintsandpermissions/
How to cite this article: Piepenbrink, K. H. et al. The basis for limited specificity and
MHC restriction in a T cell receptor interface. Nat. Commun. 4:1948 doi: 10.1038/
ncomms2948 (2013).
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TCRs Used in Cancer Gene Therapy
Cross-React with MART-1/Melan-A Tumor
Antigens via Distinct Mechanisms
Oleg Y. Borbulevych, Sujatha M. Santhanagopolan,
Moushumi Hossain and Brian M. Baker
J Immunol 2011; 187:2453-2463; Prepublished online 27
July 2011;
doi: 10.4049/jimmunol.1101268
http://www.jimmunol.org/content/187/5/2453
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Copyright © 2011 by The American Association of
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of May 27, 2015.
The Journal of Immunology
TCRs Used in Cancer Gene Therapy Cross-React with
MART-1/Melan-A Tumor Antigens via Distinct Mechanisms
Oleg Y. Borbulevych,*,1,2 Sujatha M. Santhanagopolan,*,1,3 Moushumi Hossain,* and
Brian M. Baker*,†
T
he identification of tumor-associated Ags preferentially
presented by human cancers has led to the development of
immunotherapeutic strategies for cancer such as peptide
vaccines and adoptive T cell transfer. In adoptive T cell transfer,
tumor Ag-specific T cells are activated ex vivo and transplanted
back into a lymphodepleted patient. Although clinical trials with
adoptive transfer have been promising (reviewed in Ref. 1), a liability is that variation in T cell repertoires impacts the likelihood
of any individual producing a highly avid TCR specific for a given
tumor Ag. That most tumor Ags are nonmutated self-Ags against
which T cells will likely be negatively selected compounds this
liability. A recent development that can address these concerns is
the transfer of T cells genetically engineered to express tumor Agspecific TCRs with defined recognition properties.
*Department of Chemistry and Biochemistry, University of Notre Dame, Notre
Dame, IN 46556; and †Walther Cancer Research Center, University of Notre Dame,
Notre Dame, IN 46556
1
O.Y.B. and S.M.S. contributed equally to this work.
2
Current address: QuantumBio, Inc., State College, PA.
3
Current address: Public Health Research Institute Center, University of Medicine
and Dentistry of New Jersey, New Jersey Medical School, Newark, NJ.
Received for publication May 3, 2011. Accepted for publication June 17, 2011.
This work was supported by Grant GM067079 from the National Institute of General
Medical Sciences, National Institutes of Health and Grant RSG-05-202-01-GMC
from the American Cancer Society. S.M.S. was supported by a fellowship from the
Walther Cancer Center. Results were derived from work performed at the Structural
Biology Center, Life Sciences Collaborative Access Team (LS-CAT), and Lilly
Research Laboratories Collaborative Access Team (LRL-CAT) at the Advanced Photon Source (APS), Argonne National Laboratory. Argonne is operated by UChicago
Argonne, LLC for the U.S. Department of Energy under contract DE-AC0206CH11357. Use of LS-CAT at APS Sector 21 was supported by the Michigan
Economic Development Corporation and the Michigan Technology Tri-Corridor
(Grant 085P1000817). Use of the LRL-CAT at APS Sector 31 was provided by Eli
Lilly and Company, which operates the facility.
Address correspondence and reprint requests to Dr. Brian M. Baker, Walther Cancer
Research Center, University of Notre Dame, 251 Nieuwland Science Hall, Notre
Dame, IN 46556. E-mail address: brian-baker@nd.edu
The online version of this article contains supplemental material.
Abbreviations used in this article: HLA-A2, HLA-A*0201; PDB, Protein Data Bank;
RMSD, root mean square deviation; TLS, translation/libration/screw.
Copyright Ó 2011 by The American Association of Immunologists, Inc. 0022-1767/11/$16.00
www.jimmunol.org/cgi/doi/10.4049/jimmunol.1101268
The first two trials examining the use of genetically engineered
T cells in humans were published recently (2, 3). Both trials targeted the MART-1 protein (also referred to as Melan-A), upregulated in the majority of melanomas. The two trials used different
class I MHC-restricted TCRs: DMF4 and DMF5. The two
receptors are unrelated, using different Va and Vb segments and
possessing different CDR3 loops (Table I). In functional assays,
DMF5 T cells are more avid than DMF4, and DMF5 T cells are
more efficiently stained with MART-1/HLA-A*0201 (HLA-A2)
tetramers (4). Although the clinical trials were small, use of
DMF5 resulted in an improved rate of cancer regression (13%
with DMF4 versus 30% with DMF5). Use of DMF5 was also
associated with incidences of eye, ear, and skin autoimmune
toxicity not reported with DMF4. Expanded trials with DMF5engineered T cells are underway, and DMF5 continues to be
exploited as a model receptor for the development of T cell-based
gene therapy of cancer (5–7).
Despite this progress, Ag recognition by MART-1–specific
TCRs in general is complex and poorly understood. Most MART1–specific TCRs examined cross-react between the decameric
epitope spanning residues 26–35 (EAAGIGILTV), as well as the
nonameric epitope spanning residues 27–35 (AAGIGILTV), both
presented by the class I MHC (HLA-A2). Compared with the
nonamer, the additional amino acid in the decamer forces the
peptide to bulge and zigzag in the HLA-A2 peptide-binding
groove, resulting in the presentation of different surfaces to the
T cell repertoire (8). In addition to highlighting the capacity for
TCRs to cross-react with structurally diverse ligands (9), nonamer/
decamer cross-reactivity is likely to be important in melanoma
immunotherapy. The nonamer is believed to be the clinically
relevant Ag in HLA-A2+ individuals (10–13). Yet due to poor
binding of the nonamer to HLA-A2 and the inability to generate
a superior heteroclitic nonamer that maintains the nonameric
conformation in the HLA-A2 peptide-binding groove (8, 14), the
majority of efforts targeting MART-1 have made use of the
stronger binding decamer or a decameric variant modified at position 2 (ELAGIGILTV) to select, assay, and activate MART-1–
specific T cells. The decamer (or its anchor-modified variant) was
among the first peptides to be used in clinical trials of peptide-
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
T cells engineered to express TCRs specific for tumor Ags can drive cancer regression. The first TCRs used in cancer gene therapy,
DMF4 and DMF5, recognize two structurally distinct peptide epitopes of the melanoma-associated MART-1/Melan-A protein, both
presented by the class I MHC protein HLA-A*0201. To help understand the mechanisms of TCR cross-reactivity and provide
a foundation for the further development of immunotherapy, we determined the crystallographic structures of DMF4 and DMF5
in complex with both of the MART-1/Melan-A epitopes. The two TCRs use different mechanisms to accommodate the two ligands.
Although DMF4 binds the two with a different orientation, altering its position over the peptide/MHC, DMF5 binds them both
identically. The simpler mode of cross-reactivity by DMF5 is associated with higher affinity toward both ligands, consistent with
the superior functional avidity of DMF5. More generally, the observation of two diverging mechanisms of cross-reactivity with the
same Ags and the finding that TCR-binding orientation can be determined by peptide alone extend our understanding of the
mechanisms underlying TCR cross-reactivity. The Journal of Immunology, 2011, 187: 2453–2463.
2454
MECHANISMS OF CROSS-REACTIVITY IN MART-1–SPECIFIC TCRs
Table I. Gene usage and CDR loop sequences of DMF4 and DMF5
Va
CDR1
CDR2
CDR3
HV4
Vb
CDR1
CDR2
CDR3
DMF4
DMF5
35
SSSIFNTW
YKAGELT
AGGTGNQFYF
GITRKDS
10-3
QTENHRY
YSYGVKDTD
AISEVGVGQPQHF
12-2
YSDRGSQSF
YSNGDK
AVNFGGGKLIF
NKASQYV
6-4
QDMRHNA
YSNTAGTT
ASSLSFGTEAFF
Materials and Methods
Proteins and peptides
Recombinant soluble TCRs and peptide/HLA-A2 molecules were refolded
from bacterially expressed inclusion bodies using established procedures
X-ray crystallography
Crystals of the DMF4-peptide/HLA-A2 complexes were grown from 15%
PEG4000, 0.2 M MgCl2 buffered with 0.1 M Tris (pH 8.5) at 25˚C.
Crystals of the DMF5-peptide/HLA-A2 complexes were grown from 20%
PEG4000 buffered with 0.1 M HEPES (pH 7.5), with the addition of 10%
propanol at 25˚C. Crystals of free DMF5 were grown from 15% PEG 3350,
0.2 M MgCl2 buffered with 0.1 M Tris (pH 8.5) at 25˚C. Crystallization
was performed using sitting drop/vapor diffusion. Streak seeding was used
to obtain higher-quality crystals. For cryoprotection, crystals were transferred into 20% glycerol/80% mother liquor for 30 s and immediately
frozen in liquid nitrogen. Diffraction data were collected at the 19BM,
19ID, 21ID, and 31ID beamlines at the Advanced Photon Source, Argonne
National Laboratories. Data reduction was performed with HKL2000 (18).
The ternary complexes were solved by molecular replacement using
MOLREP or Phaser using Protein Data Bank (PDB) entry 2GJ6 (19) as
a search model, with the coordinates of peptides, solvent, and CDR loops
removed. The structure of free DMF5 was solved using the coordinates of
the TCR from PDB entry 1AO7 (20) as a search model with solvent and
CDR loops removed. Rigid body refinement, followed by translation/libration/screw (TLS) refinement and multiple steps of restrained refinement
were performed with Refmac5 (21). TLS groups were chosen as previously
described (19). Once defined, TLS parameters were included in all subsequent steps of the refinement. Anisotropic and bulk solvent corrections
were taken into account throughout refinement. After TLS refinement, it
was possible to unambiguously trace the position of peptides and TCR
CDR loops in all structures against sA-weighted 2Fo-Fc maps. Waters were
added using ARP/wARP (22). Evaluation of models and fitting to maps
were performed using Coot (23) and XtalView (24). Procheck (25), the
template structure check in WHATIF (26), and MolProbity (27) were used
to evaluate the structures during and after refinement. Hydrogen bonds
were determined with the PISA Web server and validated with distance and
geometry criteria (28). Intermolecular contacts were tabulated using a
˚ . Measurements of TCR-docking angle followed the recomcutoff of 4 A
mended procedure (29). Surface complementarities are the Sc statistic of
Lawrence and Colman (30). Note that the peptides in the decamer complexes are numbered from 1 to 10, in contrast with our previous structure
of the decamer/HLA-A2 complex, in which the peptide was numbered
from 0 to 9 (8). PDB entries for the structures are listed in Table II.
Table II. X-ray data collection and refinement statistics
Data collection
Space group
Cell dimensions
˚)
a, b, c (A
a, b, g (˚)
˚)
Resolution (A
Rmerge
I/sI
Completeness (%)
Redundancy
Refinement
˚)
Resolution (A
No. reflections
Rwork/Rfree
No. atoms
Protein
Water
B-factors
Protein
Water
RMSD from ideality
˚)
Bond length (A
Bond angle (˚)
PDB entry
DMF4-Nonamer/HLA-A2
DMF4-Decamer/HLA-A2
DMF5-Nonamer/HLA-A2
DMF5-Decamer/HLA-A2
DMF5
21ID
P212121
19BM
P212121
19ID
C2
21ID
C2
31ID
C2
59.7, 73.7, 225.3
90.0, 90.0, 90.0
20–2.60 (2.64–2.60)
0.08 (0.28)
25.8 (5.6)
99.6 (98.8)
6.6 (6.1)
56.0, 69.8, 227.1
90.0, 90.0, 90.0
20–2.80 (2.85–20.80)
0.15 (0.86)
13.7 (1.9)
92.9 (89.8)
5.2 (4.3)
227.8, 46.3, 85.9
90.0, 106.6, 90.0
20–2.30 (2.34–2.30)
0.07 (0.41)
19.1 (2.0)
97.0 (81.5)
3.6 (2.8)
228.4, 46.6, 86.0
90.0, 106.7, 90.0
20–2.70 (2.75–2.70)
0.08 (0.27)
18.2 (3.4)
90.3 (62.2)
3.1 (2.7)
184.2, 86.5, 66.5
90.0, 104.0, 90.0
30–2.10 (2.14–2.10)
0.05 (0.29)
20.7 (3.2)
99.7 (99.7)
3.7 (3.4)
20–2.60
31,550
0.23/0.27
20–2.80
21,058
0.21/0.28
20–2.30
37,477
0.24/0.30
20–2.70
22,059
0.22/0.28
29.79–2.09
59,136
0.21/0.27
6,576
103
6,602
33
6,598
48
6,610
27
6,863
498
22.4
19.7
23.5
14.0
47.4
39.9
45.6
35.1
42.1
43.4
0.013
1.589
3QEQ
0.01
1.476
3QDM
0.012
1.562
3QDJ
0.009
1.354
3QDG
0.014
1.668
3QEU
Data in parentheses are for the highest-resolution shell.
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
based cancer vaccines and remains a component of many candidate cancer vaccine formulations (e.g., Ref. 15).
We studied MART-1 nonamer/decamer recognition by the
DMF4 and DMF5 TCRs, determining the structural basis for crossreactivity between the nonamer and decamer peptide/HLA-A2
complexes. We found that the two receptors cross-react via fundamentally different mechanisms. DMF4 cross-reacts with
a complex mechanism, altering its orientation over the peptide/
MHC complex to accommodate the differences in the peptides.
In contrast, DMF5 binds the two ligands identically, accommodating the differences through the use of a permissive architecture
that is preformed in the free receptor. The simpler mode of crossreactivity for DMF5 is associated with higher affinity toward both
ligands, helping to explain DMF5’s stronger functional avidity. In
addition to providing a foundation for further developments in
cancer immunotherapy, the results contribute to our understanding
of the mechanisms underlying TCR cross-reactivity, demonstrating that different TCRs can use different mechanisms to crossreact with the same two ligands and that TCR binding orientation
can be determined by peptide alone.
(16). Peptides were purchased from Genscript or synthesized locally using
an ABI 433A instrument and verified by mass spectrometry. All structure
and binding experiments with the MART-1 decamer used the anchormodified ELAGIGILTV variant. Recombinant DMF4 and DMF5 used an
engineered disulfide bond in the constant domains to enhance stability
(17).
The Journal of Immunology
2455
Table III. Structural descriptors of the DMF4 and DMF5 ternary complexes
Docking angle (˚)
Surface complementarity
TCR-MHC hydrogen bonds/salt bridges
TCR-peptide hydrogen bonds/salt bridges
˚ 2)
Buried surface area (A
Total
CDR1a/CDR2a/HV4a/CDR3a
CDR1b/CDR2b/CDR3b
a1 helix/a2 helix/peptide
DMF4Nonamer/HLA-A2
DMF4Decamer/HLA-A2
DMF5Nonamer/HLA-A2
DMF5Decamer/HLA-A2
44
0.72
6
2
29
0.64
2
5
31
0.64
5
6
31
0.65
4
8
1890
78/157/52/137
62/144/313
426/289/230
1712
78/138/76/130
68/68/327
355/191/280
2201
344/129/41/140
50/171/232
471/361/261
2137
324/135/35/116
49/178/238
449/320/296
Results
Surface plasmon resonance experiments were performed using a Biacore
3000 instrument, as previously described (16). The TCR was coupled to
the sensor surface using amine coupling. Data were corrected for bulk
solvent effects using a blank flow cell. For experiments with the nonamer,
improved accuracy was obtained by fixing the activity of the surface at
values predetermined with the decamer (31). Flow rates were 5 ml/min. All
injections were repeated twice, and affinity measurements reflect simultaneous fits to both datasets. Solution conditions were 10 mM HEPES, 150
mM NaCl, 3 mM EDTA, 0.005% surfactant P-20 (pH 7.4), 25˚C. Data
were processed with Biaevaluation 4.1 (GE Healthcare) and fit with OriginPro 7.5 (OriginLabs).
Structures of the DMF4 and DMF5 TCRs bound to the
nonameric and decameric MART-1/HLA-A2 complexes
The structures of the DMF4 and DMF5 TCRs bound to the MART1 27–35 nonamer (AAGIGILTV) and anchor-modified 26–35
decamer (ELAGIGILTV) were determined at resolutions between
˚ (Table II). All four ternary complexes displayed the
2.3 and 2.8 A
diagonal docking mode traditionally seen in TCR recognition of
foreign Ags. This and other structural descriptors, such as buried
surface area and shape complementarity, were within the range
FIGURE 1. Overview of the DMF4 and DMF5 MART-1 nonamer and decamer peptide/HLA-A2 ternary complexes. A, Side view of the two DMF4
complexes, showing the differences in the TCR variable domains when the HLA-A2 peptide-binding domains are superimposed. The color scheme is
maintained in B and C. B, Top view of the superimposition in A showing the positions of the DMF4 CDR loops over the peptide/HLA-A2 complexes. The
differences in the TCR are attributable to a 15˚ rotation of the TCR over HLA-A2, with CDR3b as the pivot point. C, Same as B, but with the variable
domains of the TCR used for superimposition. The positions of Arg65 and Thr163 are highlighted in blue. The positions of Gln72 and Gln155 are
highlighted in red. D, Side view of the two DMF5 complexes, showing the identical binding mode of the TCR. E, Top view of the superimposition in D
showing the positions of the DMF5 CDR loops over the peptide/HLA-A2 complexes.
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
Surface plasmon resonance
2456
MECHANISMS OF CROSS-REACTIVITY IN MART-1–SPECIFIC TCRs
seen for other TCR–pMHC interactions (29) and are summarized
in Table III. Electron-density images for key regions of each
structure are shown in Supplemental Fig. 1. The structures are
described and compared in detail below, beginning with the more
complex DMF4 structures.
The DMF4 TCR is oriented differently over the MART-1
nonamer and decamer peptide/HLA-A2 complexes
FIGURE 2. Amino acids on HLA-A2
involved in key intermolecular contacts
in the DMF4 (A) and DMF5 (B) ternary
complexes with the MART-1 nonamer and
decamer. Key contacts are defined as those
˚ . More
with interatomic distances #3.75 A
expanded lists of contacts are provided in
Supplemental Fig. 2
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
The structures of the DMF4 TCR bound to the MART-1 nonamer
and decamer peptide/HLA-A2 complexes showed that the TCR
binds the two ligands differently (Fig. 1A). When the HLA-A2
peptide-binding domains in the two structures are superimposed,
the root mean square deviation (RMSD) between the TCR vari˚ . Viewed from the top through the TCR, each
able domains is 5.1 A
loop, with the exception of CDR3b, is arranged differently over
the pMHCs (Fig. 1B). This is reflected in a 15˚ difference in
docking angle, with the TCR positioned more diagonally over the
nonamer (44˚) than the decamer (29˚). Other than CDR3a, each
CDR loop remains in the same conformation. Thus, DMF4
engages the nonameric and decameric MART-1/HLA-A2 complexes with geometries that differ predominantly by a rigid-body
rotation over the pMHC, with the pivot point of rotation centered
on CDR3b (Fig. 1C).
The different geometries by which DMF4 binds the nonamer and
decamer complexes result in different contacts made by various
CDR loop amino acids to positions on HLA-A2 (Fig. 2, see
Supplemental Fig. 2 for a more detailed list). One illustration of
these differences is in the TCR–HLA-A2 hydrogen-bonding patterns: only two hydrogen bonds are formed to HLA-A2 in the
DMF4–decamer complex. In contrast, six TCR–HLA-A2 hydrogen bonds are formed in the nonamer complex.
Examining the DMF4–HLA-A2 interfaces in more detail, the
differences in environments due to the change in TCR orientation
can be broken down into three general classes: placement of TCR
and HLA-A2 atoms into different environments with the formation of wholly new interatomic interactions; a mimicking of the
general chemical environment around HLA-A2 residues but using
atoms from different TCR amino acids; and retention of envi-
ronment with only small changes in interatomic interactions. Instances of each class are shown in Fig. 3. The most dramatic
change in environment occurs with Thr163 in the HLA-A2 a2
helix. In the nonamer structure, Thr163 hydrogen bonds with
Asn29 of CDR1a and Arg68 of HV4a. However, in the decamer
structure, Thr163 forms only a single long-range van der Waals
contact with Asn29a, with Asn29a and Arg68a instead interacting with the peptide (Fig. 3A).
An example in which the HLA-A2 chemical environment is
mimicked using different TCR amino acids is seen with Arg65 in
the HLA-A2 a1 helix, which hydrogen bonds with Thr92a of
CDR3a in the decamer complex but with Gly93 of CDR3a in the
nonamer complex (Fig. 3B). In addition to rotation of the DMF4
TCR, the change in environment around Arg65 is driven by a shift
in CDR3a conformation (Fig. 1C). This conformational change
seems to occur solely for the TCR to hydrogen bond with Arg65,
as CDR3a forms no contacts with the peptide in either the nonamer or decamer structure and there are no steric clashes that
would force a conformational change in the loop if DMF4 were to
bind the nonamer with a decamer-like orientation. The importance
of position 65 in TCR recognition of class I MHC, and HLA-A2 in
particular, was noted previously (32–34) and is likely reflected in
this case in how the need to hydrogen bond with the TCR forces
a conformational change CDR3a.
Thr163 and Arg65 of HLA-A2 lie toward the N-terminal end of
the peptide in the HLA-A2–binding groove, where the differences
in environment are magnified because they are most distant from
the CDR3b pivot point (blue highlights in Fig. 1C). Thus, positions on HLA-A2 closer to CDR3b retain more of their chemical
environments in the two complexes. Indeed, the DMF4–HLA-A2
contacts near CDR3b are the only ones shared in the two DMF4
structures. Of particular interest are shared contacts between
germline CDR loops and HLA-A2. Gln155 maintains the greatest
number of these (Fig. 3C), forming eight with Tyr49 in CDR2a.
Both Gln155 and tyrosines in CDR2a have been suggested to play
a key role in TCR recognition of class I MHC (32, 35), and the
close alignment of Gln155 with Tyr49a, despite the different
docking angle, could indicate such a role. However, Gln155 also
The Journal of Immunology
forms a hydrogen bond with Gln100 of CDR3a in both structures
(Fig. 3C), complicating such an interpretation.
DMF4 cross-reactivity between the MART-1 nonamer and
decamer is attributable to different binding orientations,
nonamer conformational changes, and shared CDR3b–peptide
interactions
We next compared the structures of the DMF4-bound pMHC
complexes with those of the previously solved free pMHCs (8, 36).
No changes occur in either peptide or MHC upon TCR recognition
of the decamer (Fig. 4A). However, upon recognition of the
nonamer, a large shift occurs in the center of the peptide, bringing
the conformation of the center closer to that of the decamer (Fig.
4B). The shift extends from the carbonyl oxygen of Ile4 to the
amide nitrogen of Ile6 and is maximal at the amide nitrogen of
˚ toward the HLA-A2 a2 helix. The shift
Gly5, which moves 2.7 A
in the nonamer is similar to a recent description of “induced
molecular mimicry” upon TCR binding (37). However, due to the
presence of the additional amino acid in the decamer there are still
conformational differences between the nonamer and decamer,
with the peptides out of alignment and register at Ile4 (nonamer)
and Ile5 (decamer) (Fig. 4C).
Closer examination of the DMF4-peptide/HLA-A2 interfaces
shows how the repositioning of DMF4 over the two pMHC molecules allows the TCR to accommodate the remaining structural
differences in the peptides. Beginning with the peptide N terminus, multiple electrostatic interactions link DMF4 to the decamer
(Fig. 5A): Arg68 of the HV4a loop forms a salt bridge with the
N-terminal glutamate, and an interfacial water links Asn29 of
CDR1a and Thr92 of CDR3a to the carbonyl oxygen of Gly4.
None of these interactions is present in the structure with the
nonamer (Fig. 5B): without a hydrogen-bonding partner the water
molecule is absent, and most importantly, the side chain of Ile4 in
the nonamer complex occupies the position of the Gly4 backbone
in the decamer complex, forcing a repositioning of the CDR1a
loop. Without movement of CDR1a, steric clashes would occur
between the side chains of Ile4 and Asn29a (Fig. 5C). These
clashes are avoided by the more diagonal placement of DMF4
over the nonamer, which moves CDR1a out of the way of the Ile4
side chain. The clashes between Ile4 and Asn29a are the only
clashes that occur when the pMHC from the nonameric complex is
superimposed onto that of the decameric complex. Because the
conformation of CDR1a is unchanged despite the different position of the TCR, the surprising conclusion is that the energetic cost
for the TCR to bind in a different orientation is less than that for
moving CDR1a out of the way via a conformational change.
After Ile4/5, the nonamer and decamer peptides begin to move
into alignment and are superimposable at Ile6/7. At this point,
both peptides interact with CDR3b, which, as the pivot point for
the TCR, maintains its position in the two structures. CDR3b is
aligned parallel to the C-terminal halves of the peptides, forming
a motif similar to that of an antiparallel b-sheet (Fig. 5A, 5B). A
hydrogen bond is formed between the amide nitrogen of Val98b
and the carbonyl oxygen of Ile6/7 in both DMF4 complexes, and
the Val98 side chain forms several van der Waals interactions with
the peptides. The position of Val98b appears to drive the conformational change that occurs in the nonamer peptide, as steric
clashes would occur between Val98b and the backbone of Gly5 of
the nonamer if the peptide did not move. Two residues down the
CDR3b loop, Val96 hydrogen bonds with Thr8/9.
The DMF5 TCR engages the MART-1 nonamer and decamer
pMHC complexes identically
Unlike DMF4, the DMF5 TCR binds the MART-1 nonamer and
decamer peptide/HLA-A2 complexes identically (Fig. 1D). In
the two DMF5 complexes, the backbones of the TCR Va/Vb
domains, common residues of the peptides, and the HLA-A2
peptide-binding domains superimpose with an RMSD of only
˚ , and the conformations of the CDR loops are the same (Fig.
0.5 A
1E). The key interresidue contacts within the DMF5-peptide/
HLA-A2 interfaces are listed in Fig. 2; a more detailed list of
contacts is given in Supplemental Fig. 2. As expected from the
near-identical structures, the participation of HLA-A2 amino acids
in the two DMF5 interfaces is essentially the same.
DMF5 uses an open architecture and interfacial water to
accommodate the structural differences in the peptides
We next compared the structures of the DMF5-bound pMHC
complexes with those of the free. As with DMF4, no changes occur
in either peptide or MHC upon DMF5 recognition of the decamer
(Fig. 4D). However, upon recognition of the nonamer, a shift
occurs in the center of the peptide, bringing the conformation of
the center closer to that of the decamer (Fig. 4E). The shift is
nearly identical to that seen with DMF4: it extends from the carbonyl oxygen of Ile4 to the amide nitrogen of Ile6 and is maximal
˚ toward the
at the amide nitrogen of Gly5, which moves 2.7 A
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FIGURE 3. Molecular environments around HLA-A2 contact positions
in the two DMF4 ternary complexes. For all panels, dotted green lines
indicate hydrogen bonds. Dashed bars indicate interatomic van der Waals
˚ ) indicated. A, Environcontacts, with the number and average length (A
ment around Thr163, showing the switch in hydrogen-bonding patterns
between DMF4 recognition of decamer and nonamer. B, Environment
around Arg65, showing the switch in van der Waals and hydrogen-bonding
patterns. Of note is the conformational change in CDR3a, which occurs for
Arg65 to hydrogen bond with Thr92a in the decamer complex and Gly93a
in the nonamer complex. C, Environment around Gln155, showing the
conserved van der Waals interactions with Tyr49 of CDR2a and the hydrogen bond to Gln100 of CDR3b.
2457
2458
MECHANISMS OF CROSS-REACTIVITY IN MART-1–SPECIFIC TCRs
HLA-A2 a2 helix. Again, although the backbones are closer,
the peptides remain out of alignment and register at Ile4/5 (Fig.
4F).
A close inspection of the two DMF5-peptide/HLA-A2 interfaces
reveals how DMF5 is able to recognize the decamer and the shifted
nonamer without requiring the changes in TCR-binding orientation
or CDR-loop conformation required for DMF4. Beginning with the
N termini of the peptides, the side chain of Gln30 of CDR1a
hydrogen bonds to the carbonyl oxygen of Leu2 in the decamer
and Ala2 in the nonamer (Fig. 5D, 5E). Although the conformations of the peptides begin to diverge after this hydrogen
bond, they are close enough to permit the side chain of Gln30a to
form a second hydrogen bond to the amide nitrogen of Gly5
(decamer) and Ile4 (nonamer). The DMF5 TCR does not form
a hydrogen bond or salt bridge with the N-terminal glutamate in
the decamer, making only long-range van der Waals contacts to
the glutamate side chain.
The structural differences between the nonamer and decamer become more significant following the second hydrogen bond made
by Gln30 of CDR1a. After this hydrogen bond, the backbone of
the decamer bulges up toward the TCR. This bulge does not occur
in the nonamer, but the b carbon of Ile4 of the nonamer occupies
the same position as the carbonyl carbon of Gly4 of the decamer.
Both the bulge in the decamer and the side chain of Ile4 in the
nonamer are accommodated by a wide slot in the TCR that is
walled by the side chains of Gln30 of CDR1a and Phe100 of
CDR3b and roofed by the triple-glycine motif in the center of
CDR3a (Fig. 5E, 5F). The slot is large enough to accommodate
both peptides without any compensatory adjustments. Indeed, the
CDR3a “roof” is high enough such that CDR3a forms no contacts
to the decamer and only three, long-range van der Waals contacts
to the nonamer (Supplemental Fig. 3). Thus, an accommodating
architecture is one component of how DMF5 recognizes both the
MART-1 nonamer and decamer.
After exiting the slot, the side chain of Ile5 in the decamer
extends toward the HLA-A2 a2 helix, occupying space at the
periphery of the interface that is empty in the nonamer structure.
At this point, the peptide backbones are closer in alignment and
are linked to the TCR via a water molecule that serves as the hub
of a network of hydrogen bonds between CDR3b and the centers
of the peptides. In both structures, the water links the backbone of
Ile6 (nonamer) and Ile7 (decamer) with the backbone of Phe100b
and the side chain of Ser99b (Fig. 5C, 5D). An additional hydrogen bond is made to Gly6 in the decamer but not to Gly5 in the
nonamer due to lingering structural differences in the peptides.
This network of hydrogen bonds explains the need for the structural shift that occurs in the center of the nonamer upon binding; if
the nonamer did not adopt a conformation closer to the decamer at
this point, there would be no room for the bridging water molecule, preventing the formation of the hydrogen bonds between
CDR3b and the peptide.
Following the water-bridged hydrogen bonds to the centers of the
peptides, the conformations of the nonamer and decamer peptides
are identical. In both structures, a final TCR–peptide hydrogen
bond is made by the side chain of Asn33 of CDR1b to the side
chain of Thr8/9 (Fig. 5D, 5E).
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
FIGURE 4. DMF4 and DMF5 recognize the MART-1 decamer without changes in peptide conformation but force a shift in the center of the nonamer. A,
˚ . B, The center of the nonamer
The conformation of the decamer is unchanged upon DMF4 binding. RMSD for all atom peptide superimposition is 0.6 A
˚ shift at the a carbon of Gly5. RMSD for all atom peptide superundergoes a conformational change upon DMF4 binding, best summarized as a 3.0-A
˚ . C, Although the shift in the nonamer brings the backbone conformation closer to that of the decamer, the nonamer and decamer are still
imposition is 1.3 A
˚ . D, The conformation of the
out of register and alignment, with the b carbons (yellow spheres) of Ile4 (nonamer) and Ile5 (decamer) offset by 3.4 A
˚ . E, As with DMF4, the center of the nonamer undergoes
decamer is unchanged upon DMF5 binding. RMSD for all atom superimposition is 0.4 A
˚ shift at the a carbon of Gly5. RMSD for all atom superimposition is 1.0 A
˚ . F, As
a conformational change upon DMF5 binding, best summarized as a 2.7-A
with DMF4, although the backbone conformations are closer, the nonamer and decamer peptides are still out of register and alignment, with the b carbons
˚.
(yellow spheres) of Ile4 (nonamer) and Ile5 (decamer) offset by 3.8 A
The Journal of Immunology
2459
Only minor conformational adaptations are needed for the
DMF5 TCR to engage peptide
We next determined the structure of the free DMF5 TCR to 2.1
˚ resolution in a crystal form with two molecules per asymmeA
tric unit (Table II; see Supplemental Fig. 1 for electron-density
images). The two copies of the molecule superimpose closely
(RMSD for superimposition of the backbones of the variable
˚ ). Each CDR loop adopts the same overall condomains is 0.8 A
formation in the two copies of the molecule (Fig. 6A). However,
˚ disthe positions at the tip of CDR3a differ by 2.1 and 1.4 A
FIGURE 6. The structure of the free DMF5 TCR indicates that only minor conformational changes are needed to bind. A, Superimposition of the variable
domains for the two molecules in the asymmetric unit of the free DMF5 structure onto the variable domain from the ternary complex with the decamer. The
color scheme is given in the inset and maintained in B and C. B, Conformational diversity in CDR3a is centered on Gly93 and Gly94, with differences of
˚ at the carbonyl carbon of Gly93 and 1.4 A
˚ at the carbonyl carbon of Gly94. The conformation of the loop in the first molecule in the asymmetric unit
2.1 A
˚ in the two
most closely resembles that in the ternary complex. C, Conformational diversity for CDR1a is centered on Gly28, which is displaced by 1.7 A
˚ upon binding. D, Despite the conformational adjustments needed in CDR1a and CDR3a, the open
copies of the free TCR, and displaced a further 1.7 A
architecture in bound DMF5 is largely present in free DMF5, evident when the structure of the free TCR is superimposed onto that in the complex with the
decamer.
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
FIGURE 5. Mechanisms of peptide engagement in the DMF4 and DMF5 ternary complexes. A, DMF4 engages the decamer through a salt bridge to Glu1
from HV4a, and water-bridged hydrogen bonds to Ile5 from CDR1a and CDR3a. CDR3b aligns alongside the C-terminal half of the peptide, hydrogen
bonding to Ile7 and Thr9 and forming van der Waals contacts using Val96 and Val98. Dotted green lines represent hydrogen bonds or salt bridges in this and
all subsequent panels. B, The rotation of the DMF4 over HLA-A2 moves the HV4a, CDR1a, and CDR3a loops away from the N-terminal half of the
nonamer. Peptide engagement is only through CDR3b, the pivot point of DMF4 rotation, which mimics its role in recognition of the decamer. C, Without
rotation of the TCR, the side chain of Asn29 of CDR1a would clash sterically with the side chain of Ile4 of the nonamer (red dashed lines). D and E, DMF5
engages the decamer (D) and nonamer (E) via hydrogen bonds from Glu30 of CDR1a, water-bridged hydrogen bonds from CDR3b, and a hydrogen bond
from CDR1b. F and G, DMF5 accommodates the structural differences in the nonamer and decamer through the use of a wide slot, with sides formed by the
side chains of Gln30 (CDR1a) and Phe100 (CDR3b) and a roof formed by the backbone of CDR3a.
2460
MECHANISMS OF CROSS-REACTIVITY IN MART-1–SPECIFIC TCRs
DMF5 binds both the nonamer and decamer with higher
affinity than DMF4
We next examined the interactions of the DMF4 and DMF5 TCRs
with the two MART-1 ligands using surface plasmon resonance
(Fig. 7). The affinity of DMF5 toward the decamer and nonamer
ligand was 6 and 40 mM, respectively. The affinity of DMF4 toward the decamer and nonamer was 29 and 170 mM, respectively. Thus, both TCRs bind the decamer more strongly than the
nonamer, with DMF5 possessing stronger affinity for both. The
stronger affinities toward decamer are consistent with the need for
the nonamer to undergo a structural shift upon binding of both
TCRs.
Interestingly, although DMF5 binds both the nonamer and decamer more tightly than does DMF4, the difference in binding
free energy between recognition of the nonamer and decamer is
identical within error for the two TCRs (DDG˚ = 1.2 6 0.3 kcal/
mol for decamer, 1.1 6 0.1 kcal/mol for nonamer). Thus, from
a free energy perspective, although DMF5 binds both nonamer
and decamer with higher affinity, its mechanism of cross-reactivity
is not superior to DMF4’s. Lastly, although we attempted kinetic
measurements, dissociation rates for all cases were fast (.0.5 s-1),
precluding accurate measurements of binding kinetics.
Discussion
Recent clinical trials demonstrated that the adoptive transfer of
genetically redirected T cells can lead to cancer regression in
humans (2, 3). The first two TCRs used in this approach, DMF4
and DMF5, both recognize the overlapping, but structurally diverging, 26–35 (decamer) and 27–35 (nonamer) epitopes from the
MART-1/Melan-A protein. Although the trials were small in size,
clinical outcomes differed with the two receptors. Use of DMF4
led to a 13% rate of cancer regression, whereas use of DMF5 led
to a 30% rate of regression and associated eye, ear, and skin
toxicity. The DMF5 TCR is currently in use in larger clinical trials
and continues to be used as a model TCR for improvements in
T cell-based gene therapy of cancer (5–7).
Early work assumed the MART-1 nonamer and decamer were
structurally equivalent because of the high frequency of cross-
FIGURE 7. Surface plasmon resonance binding data define the hierarchy of DMF4/DMF5 nonamer/decamer recognition. A, Steady-state equilibrium data for DMF5 recognition of the decamer and nonamer peptide/
HLA-A2 complexes. Lines show fits to a single-site binding model. Affinities are indicated. B, Steady-state equilibrium data for DMF4 recognition of the decamer and nonamer peptide/HLA-A2 complexes. Affinities
are indicated.
reactive T cells in HLA-A2+ individuals (39). However, comparative structures of the two peptide/HLA-A2 complexes demonstrated that this is not the case, with the decamer adopting a
bulged conformation as a result of the additional amino acid (8).
Although the mechanisms underlying nonamer/decamer crossreactivity are of interest given the fundamental role that T cell
cross-reactivity plays in cellular immunity (9), MART-1 nonamer/
decamer cross-reactivity may also be important in immunotherapy. The nonamer is believed to be the physiologically relevant
epitope in HLA-A2+ individuals (10–13); however, because of the
poor binding of the nonamer to HLA-A2, the decamer or its
anchor-modified variant is regularly used to identify and activate
MART-1–specific T cells. The decamer or its variant also continues to be used as a chief component of many cancer-vaccine
formulations.
In cross-reacting between the MART-1 nonamer and decamer,
both DMF4 and DMF5 require the nonamer to shift its backbone
into a more decamer-like conformation, explaining the higher
affinity toward decamer for both TCRs. Binding-induced conformational changes in peptide backbones have been observed previously in TCR recognition (e.g., Refs. 20, 40, 41), but it is
interesting that in this study, the changes are observed in the
nonamer rather than in the longer and more extensively bulged
decamer. An earlier analysis of MART-1 bound to HLA-A2 suggested that the nonamer possesses greater intrinsic flexibility
than does the decamer (8). Both DMF4 and DMF5 apparently use
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placements at the backbone carbonyls of Gly93 and Gly94, respectively (Fig. 6B), indicating that the triple-glycine motif of
Gly93, Gly94, and Gly95 imparts a degree of flexibility to
CDR3a. The conformation of CDR3a in the first molecule in the
asymmetric unit is closest to the conformation seen in the bound
state of the receptor.
The position of CDR1a also differs slightly in the two molecules in the asymmetric unit of the free DMF5 structure, with
a rotation around Gly28 that impacts the path and position of the
C-terminal end of the loop (Fig. 6C). The C-terminal end of
CDR1a in the bound state of the receptor is displaced slightly
away from the two conformations seen in the unbound state. The
N-terminal half of CDR1a is largely the same in the bound and
unbound conformations, although modest changes are needed in
the Gln30 side chain torsion angles for it to engage peptide.
Although the structure indicates some flexibility for CDR1a and
CDR3a, the conformational adaptations needed to bind ligand
are small in context, less than the average seen for CDR1a and
CDR3a in a recent comparison of bound and free TCRs (38). Thus,
the major elements of DMF5 used to bind ligand appear largely
preconfigured in the free receptor. This is illustrated in Fig. 6D,
which shows how free DMF5 sits over the decamer peptide when
superimposed onto the TCR in the DMF5-decamer/HLA-A2
complex, emphasizing the slot needed to accommodate the peptide.
The Journal of Immunology
seen with TCRs bound to self-Ags associated with autoimmunity
(reviewed in Ref. 49).
Although the changes in binding orientation seen with DMF4
alter the interactions between the TCR germline elements and
HLA-A2, some interactions are conserved, most notably those
between Tyr49 of CDR2a and Gln155 of HLA-A2. Both tyrosines
in TCR CDR2 loops and Gln155 in class I MHC molecules have
been proposed to play key roles in TCR binding, with tyrosines in
particular implicated in encoding a genetic bias of TCRs toward MHC proteins (32, 35, 50). The two DMF4 structures, with
different binding orientations despite the same variable domains
and MHC, provide a new opportunity to test this hypothesis
with structure-guided mutations. It is notable that, in addition
to interacting with Tyr49 of CDR2a, Gln155 hydrogen bonds
with Gln100 of CDR3a, highlighting possible cooperativity in
the interactions of the germline and nongermline elements with
HLA-A2.
Recognition of MART-1 Ags in HLA-A2+ individuals is characterized by a strong bias toward TCRs using the Va 12-2 variable
domain (51, 52). Based on the structure of the Va 12-2 Mel5 TCR
with the MART-1 nonamer presented by HLA-A2, Cole et al. (53)
proposed that this bias was attributable to interactions between the
germline CDR1a loop and the peptide, describing this as “innatelike” recognition of Ag. The DMF5 TCR forms the same CDR1apeptide interactions as does Mel5, using Gln30 to form two hydrogen bonds to the peptide backbone (Supplemental Fig. 5A).
Interestingly, CDR1a of the well-characterized TCR A6, which
also uses Va 12-2, forms similar interactions with the Tax, Tel1p,
and HuD peptides (20, 54, 55). Although these peptides are unrelated to those of MART-1, their N-terminal conformations are
very similar when bound to HLA-A2. Thus, CDR1a of Va 12-2
appears optimally positioned to interact with this peptide conformation. However, the extent to which CDR1a-peptide interactions underlie the Va 12-2 bias in MART-1–specific TCRs
remains uncertain, as there are also conserved patterns of van der
Waals interactions between the Va 12-2 germline loops and HLAA2 in the various structures (Supplemental Fig. 5B). Determining
the energetic balance between these two sets of interactions will
again require more probing investigations. Lastly, MART-1–specific Va 12-2 TCRs also show a weak conservation in the length
and sequence of CDR3a and CDR3b (56). The two CDR3 loops
of Mel5 form a similar slot as in DMF5 to accommodate the bulge
in the MART-1 decamer (Supplemental Fig. 6); the weak bias in
CDR3a/CDR3b composition may thus reflect that only a subset of
possible CDR3 loops is compatible with this architecture.
Acknowledgments
We thank Cynthia Piepenbrink for outstanding technical assistance.
Disclosures
The authors have no financial conflicts of interest.
References
1. Rosenberg, S. A., N. P. Restifo, J. C. Yang, R. A. Morgan, and M. E. Dudley.
2008. Adoptive cell transfer: a clinical path to effective cancer immunotherapy.
Nat. Rev. Cancer 8: 299–308.
2. Johnson, L. A., R. A. Morgan, M. E. Dudley, L. Cassard, J. C. Yang,
M. S. Hughes, U. S. Kammula, R. E. Royal, R. M. Sherry, J. R. Wunderlich,
et al. 2009. Gene therapy with human and mouse T-cell receptors mediates
cancer regression and targets normal tissues expressing cognate antigen. Blood
114: 535–546.
3. Morgan, R. A., M. E. Dudley, J. R. Wunderlich, M. S. Hughes, J. C. Yang,
R. M. Sherry, R. E. Royal, S. L. Topalian, U. S. Kammula, N. P. Restifo, et al.
2006. Cancer regression in patients after transfer of genetically
engineered lymphocytes. Science 314: 126–129.
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
this flexibility in engaging nonamer, albeit for different reasons:
DMF4 to avoid steric clashes and DMF5 to form hydrogen bonds.
After shifting the nonamer, the methods of DMF4 and DMF5
cross-reactivity diverge. The DMF4 TCR uses a complex mechanism, alternating between a binding orientation that, judging by
hydrogen bonds, optimizes interactions with the peptide at the
expense of the MHC (decamer) or optimizes interactions with the
MHC at the expense of the peptide (nonamer). In contrast, DMF5
engages both ligands almost identically, using an open architecture
apparently preformed in the free TCR. Although the structures do
not readily indicate why, DMF5’s simpler mode of cross-reactivity
is associated with improved affinity toward both ligands.
The differences in affinity between the DMF4 and DMF5 TCRs
are relatively modest: 5-fold for the decamer and 4-fold for the
nonamer. These results are consistent with the differences in
functional avidity with the original DMF4 and DMF5 T cell clones
(4) and could help to explain the reported differences in clinical outcomes with the two TCRs. Enhancing TCR affinity has
been suggested as a means for improving immunotherapy (42),
and TCRs with $1000-fold gains in affinity have been generated
through molecular-evolution techniques (e.g., Refs. 43, 44). The
small differences in affinity between DMF4 and DMF5 raise the
possibility that such large enhancements may not be needed to
impact clinical results. This may be significant given that losses in
peptide specificity have been observed with some very highaffinity TCRs (45, 46), an outcome that would clearly be detrimental for Ag-specific immunotherapy (again though, we emphasize that the clinical trials with DMF4 and DMF5 were small,
and other factors, such as differences in a/b-chain pairing in the
transduced TCRs, could have contributed to the outcomes).
Structure-guided computational design has also been used to
enhance TCR affinity (47), in principle providing a degree of
control absent in molecular evolution and reducing the risk of
losses in Ag specificity. The structures with the DMF5 TCR provide a starting point for pursuing such an approach. The fact that
DMF5 engages both the MART-1 nonamer and decamer identically using a preformed architecture raises the likelihood of successfully enhancing affinity toward both nonamer and decamer
without losses in specificity, reducing concerns that a MART-1–
specific TCR with enhanced affinity toward the nonamer would
have reduced affinity toward the decamer or vice versa, either of
which would negatively impact immunotherapy using decamerbased peptides to identify or activate nonamer-specific T cells. A
natural concern is that higher-affinity TCRs targeting MART-1
may induce even stronger autoimmune toxicity if used clinically, requiring more significant interventions than previously
used (2).
The finding that the binding orientation of DMF4 differed with
the nonamer and decamer was surprising. The switch in binding
orientation seems attributable to two structural features: the need to
avoid steric clashes between CDR1a and the center of the nonamer
and the ability of HV4a to form a salt bridge with the N-terminal
glutamate of the decamer. Different orientations of a single TCR
over two different ligands were previously observed with the
murine 2C TCR in complex with the dEV8 and the QL9 peptides
(48). However, in that case, the two peptides were presented
by different MHC proteins (H-2Ld and H-2Kb, respectively). The
results with DMF4 extend this finding by demonstrating that
TCR-binding orientations can be dictated by peptide alone. This
peptide-determined binding mode necessitates a structurally and
energetically permissive relationship between the germline elements of DMF4 and HLA-A2. Such permissiveness may be a
fundamental mechanism of TCR cross-reactivity and is likely further illustrated in the observation of unusual TCR-binding modes
2461
2462
MECHANISMS OF CROSS-REACTIVITY IN MART-1–SPECIFIC TCRs
27. Chen, V. B., W. B. Arendall, III, J. J. Headd, D. A. Keedy, R. M. Immormino,
G. J. Kapral, L. W. Murray, J. S. Richardson, and D. C. Richardson. 2010.
MolProbity: all-atom structure validation for macromolecular crystallography.
Acta Crystallogr. D Biol. Crystallogr. 66: 12–21.
28. Krissinel, E., and K. Henrick. 2007. Inference of macromolecular assemblies
from crystalline state. J. Mol. Biol. 372: 774–797.
29. Rudolph, M. G., R. L. Stanfield, and I. A. Wilson. 2006. How TCRs bind MHCs,
peptides, and coreceptors. Annu. Rev. Immunol. 24: 419–466.
30. Lawrence, M. C., and P. M. Colman. 1993. Shape complementarity at protein/
protein interfaces. J. Mol. Biol. 234: 946–950.
31. Piepenbrink, K. H., B. E. Gloor, K. M. Armstrong, and B. M. Baker. 2009.
Methods for Quantifying T cell Receptor Binding Affinities and Thermodynamics. Methods Enzymol. 466: 359–381.
32. Clements, C. S., M. A. Dunstone, W. A. Macdonald, J. McCluskey, and
J. Rossjohn. 2006. Specificity on a knife-edge: the alphabeta T cell receptor.
Curr. Opin. Struct. Biol. 16: 787–795.
33. Baxter, T. K., S. J. Gagnon, R. L. Davis-Harrison, J. C. Beck, A.-K. Binz,
R. V. Turner, W. E. Biddison, and B. M. Baker. 2004. Strategic mutations in
the class I major histocompatibility HLA-A2 independently affect both peptide binding and T cell receptor recognition. J. Biol. Chem. 279: 29175–
29184.
34. Gagnon, S. J., O. Y. Borbulevych, R. L. Davis-Harrison, T. K. Baxter,
J. R. Clemens, K. M. Armstrong, R. V. Turner, M. Damirjian, W. E. Biddison,
and B. M. Baker. 2005. Unraveling a hotspot for TCR recognition on HLA-A2:
evidence against the existence of peptide-independent TCR binding determinants. J. Mol. Biol. 353: 556–573.
35. Marrack, P., J. P. Scott-Browne, S. Dai, L. Gapin, and J. W. Kappler. 2008.
Evolutionarily conserved amino acids that control TCR-MHC interaction. Annu.
Rev. Immunol. 26: 171–203.
36. Sliz, P., O. Michielin, J.-C. Cerottini, I. Luescher, P. Romero, M. Karplus, and
D. C. Wiley. 2001. Crystal structures of two closely related but antigenically
distinct HLA-A2/melanocyte-melanoma tumor-antigen peptide complexes. J.
Immunol. 167: 3276–3284.
37. Macdonald, W. A., Z. Chen, S. Gras, J. K. Archbold, F. E. Tynan, C. S. Clements, M. Bharadwaj, L. Kjer-Nielsen, P. M. Saunders, M. C. J. Wilce, et al. 2009.
T cell allorecognition via molecular mimicry. Immunity 31: 897–908.
38. Armstrong, K. M., K. H. Piepenbrink, and B. M. Baker. 2008. Conformational
changes and flexibility in T-cell receptor recognition of peptide-MHC complexes. Biochem. J. 415: 183–196.
39. Pittet, M. J., D. Valmori, P. R. Dunbar, D. E. Speiser, D. Lie´nard, F. Lejeune,
K. Fleischhauer, V. Cerundolo, J.-C. Cerottini, and P. Romero. 1999. High frequencies of naive Melan-A/MART-1-specific CD8(+) T cells in a large proportion of human histocompatibility leukocyte antigen (HLA)-A2 individuals. J.
Exp. Med. 190: 705–715.
40. Tynan, F. E., H. H. Reid, L. Kjer-Nielsen, J. J. Miles, M. C. J. Wilce,
L. Kostenko, N. A. Borg, N. A. Williamson, T. Beddoe, A. W. Purcell, et al.
2007. A T cell receptor flattens a bulged antigenic peptide presented by a major
histocompatibility complex class I molecule. Nat. Immunol. 8: 268–276.
41. Lee, J. K., G. Stewart-Jones, T. Dong, K. Harlos, K. Di Gleria, L. Dorrell,
D. C. Douek, P. A. van der Merwe, E. Y. Jones, and A. J. McMichael. 2004.
T cell cross-reactivity and conformational changes during TCR engagement. J.
Exp. Med. 200: 1455–1466.
42. Rosenberg, S. A., and M. E. Dudley. 2009. Adoptive cell therapy for the
treatment of patients with metastatic melanoma. Curr. Opin. Immunol. 21: 233–
240.
43. Holler, P. D., P. O. Holman, E. V. Shusta, S. O’Herrin, K. D. Wittrup, and
D. M. Kranz. 2000. In vitro evolution of a T cell receptor with high affinity for
peptide/MHC. Proc. Natl. Acad. Sci. USA 97: 5387–5392.
44. Li, Y., R. Moysey, P. E. Molloy, A.-L. Vuidepot, T. Mahon, E. Baston, S. Dunn,
N. Liddy, J. Jacob, B. K. Jakobsen, and J. M. Boulter. 2005. Directed evolution
of human T-cell receptors with picomolar affinities by phage display. Nat.
Biotechnol. 23: 349–354.
45. Holler, P. D., L. K. Chlewicki, and D. M. Kranz. 2003. TCRs with high affinity
for foreign pMHC show self-reactivity. Nat. Immunol. 4: 55–62.
46. Zhao, Y., A. D. Bennett, Z. Zheng, Q. J. Wang, P. F. Robbins, L. Y. L. Yu, Y. Li,
P. E. Molloy, S. M. Dunn, B. K. Jakobsen, et al. 2007. High-affinity TCRs
generated by phage display provide CD4+ T cells with the ability to recognize
and kill tumor cell lines. J. Immunol. 179: 5845–5854.
47. Haidar, J. N., B. Pierce, Y. Yu, W. Tong, M. Li, and Z. Weng. 2009. Structurebased design of a T-cell receptor leads to nearly 100-fold improvement in
binding affinity for pepMHC. Proteins 74: 948–960.
48. Colf, L. A., A. J. Bankovich, N. A. Hanick, N. A. Bowerman, L. L. Jones,
D. M. Kranz, and K. C. Garcia. 2007. How a single T cell receptor recognizes
both self and foreign MHC. Cell 129: 135–146.
49. Wucherpfennig, K. W., M. J. Call, L. Deng, and R. Mariuzza. 2009. Structural
alterations in peptide-MHC recognition by self-reactive T cell receptors. Curr.
Opin. Immunol. 21: 590–595.
50. Feng, D., C. J. Bond, L. K. Ely, J. Maynard, and K. C. Garcia. 2007. Structural
evidence for a germline-encoded T cell receptor-major histocompatibility
complex interaction ‘codon’. Nat. Immunol. 8: 975–983.
51. Trautmann, L., N. Labarrie`re, F. Jotereau, V. Karanikas, N. Gervois,
T. Connerotte, P. Coulie, and M. Bonneville. 2002. Dominant TCR V alpha usage
by virus and tumor-reactive T cells with wide affinity ranges for their specific
antigens. Eur. J. Immunol. 32: 3181–3190.
52. Dietrich, P. Y., F. A. Le Gal, V. Dutoit, M. J. Pittet, L. Trautman, A. Zippelius,
I. Cognet, V. Widmer, P. R. Walker, O. Michielin, et al. 2003. Prevalent role of
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
4. Johnson, L. A., B. Heemskerk, D. J. Powell, Jr., C. J. Cohen, R. A. Morgan,
M. E. Dudley, P. F. Robbins, and S. A. Rosenberg. 2006. Gene transfer of tumorreactive TCR confers both high avidity and tumor reactivity to nonreactive peripheral blood mononuclear cells and tumor-infiltrating lymphocytes. J. Immunol. 177: 6548–6559.
5. Goff, S. L., L. A. Johnson, M. A. Black, H. Xu, Z. Zheng, C. J. Cohen,
R. A. Morgan, S. A. Rosenberg, and S. A. Feldman. 2010. Enhanced receptor
expression and in vitro effector function of a murine-human hybrid MART-1reactive T cell receptor following a rapid expansion. Cancer Immunol. Immunother. 59: 1551–1560.
6. Ray, S., A. Chhabra, N. G. Chakraborty, U. Hegde, D. I. Dorsky, T. Chodon,
E. von Euw, B. Comin-Anduix, R. C. Koya, A. Ribas, et al; UCLA-CALTECHCHLA-USC-UCONN Consortium on Translational Program in Engineered
Immunity. 2010. MHC-I-restricted melanoma antigen specific TCR-engineered
human CD4+ T cells exhibit multifunctional effector and helper responses,
in vitro. Clin. Immunol. 136: 338–347.
7. Jazirehi, A. R., S. Baritaki, R. C. Koya, B. Bonavida, and J. S. Economou. 2011.
Molecular mechanism of MART-1+/A*0201+ human melanoma resistance to
specific CTL-killing despite functional tumor-CTL interaction. Cancer Res. 71:
1406–1417.
8. Borbulevych, O. Y., F. K. Insaidoo, T. K. Baxter, D. J. Powell, Jr., L. A. Johnson,
N. P. Restifo, and B. M. Baker. 2007. Structures of MART-126/27-35 Peptide/
HLA-A2 complexes reveal a remarkable disconnect between antigen structural
homology and T cell recognition. J. Mol. Biol. 372: 1123–1136.
9. Mason, D. 1998. A very high level of crossreactivity is an essential feature of the
T-cell receptor. Immunol. Today 19: 395–404.
10. Skipper, J. C., P. H. Gulden, R. C. Hendrickson, N. Harthun, J. A. Caldwell,
J. Shabanowitz, V. H. Engelhard, D. F. Hunt, and C. L. Slingluff Jr. 1999. Massspectrometric evaluation of HLA-A*0201-associated peptides identifies dominant naturally processed forms of CTL epitopes from MART-1 and gp100. Int. J.
Cancer 82: 669–677.
11. Derre´, L., M. Ferber, C. Touvrey, E. Devevre, V. Zoete, A. Leimgruber,
P. Romero, O. Michielin, F. Le´vy, and D. E. Speiser. 2007. A novel population of
human melanoma-specific CD8 T cells recognizes Melan-AMART-1 immunodominant nonapeptide but not the corresponding decapeptide. J. Immunol. 179:
7635–7645.
12. Held, G., A. Wadle, N. Dauth, G. Stewart-Jones, C. Sturm, M. Thiel, C. Zwick,
D. Dieckmann, G. Schuler, H. R. Hoogenboom, et al. 2007. MHC-peptidespecific antibodies reveal inefficient presentation of an HLA-A*0201-restricted,
Melan-A-derived peptide after active intracellular processing. Eur. J. Immunol.
37: 2008–2017.
13. Michaeli, Y., G. Denkberg, K. Sinik, L. Lantzy, C. Chih-Sheng, C. Beauverd,
T. Ziv, P. Romero, and Y. Reiter. 2009. Expression hierarchy of T cell epitopes
from melanoma differentiation antigens: unexpected high level presentation of
tyrosinase-HLA-A2 Complexes revealed by peptide-specific, MHC-restricted,
TCR-like antibodies. J. Immunol. 182: 6328–6341.
14. Valmori, D., J.-F. Fonteneau, C. M. Lizana, N. Gervois, D. Lie´nard,
D. Rimoldi, V. Jongeneel, F. Jotereau, J.-C. Cerottini, and P. Romero. 1998.
Enhanced generation of specific tumor-reactive CTL in vitro by selected
Melan-A/MART-1 immunodominant peptide analogues. J. Immunol. 160:
1750–1758.
15. Ribas, A., B. Comin-Anduix, B. Chmielowski, J. Jalil, P. de la Rocha,
T. A. McCannel, M. T. Ochoa, E. Seja, A. Villanueva, D. K. Oseguera, et al.
2009. Dendritic cell vaccination combined with CTLA4 blockade in patients
with metastatic melanoma. Clin. Cancer Res. 15: 6267–6276.
16. Davis-Harrison, R. L., K. M. Armstrong, and B. M. Baker. 2005. Two different
T cell receptors use different thermodynamic strategies to recognize the same
peptide/MHC ligand. J. Mol. Biol. 346: 533–550.
17. Laugel, B., J. M. Boulter, N. Lissin, A. Vuidepot, Y. Li, E. Gostick, L. E. Crotty,
D. C. Douek, J. Hemelaar, D. A. Price, et al. 2005. Design of soluble
recombinant T cell receptors for antigen targeting and T cell inhibition. J. Biol.
Chem. 280: 1882–1892.
18. Otwinowski, Z., and W. Minor. 1997. Processing of X-ray diffraction data collected in oscillation mode. Methods Enzymol. 276: 307–326.
19. Gagnon, S. J., O. Y. Borbulevych, R. L. Davis-Harrison, R. V. Turner, M. Damirjian,
A. Wojnarowicz, W. E. Biddison, and B. M. Baker. 2006. T cell receptor recognition
via cooperative conformational plasticity. J. Mol. Biol. 363: 228–243.
20. Garboczi, D. N., P. Ghosh, U. Utz, Q. R. Fan, W. E. Biddison, and D. C. Wiley.
1996. Structure of the complex between human T-cell receptor, viral peptide and
HLA-A2. Nature 384: 134–141.
21. Murshudov, G. N., A. A. Vagin, and E. J. Dodson. 1997. Refinement of macromolecular structures by the maximum-likelihood method. Acta Crystallogr. D
Biol. Crystallogr. 53: 240–255.
22. Perrakis, A., T. K. Sixma, K. S. Wilson, and V. S. Lamzin. 1997. wARP: improvement and extension of crystallographic phases by weighted averaging of
multiple-refined dummy atomic models. Acta Crystallogr. D Biol. Crystallogr.
53: 448–455.
23. Emsley, P., and K. Cowtan. 2004. Coot: model-building tools for molecular
graphics. Acta Crystallogr. D Biol. Crystallogr. 60: 2126–2132.
24. McRee, D. E. 1999. XtalView/Xfit—A versatile program for manipulating
atomic coordinates and electron density. J. Struct. Biol. 125: 156–165.
25. Laskowski, R. A., M. W. MacArthur, D. S. Moss, and J. M. Thornton. 1993.
PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl. Cryst. 26: 283–291.
26. Rodriguez, R., G. Chinea, N. Lopez, T. Pons, and G. Vriend. 1998. Homology
modeling, model and software evaluation: three related resources. Bioinformatics 14: 523–528.
The Journal of Immunology
TCR alpha-chain in the selection of the preimmune repertoire specific for a human tumor-associated self-antigen. J. Immunol. 170: 5103–5109.
53. Cole, D. K., F. Yuan, P. J. Rizkallah, J. J. Miles, E. Gostick, D. A. Price,
G. F. Gao, B. K. Jakobsen, and A. K. Sewell. 2009. Germ line-governed recognition of a cancer epitope by an immunodominant human T-cell receptor. J.
Biol. Chem. 284: 27281–27289.
54. Borbulevych, O. Y., K. H. Piepenbrink, and B. M. Baker. 2011. Conformational
melding permits a conserved binding geometry in TCR recognition of foreign
and self molecular mimics. J. Immunol. 186: 2950–2958.
2463
55. Borbulevych, O. Y., K. H. Piepenbrink, B. E. Gloor, D. R. Scott, R. F. Sommese,
D. K. Cole, A. K. Sewell, and B. M. Baker. 2009. T cell receptor cross-reactivity
directed by antigen-dependent tuning of peptide-MHC molecular flexibility.
Immunity 31: 885–896.
56. Wieckowski, S., P. Baumgaertner, P. Corthesy, V. Voelter, P. Romero,
D. E. Speiser, and N. Rufer. 2009. Fine structural variations of alphabetaTCRs
selected by vaccination with natural versus altered self-antigen in melanoma
patients. J. Immunol. 183: 5397–5406.
Downloaded from http://www.jimmunol.org/ at UNiversity of Nebraska Medical Center on May 27, 2015
a)
DMF4/decamer
DMF4/nonamer
amer
b)
DMF5/decamer
DMF5/nonamer
c)
molecule 1 (chain AB)
CDR1α
CDR3α
CDR3β
molecule 2 (chain DE)
CDR1α
CDR3α
CDR3β
Supplemental Fig. 1. 2Fo-Fc electron density contoured at 1σ for the DMF4 (A) and DMF5 (B) TCR-peptide/HLA-A2 ternary complexes and the free DMF5 TCR (C).
For the ternary complexes, density for the CDR1α , CDR3α, and CDR3β loops and the peptides are shown. CDR1α loops are magenta with dark blue mesh, CDR3α
loops are orange with grey mesh, and CDR3β loops are yellow with light blue mesh.
a) contacts in DMF4 structures
CDR1
CDR2
pI4 (1)
pG3 (1)
A158 (1)
T163 (4)
Q155 (12)
T163 (2)
6
13
2
N
T
29
3
decamer
nonamer
W
1
K66 (1)
Y
R65 (5)
49
13
pI5 (1)
K
A
R
T
59
G62 (2)
A69 (1)
R65 (6)
7
1
6
8
9
Q155 (9)
T163 (1)
R65 (6)
pG4 (1)
E154 (1)
W167 (3)
K66 (2)
pI5 (1)
A158 (1)
pE1 (5)
N
G
92
R65 (1)
1
F
Q
3
Y
A69 (3)
peptide contact
hydrogen bond / salt-bridge
two hydrogen bonds / salt-bridges
water-bridged hydrogen bond(s)
pI5 (2)
decamer
nonamer
CDR1
CDR2
CDR3
pI6 (4)
pI4 (4)
pG5 (1)
pG3 (1)
Q72 (6)
Q72 (1)
V76 (3)
H 29
A69 (4)
3
5
R
2
Y
Y 48
2
pT8 (5)
A69 (2)
R65 (1)
R65 (2)
Q72 (1)
9
S
Y
G
3
V
1
K
D
R75 (1)
H70 (3)
T73 (1)
A69 (1)
A69 (2)
K66 (1)
6
15
8
E 95
pL7 (3)
pI6 (1)
pI4 (2)
Q155 (4)
6
8
2
12
V
G
6
23
V
G
Q
pL7 (2)
V76 (1)
T73 (4)
A69 (3)
pG4 (2)
Q155 (3)
pL8 (3)
pI7 (2)
1
Q72 (3)
Q72 (2)
pI6 (3)
pL7 (1)
T73 (2)
pT9 (8)
2
5
H70 (3)
pI7 (1)
pG4 (5)
pL8 (1)
pI5 (2)
pG6 (1)
pI7 (9)
b) contacts in DMF5 structures
nonamer
pG3 (2)
pA2 (3)
T163 (5)
K
E58 (6)
E58 (1)
6
1
1
3
decamer
pI4 (3)
FW S
25
D
1
E58 (2)
E58 (1)
pI4 (1)
R170 (4)
Y159 (2)
W167 (2) W167 (2)
K66 (2)
pI4 (3)
17
3
6
2
G
R
5
9
S
R170 (5) W167 (2)
R65 (1)
Q
S
K66 (1)
pI5 (2)
2
19
pE1 (7)
A158 (1) A158 (1)
E166 (1)
R65 (2)
K66 (5)
K66 (1)
Q155 (2) A158 (2) E166 (1)
T163 (1)
pI4(2)
G62 (1)
G62 (1)
R65 (4)
2
2
3
7
5
3
Y
50
7
3
1
S
N
2
G
1
K
1
Q155 (4) A158 (2) E166 (1)
Y159 (2)
A158 (1)
T163 (4)
pI5 (2)
66
N
91
F
G
G
G62 (1)
R65 (2)
R65 (1)
R65 (3)
K66 (3)
5
4
T163 (1)
1
R65 (7)
G
7
K
7
R65 (7)
pE1 (1)
pL2 (3)
pA3 (3)
pG4 (4)
pI5 (1)
decamer
nonamer
CDR1
CDR2
CD
peptide contact
hydrogen bond / salt-bridge
two hydrogen bonds / salt-bridges
water-bridged hydrogen bond(s)
pI6 (4)
pG3 (1)
pT8 (7)
H 32
Q72 (2)
V76 (2)
pL7 (1)
pL7 (1)
pI4 (2)
pL7 (1)
R65 (2)
A69 (1)
Q72 (5)
Q72 (6)
A150 (1)
pI6 (2)
A69 (7)
pI4 (2)
8
2
3
7
6
2
3
14
3
F
2
14
G
T
A150 (1)
pI7 (2)
A69 (3)
pG3 (1)
Q155 (3)
pL8 (2)
pL8 (1)
pA3 (1)
pI5 (1)
N
8
pL7 (1)
pT9 (7)
A
Y 51
2
R65 (2)
S
N
T
A69 (1)
Q72 (6)
5
Q72 (4)
9
T73 (2)
V76 (1)
A
G
T
6
Q72 (6)
L98
3
S
2
Q155 (3)
3
3
pG4 (4)
pG6 (2)
pI7 (4)
Supplemental Fig. 2. Intermolecular contacts in the two DMF4-peptide/HLA-A2 interfaces (A) and the two DMF5-peptide/HLA-A2 interfaces (B).
For both panels, TCR CDR loop sequences are shown across the center rows, with the α chain in the top panel and the β chain in the bottom.
The number of contacts to each TCR amino acid is in blue, with nonamer contacts above the sequence and decamer contacts below. HLA-A2 or
peptide amino acids forming contacts are also shown, with the number of contacts given in parentheses. Superscripts on the first number of
each loop sequence give the amino acid numbers. Peptide residues are shaded grey. Orange outlines indicate a residue is involved in a single
hydrogen bond or salt-bridge, green outlines indicate two or more hydrogen bonds or salt-bridges. Dashed outlines indicate one or more
water-mediated hydrogen bond. Contacts were tabulted with a distance cutoff of ≤ 4 Å.
a)
CDR1α - peptide
DMF5
A6
Mel5
Q30α
Q30α
Q30α
pG4
pG4
pG4
pL2
pL2
pL2
b) CDR1α - α2 helix
DMF5
Mel5
G28α
R27α
3.6 - 4.0
R27α
3.6 - 3.8
Q30α
3.7 - 4.0
T158
Q30α
3.6 - 4.0
R170
3.4 - 4.0
G28α
G28α
R27α
Q30α
3.7 - 3.8
W167
A6
3.4 - 4.0
R170
3.3 - 3.9
W167
R170
3.7 - 4.0
3.8 - 3.9
W167
T158
T158
Y159
Y159
Y159
CDR2α - α2 helix
DMF5
Mel5
A6
Y50α
N52α
S51α
Y50α
3.1
3.7 - 4.0
A158
3.8
3.2 - 3.9
3.6 - 3.9
E166
N52α
N52α
Y50α
3.3
E166
Q155
A158
H151
E154
3.6 - 3.9
E166
3.9 - 4.0
Q155
A158
3.9
Q155
E154
H151
H151
H15
E154
Supplemental Fig. 3. Interactions made by the Vα 12-2 CDR1α/CDR2β loops in the ternary complexes DMF5, Mel5, and A6 form with
peptide/HLA-A2. A) The backbone conformation of CDR1α in the DMF5, Mel5, and A6 ternary structures is the same, and in all three structures
Gln30α engages the N-terminal portions of the peptides identically. Dotted green lines illustrate hydrogen bonds made by Gln30 of CDR1α to
the peptide backbone. B) Patterns of van der Waals contacts between residues of CDR1α of DMF5 and HLA-A2 (top panel) and CDR2α of DMF5
and HLA-A2 (bottom panel) in the DMF5, Mel5, and A6 ternary complexes.
a)
b)
CDR3α
CDR1β
CDR1α
3β
CDR3β
Q30α
1α
3α
pG3
pI4
pG5
pE0
pL1
3β
1α
3α
pT8
pI6
α1 helix
Supplemental Fig. 4. The Mel5 TCR
accomodates the bulge in the MART-1
decamer via a slot formed by CDR1α,
CDR3α, and CDR3β, analogous to the
mechanism used by DMF5.