The A6 T-cell receptor (TCR)αβ and B7 TCRαβ (herein we call TCRαβ simply as TCR) are both specific for the same Tax peptide (LLFGYPVYV) of the human T lymphotropic virus 1 (HTLV-1) bound to HLA-A2 (Garboczi et al., 1996a, Garboczi et al., 1996b; Ding et al., 1998). A6 and B7 derive from T-cell clones isolated from two patients with HTLV-1-associated myelopathic/tropical spastic paraparesis (Utz et al., 1996; Ding et al., 1998). They share the same Vβ germline gene (TRBV6-5) and differ only in the Vα germline gene (A6: TRAV12-2; B7:TRAV29/DV5), with sequence similarity of 45% for Vα, 96% for Vβ, and 100% for Cα and Cβ (Ding et al., 1998). The only structural differences between the two TCRs are from the residues of the Vα domain and the highly variable complementarity-determining region 3 (CDR3β) loop of the Vβ domain that is crucial for peptide recognition (Ding et al., 1998; Bourcier et al., 2001; Rudolph et al., 2006). In crystal structures, both TCRs bind in a diagonal orientation to the Tax peptide-bound major histocompatibility complex (pMHC), such that both Vα and Vβ contact the MHC α1 and α2 helices (Garboczi et al., 1996a). The similar diagonal binding modes are achieved by interactions involving different CDR residues of A6 and B7 contacting largely the same sets of pMHC residues (Ding et al., 1998). Only 1 out of 17 residues contacting pMHC in B7 is also found in the A6 pMHC interaction (Ding et al., 1998). T-cell response assays demonstrated that single-residue mutations to the Tax peptide elicit different responses in the two TCRs (Ding et al., 1998; Hausmann et al., 1999). Interfacial interactions may play a role in this TCR-specific response, as residue charges at the surface of the A6 and B7 variable domains show different electrostatic profiles, where the pocket for the Tax peptide Y5 residue is positively charged in A6 but negatively charged in B7 (Ding et al., 1998). Overall, the B7 Vα surface has fewer charged residues exposed than A6 Vα. While A6 and B7 recognize Tax-MHC with similar affinities and kinetics, it has been suggested that they achieve binding via different thermodynamic pathways (Davis-Harrison et al., 2005).

However, since αβTCR is a mechanosensor (Reinherz et al., 2023), the TCR-pMHC bond lifetime under physiological piconewton (pN) level load should be more functionally relevant than the equilibrium binding pathway. In this regard, we have previously used all-atom molecular dynamics (MD) simulations to show that contacts with pMHC of A6 (Chang-Gonzalez et al., 2024) and JM22 (Hwang et al., 2020) TCRs are stabilized when an adequate 15–20 pN force is applied. The force-induced stabilization occurs as the asymmetric domain motion of the TCR chassis leads to weakening of the interface with pMHC either in the absence of an adequate level of force or if the sequence of the bound peptide is incompatible with maintaining contacts in the loaded state. The goal of this study is to determine whether the load-dependent control of the binding with pMHC is also present in B7 TCR, and identify any differences with A6 that may impact the response of the T-cell while responding to the same pMHC.

We find that the mechanism of dynamic allostery is largely conserved in B7, yet the loaded state does not stabilize contacts with pMHC as robustly as in the A6. Thus, while both A6 and B7 possess comparable equilibrium binding affinity for pMHC, A6 appears to exhibit a stronger catch bond behavior under load. Given the nuanced and dynamic nature of TCRs against the same pMHC, including the effect of ligand abundance (Akitsu et al., 2024), difference in mechanical response between A6 and B7 suggests T-cell clones bearing those TCRs may operate differently in vivo. Our study also underscores the importance of dynamics when comparing between TCRs that have similar crystal structures and equilibrium binding affinities.

Our simulation systems include the B7 TCR bound to Tax pMHC (Figure 1A and B) with no, low, and high extensions to apply different loads, and an isolated B7 TCR (Table 1). We also used systems without the C-module (Vαβ and Vαβ-pMHC) to study the role of the C-module. To apply a load, we held the terminal C_α atoms of the added strands at different extensions (Figure 1A). This reflects the constant spacing between a T-cell and an APC maintained by adhesion molecules such as CD2 and CD58 (Reinherz et al., 2023). In in vitro single-molecule experiments, pulling to a fixed separation and holding is also commonly done. On the other hand, simulation for B7⁰ was performed by lightly holding the MHC α3 domain (Figure 1A) in a construct without added strands (Methods). It thus does not have any extension nor applied load.

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We analyzed TCR-pMHC intermolecular and intra-TCR (intramolecular) interactions and domain motion to test whether the TCR-pMHC interface is stabilized by load and to find the underlying allostery mechanism that involves the motion of the TCR chassis. We analyze dynamics during the full trajectory and average behavior during 500–1000 ns.

Stabilization of the TCRαβ-pMHC interface with load

Compared to the no- (B7⁰) and low-load (B7^low) cases, the number of high-occupancy contacts were more numerous for the high-load case (B7^high), indicative of a catch bond behavior. Absence of the C-module (Vαβ-pMHC) also promoted more contacts with pMHC, suggesting the allosteric role of the C-module for binding with pMHC (Figure 1C). These results agree well with the behaviors seen in A6 and JM22 TCRs in our previous studies (Chang-Gonzalez et al., 2024; Hwang et al., 2020). However, the number of pMHC contacts with B7 was reduced compared to A6 (Figure 1C). This is despite their comparable number of contacts with the pMHC in crystal structures and comparable equilibrium binding affinity in solution (Ding et al., 1998; Davis-Harrison et al., 2005). In fact, we had to modify our simulation protocol to avoid premature breakage of contacts between B7 and pMHC when preparing the system for production run under load (see Methods).

Time-dependent behavior of the TCR-pMHC interface further supports the load-mediated enhancement of binding. For this, we calculated instantaneous force and contact occupancy in 40 ns overlapping intervals (Figure 1D). B7^high had overall more inter- and intramolecular contacts (more orange-yellow circles) than B7^low (more purple), suggesting that the increased load stiffens the TCR-pMHC complex. B7⁰ had fewer TCR-pMHC contacts but more intra-TCR contacts (horizontal bars in Figure 1D), indicating decoupling of the TCR from pMHC in the absence of load. However, after about 1300 ns, B7^high started to lose the initial high-occupancy contacts (Figure 1D). This is likely because the fixed extension (end-to-end distance) imposed in simulation can adversely impact the interfacial stability of the B7 TCR-pMHC complex that has a higher compliance than A6, as discussed further below. For analysis of average properties, we thus used the 500–1000 ns interval, to be consistent with other systems.

Comparing average counts of high-occupancy pMHC contacts for both A6 and B7 TCRs indicates that interfacial contacts were dominated by MHC-Vα (Figure 2A). Also, Vα formed more contacts with MHC than Vβ, while Vβ formed more contacts with the peptide than it does with MHC (Figure 2A). Similar to A6 (Chang-Gonzalez et al., 2024), occupancy heat maps for individual contact residue pairs show reduced or fragmented contacts for B7⁰ and B7^low (Figure 2—figure supplement 1A and B, more red compared to blue) while B7^high and Vαβ-pMHC exhibit more persistent contact profiles (Figure 2—figure supplement 1C and D, more blue compared to red).

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Temporal progression of the number of contacts was measured via the Hamming distance ${\displaystyle {\displaystyle \mathcal{H}}}$, the number of the initial high-occupancy contacts lost over time (Figure 2B; see Methods). For B7⁰, ${\displaystyle {\displaystyle \mathcal{H}}}$ rapidly increased and by 200 ns, most of the initial high-occupancy contacts were lost. While the increase in ${\displaystyle {\displaystyle \mathcal{H}}}$ for Vαβ-pMHC was comparable to that of B7^low (Figure 2B), the contact occupancy heat maps reveal that Vαβ-pMHC maintained contacts after a brief initial adjustment (arrow in Figure 2—figure supplement 1D) while contacts were lost in B7^low (red in Figure 2—figure supplement 1B). On the other hand, B7^high maintained ${\displaystyle {\displaystyle \mathcal{H}}}$ comparable to Vαβ-pMHC until about 1300 ns, after which it approached that of B7⁰. This occurred as some of the high-occupancy contacts broke (Figure 2—figure supplement 1C). Importantly, the breakage is not due to a high force, but instead it happened when instantaneous force was low. Low-force states are reached at around 750 and 1300 ns (Figure 1D), followed by stepwise increase in ${\displaystyle {\displaystyle \mathcal{H}}}$ (Figure 2B). The difference in extension between B7^low and B7^high is 16.3 Å whereas it is 5.1 Å for A6 (Table 1), for similar ∼5 pN difference between low- and high-load cases. Being more compliant, the interface of B7 can reach a low-force state more easily, hence it is more prone to destabilization.

Location of V-module residues forming contacts with pMHC with greater than 50% average occupancy were concentrated along the peptide for B7^high and Vαβ-pMHC, but scattered in B7⁰ and B7^low (Figure 2C). This trend was also observed in A6 and JM22. Such concentration of high-occupancy contacts may protect TCR-pMHC interactions from breakage by water. In A6 and JM22 TCRs, the greater number of contacts with pMHC in the high-load cases and Vαβ-pMHC correlated with larger buried surface area (BSA) of the residues forming contacts (Chang-Gonzalez et al., 2024; Hwang et al., 2020). B7 did not follow this trend, as B7^high and Vαβ-pMHC had reduced total and per-residue BSA than B7⁰ and B7^low (Figure 2D). This is likely because the fewer high-occupancy contacts in B7 (Figure 1C) tend to be more exposed, making the relationship between the BSA and load less direct. Consistent with this, the total BSA of B7 was 67.4% (B7⁰) to 44.2% (B7^high) of the corresponding values of A6.

The residues of pMHC forming greater than 50% average occupancy under high load differed between A6 and B7 (Figure 2E), as did the location of V-module residues forming respective contacts with the pMHC residues (Figure 2C), further highlighting their divergence in the interfacial footprint under load. Despite this, the root mean square fluctuation (RMSF) of C_α atoms of the Tax peptide measured after 500 ns was reduced in B7^high and Vαβ-pMHC compared to B7⁰ and B7^low (Figure 2—figure supplement 1E), as observed for A6 (Chang-Gonzalez et al., 2024), which supports load-induced stabilization of the complex.

We calculated the distance between the V-module and pMHC as another measure of the interfacial stability (Figure 2—figure supplement 1F; Methods). The distance was stably maintained in Vαβ-pMHC and B7^high (before 1300 ns) whereas it fluctuated more in B7⁰ and B7^low. Of note, the former two systems maintained the distance greater than that in the crystal structure by 0.3–0.9 Å. Thus, a slight separation engendered by force or in the absence of constraint imposed by the C-module provides room for adjusting residues to form more stable contacts. The more stable maintenance of the distance between V-module and pMHC in Vαβ-pMHC and B7^high is consistent with other measures of their stability explained above.

CDR3 positions are controlled by load-dependent Vα-Vβ motion

The greater number of Vα-Vβ contacts in B7⁰ (Figure 3A) is consistent with the increase in total intra-TCR contact occupancy (horizontal bar in Figure 1D, bottom panel). Without load this does not translate to a stronger TCR-pMHC interface explained above. B7 in general had fewer Vα-Vβ contacts (11.0–16.3) than A6 (15.9–23.1) (Chang-Gonzalez et al., 2024). The ∼70% reduction in Vα-Vβ contacts for B7 is comparable to the ∼50% reduction in contacts with pMHC between the two TCRs (Figure 1C).

Figure 3

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Vα-Vβ motion was measured via triads (orientational markers) assigned to respective domains and by performing principal component analysis (PCA) (Figure 3B; Methods). PC amplitude was the lowest for B7^high and Vαβ-pMHC (Figure 3C), which is consistent with the greater number of Vα-Vβ contacts. Regarding the direction of motion, the mutually orthogonal PC directions can be difficult to interpret (arrows in Figure 3B). We instead measured angles between the matching arms of the two triads named ${\displaystyle {\displaystyle \mathrm{\angle }{e}_i}}$ (${\displaystyle {\displaystyle i=1,2,3}}$), to examine the Vα-Vβ motion in structurally interpretable directions (Figure 3D; Chang-Gonzalez et al., 2024). For example, ${\displaystyle {\displaystyle \mathrm{\angle }{e}_1}}$ is the angle between each ${\displaystyle {\displaystyle {\mathbf{e}}_1}}$ arm from Vα and Vβ, which describes a ‘flapping’ or ‘twisting’ motion of the two domains. Since ${\displaystyle {\displaystyle {\mathbf{e}}_2}}$ and ${\displaystyle {\displaystyle {\mathbf{e}}_3}}$ lie approximately parallel to the Vα-Vβ interface, they vary reciprocally, corresponding to a ‘scissoring’ motion (Hwang et al., 2020).

Measuring the distance between CDR3α and CDR3β (‘CDR3 distance’) revealed that this distance is the shortest for B7^high followed by Vαβ-pMHC. Comparing CDR3 distance vs. triad angles (Figure 3E) shows that CDR3 distance varied in opposite directions with ${\displaystyle {\displaystyle \mathrm{\angle }{e}_2}}$ and ${\displaystyle {\displaystyle \mathrm{\angle }{e}_3}}$, which reflects their reciprocal relation (opposite slopes in Figure 3E). In comparison, the CDR3 distance of the B7 crystal structure is 12.0 Å, which is larger than those of B7^high and Vαβ-pMHC (Figure 3E). The slight separation between the V-module and pMHC (Figure 2—figure supplement 1F) in Vαβ-pMHC and B7^high allows CDR3 loops to come closer together compared to the crystal structure, akin to pinching the central protrusion of the peptide.

Asymmetric V-C bending in the B7 TCR is suppressed with applied load

Next, we considered the motion between the V- and C-modules (‘V-C motion’). The number of high-occupancy contacts for the Cα-Cβ interface (26.2–27.5) was considerably greater than those for Vα-Vβ (11.2–16.3), indicating that the C-module acts as a single base for the V-C motion, as noted for A6 and JM22 TCRs (Hwang et al., 2020; Chang-Gonzalez et al., 2024). Continuing this general feature, there were fewer high-occupancy contacts for the Vα-Cα interface compared to the Vβ-Cβ interface (Figure 4A).

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The V-C motion was analyzed by using the bead-on-chain (BOC) model that tracks individual domains and the hinge between them (Figure 4B). PC motion directions were compared by calculating the dot products between the corresponding PC vectors (Figure 4—figure supplement 1A). PC1 corresponding to the V-C bending in B7^high (Figure 4B) was similar in other systems, whereas B7^low differed the most (darker color for B7^low in Figure 4—figure supplement 1A, PC1). Amplitudes of PC1 show a clear distinction where the unliganded Tαβ and B7^low were more mobile than B7⁰ and B7^high (Figure 4C). Comparing PC amplitudes of the elements of the BOC between α and β chains revealed that Vα moves more relative to the C-module than Vβ (Figure 4D), similar to A6 (Chang-Gonzalez et al., 2024). Amplitude of the hinge motion in the two chains varied, where Hα had greater amplitude in PC1 for B7^low compared to B7^high (Figure 4D, PC1 in bottom row). This suggests a more pronounced asymmetric motion in B7^low. The no-load B7⁰ Hβ amplitude was larger compared to Hα (Figure 4D, bottom, negative value for PC1 of B7⁰). For B7⁰, the small PC1 amplitude of the overall V-C motion without load (Figure 4C) does not suppress the motional asymmetry between α and β chains, while in B7^high, the chassis becomes less mobile under load.

The V-C angles (Figure 4B, ∠TCRα and ∠TCRβ) reveal the motional asymmetry in addition to PCA. As in the case of low-load A6 (Chang-Gonzalez et al., 2024), ∠TCRα of B7^low shows a wide bimodal distribution (Figure 4E). ∠TCRα decreased at around 700 ns as B7^low bent more (Figure 4—figure supplement 1B). This would put the V-module in an unfavorable orientation to bind pMHC (Hwang et al., 2020). The dependence of CDR3 distance on V-C angles was most steady in B7^high (Figure 4F). This supports the allosteric mechanism by which the asymmetric V-C motion of the whole TCR controls the Vα-Vβ motion and the V-C orientation that in turn affects the stability of the TCR-pMHC interface.

As a protein-protein complex, TCR-pMHC forms a weak interface. A typical heterodimeric protein-protein interface with BSA comparable to that of TCR-pMHC (∼1700 Ų) has sub-μM binding affinity (Chen et al., 2013) while the affinity of the TCR-pMHC complex ranges between μM to hundreds of μM (Rudolph and Wilson, 2002; Rudolph et al., 2006). Given the low equilibrium affinity, recent findings highlight the importance of mechanosensing, where force generated during immune surveillance of αβ T-cells is utilized to discriminate cognate vs. non-cognate pMHCs (reviewed in Zhu et al., 2019; Liu et al., 2021; Reinherz et al., 2023). Our earlier simulation studies of the JM22 and A6 TCRs showed that the dynamical motion of the TCR chassis is responsible for the force-driven stabilization of the contacts with pMHC, i.e., catch bond formation (Hwang et al., 2020; Chang-Gonzalez et al., 2024). Examining additional TCRs via all-atom MD simulation can inform how the mechanism is adopted. By finding similarities and differences between A6 and B7 TCRs, which recognize the same Tax pMHC, we can elucidate how mechanical force is utilized by each to impact the differential function of T-cells.

Catch bond mechanisms generally differ among proteins (Thomas et al., 2008). For example, FimH and vinculin have relatively well-defined weak- and strong-binding states where there are corresponding crystal structures (Bakolitsa et al., 1999; Le Trong et al., 2010; Sauer et al., 2016; Mei et al., 2020). Availability of the end-state structures enable using simulation approaches such as enhanced sampling of individual states and studying the transition between the two states (Languin-Cattoën et al., 2023; Ccoa et al., 2024). In contrast, TCRs do not have any structurally well-defined weak- or strong-binding states, which requires a different approach. As demonstrated in our present work as well as in our previous papers (Hwang et al., 2020; Chang-Gonzalez et al., 2024), our microsecond-long simulations of the complex under realistic pN-level loads and a combination of analysis methods are effective for elucidating the catch bond mechanism of TCRs, which shows that the load-dependent stabilization of the TCR-pMHC complex differs from simple relaxation of the structure in the initial crystallographic confinement.

Recently, Choi et al., 2023, proposed a mathematical model of TCR catch bond formation. Their assumptions are based mainly on the steered MD simulation (Wu et al., 2019) where partial unfolding of MHC and tilting of the TCR-pMHC interface were considered as required. Our mechanism does not conflict with their assumptions since the complex in the fully folded state should first bear load in a ligand-dependent manner in order to allow any subsequent larger-scale changes.

We found that the dynamic allostery of the TCR chassis observed in A6 (Chang-Gonzalez et al., 2024) and JM22 (Hwang et al., 2020) is largely conserved in B7. Cα and Cβ domains form extensive contacts to construct a base, and the Vβ-Cβ contacts are more extensive than Vα-Cα contacts. This leads to an asymmetric V-C motion where Vα is more mobile relative to the C-module than Vβ. In turn, the motional asymmetry affects the relative positioning of CDR loops, as measured by the CDR3 distance as well as the orientation of the TCR-pMHC interface relative to the loading direction. Unless an adequate load is applied to the complex to suppress the motion, destabilization of the interface occurs. As noted in A6 and JM22, the C domain renders a disadvantage to binding except under force. This is indicated by the greater number of interfacial contacts and decreased Vα-Vβ motion of Vαβ-pMHC (no C-module) simulations. The increased interfacial stability of Vαβ-pMHC is also consistent with our discovery that the C-module likely undergoes a partial unfolding to an extended state, where the bond lifetime increases (Das et al., 2015; Akitsu et al., 2024). Therefore, while the variable domain dictates TCR fit with pMHC, a logical evolutionary pressure would be for the constant domain to maximize discriminatory power by adding instability to the TCR chassis. Furthermore, considering single-chain versions of an antibody lacking the C-module (scFv) are in widespread use (Ahmad et al., 2012) including CAR T cells (Reinherz et al., 2023), a better understanding of a TCR lacking the C-module may help with developing a novel TCR-based immunotherapy. Given the conservation of the asymmetric motion, we also predict the Cβ FG-loop deletion mutant of B7 TCR to possess a diminished catch-bond response, as our previous experiment (Das et al., 2015) and simulation Hwang et al., 2020; Chang-Gonzalez et al., 2024 demonstrated for other TCRs.

While dynamic allostery is overall conserved, A6 and B7 differ in the behavior of the TCR-pMHC interface under load. The crystal structures of the two complexes have a comparable number of TCR-pMHC contacts, with a total of 33 for A6 and 29 for B7 in terms of residue pairs, while the number of distinct atom pairs forming contacts are 46 for A6 (Garboczi et al., 1996a) and 63 for B7 (Ding et al., 1998). During MD simulations, many of these contacts become transient, resulting in fewer high-occupancy contacts. In the thermally fluctuating state, there is a fourfold increase in the difference in number of contacts between A6 and B7 over the difference for static crystal structures (Figure 1C). Previously, contacts found in crystal structures have been used to explain differences in responses to point mutations to the Tax peptide. For example, the sensitivity of B7 to the mutation of Y5 of Tax was explained based on the Y5-D30α hydrogen bond and stacking of Y5 with Y101β of B7 (Y101β in the present study was numbered Y104β in Ding et al., 1998, and Hausmann et al., 1999). In comparison, the more amenable pocket for Y5 on A6 was suggested to be responsible for the greater tolerance of A6 under mutations of Y5. In MD simulations of B7, the Y5-D30α hydrogen bond is formed only in B7^high, after about 300 ns (Figure 2—figure supplement 1C), and the Y5-Y101β nonpolar contact breaks during simulation of B7⁰ and is not present in B7^low (Figure 2—figure supplement 1A and B) while it persists with 62% occupancy in B7^high and 52% occupancy in Vαβ-pMHC (Figure 2C and D; these occupancies are for the whole simulation period). Changes to T-cell specificity by point mutations on Y5 are thus unlikely to arise solely from the size or the polarity of its binding pocket as a static structure. Instead, point mutations affect the organization and dynamics of the surrounding contacts in addition to fit (Chang-Gonzalez et al., 2024). In a related vein, intermolecular motional network has been suggested to be a controlling factor for allostery in a peptide-SH3 domain complex (Gomez et al., 2024), which aligns with the nonlocal and dynamic role of contacts at the TCR-pMHC interface. The inter-domain motion of TCR enables long-range allosteric discrimination of pMHCs, integrating the motion of the two entities such that they influence each other.

The 14.5 pN force on B7^high was applied under 190.0 Å extension (Table 1), whereas the corresponding high-load simulation for A6 was with 18.2 pN at a slightly lower 187.7 Å extension (Chang-Gonzalez et al., 2024). The average total intra-TCR contact occupancy for B7^high between 500 and 1000 ns is 30.4±0.49 contacts (Figure 1C), compared to 38.7±0.87 for A6 under high load (after 500 ns), which further supports a higher compliance of the former. With its higher compliance, the B7 TCR-pMHC complex needs to be under a greater extension than A6 to apply comparable levels of force, and it would be more difficult to achieve load-induced stabilization of the TCR-pMHC interface. This leads us to predict that B7 will exhibit a weaker catch bond where the peak of the TCR-pMHC bond lifetime is at a lower force. And the destabilization of B7^high at 1300 ns (Figures 1D and 2B) may have been a result of our constant-extension approach to apply load, which allows reaching low-force states by the compliant B7. Although this approach was motivated by the constant spacing between a T-cell and an APC (Reinherz et al., 2023), the actin cytoskeleton also adjusts the load applied to the TCR-pMHC complex (Feng et al., 2017; Hu et al., 2024). How fluctuation in the applied load affects the TCR-pMHC dynamics is a subject of a future study.

As a related example to A6 and B7 TCRs, PA59 and PA25 TCRs share the same TRBV and TRBJ genes, and they share 11-aa CDR3β loops that differ only at a single position (Trp vs. Leu) (Akitsu et al., 2024). Recognizing the same pMHC (PA_224-233/D^b), their maximum bond lifetimes and the peak catch bond forces differ considerably, 75 s at 21 pN for PA59, and 13 s at 15 pN for PA25 (Akitsu et al., 2024). These differences may facilitate actions of the corresponding T-cells in tissues that present diverse mechanical environments provided by cell movement, adhesion molecules, tight junction, and noncompliant inflammation.

Likewise, T-cells bearing A6 and B7 may also perform differently in vivo depending on tissue localization (Akitsu et al., 2024) even though they behave similarly in vitro in terms of cytotoxicity and secretion of select cytokines (γ-IFN, MIP-1α, and TNFα) (Ding et al., 1998; Hausmann et al., 1999). We also predict the different catch bond profiles of A6 and B7 will render the two types of T cells to respond differently when the pMHC copy number on the APC is limited (Akitsu et al., 2024). Differences in the catch-bond profiles may also affect the energy input for downstream signaling events that involve reversible conformational transitions in TCRαβ within a certain range of forces and extends the TCR-pMHC bond lifetime by more than an order of magnitude (Akitsu et al., 2024). Elucidating details of those differences is beyond the scope of the present work.

Disparate biological outcomes between structurally similar TCRs recognizing the same pMHC are mechanically possible since slight changes in interfacial contacts can result in altered distribution of loads across the TCR chassis so that changes in its dynamics affect interaction with CD3 signaling subunits (Reinherz et al., 2023). Structural details of the dynamic amplification and propagation of the recognition signal warrant further investigation.

Sample simulation systems and scripts are available in GitHub (copy archived at Hwang, 2025).

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Author details

1. Ana Cristina Chang-Gonzalez

   Department of Biomedical Engineering, Texas A&M University, College Station, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1517-4172

2. Aoi Akitsu

   1. Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, United States
   2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, United States
   3. Department of Medicine, Harvard Medical School, Boston, United States

   Contribution

   Conceptualization, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7672-9664

3. Robert J Mallis

   1. Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, United States
   2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, United States
   3. Department of Dermatology, Harvard Medical School, Boston, United States

   Contribution

   Conceptualization, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2087-9468

4. Matthew J Lang

   1. Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, United States
   2. Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, United States

   Contribution

   Conceptualization, Funding acquisition, Investigation, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8198-144X

5. Ellis L Reinherz

   1. Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, United States
   2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, United States
   3. Department of Medicine, Harvard Medical School, Boston, United States

   Contribution

   Conceptualization, Funding acquisition, Investigation, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1048-5526

6. Wonmuk Hwang

   1. Department of Biomedical Engineering, Texas A&M University, College Station, United States
   2. Department of Materials Science & Engineering, Texas A&M University, College Station, United States
   3. Center for AI and Natural Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea
   4. Department of Physics & Astronomy, Texas A&M University, College Station, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing – review and editing

   For correspondence

   hwm@tamu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7514-3186

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