{"paper_id":"297caaae-472e-45dc-8933-6b386ec4ece8","body_text":"Structure-Guided Analysis of KRAS G12 Mutants Reveals a Length-Encoded Immunogenic Advantage in G12D | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Structure-Guided Analysis of KRAS G12 Mutants Reveals a Length-Encoded Immunogenic Advantage in G12D Linlin Zhao, Jiali Zhu, Zhifeng Chen, Xi Xu, Yuxuan Wang, Pei Liu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6720638/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Communications Biology → Version 1 posted You are reading this latest preprint version Abstract KRAS G12 mutations are frequent oncogenic drivers, yet their differential immunogenicity complicates T cell-based therapies. Here, we integrate structural, biophysical, and functional analyses to examine how KRAS G12 variants remodel peptide-MHC-I (pMHC) architecture and T cell receptor (TCR) recognition. Using HLA-A*11:01, we show that single residue substitutions at position 12 induce distinct conformational changes in the MHC groove, with G12D uniquely destabilizing the complex through a buried aspartate side chain. Notably, G12D peptides adopt two registers, a 9-mer and a 10-mer, that diverge sharply in structure and immunogenicity. The 10-mer forms a compact, stable pMHC with a TCR-accessible surface, while the 9-mer adopts a bent conformation incompatible with recognition. Molecular dynamics and NMR titration confirm the superior stability and binding affinity of the 10-mer. These results highlight how peptide length and conformation critically shape immune visibility, offering mechanistic insight for optimizing TCR-T therapies against elusive neoantigens like KRAS G12D. Biological sciences/Cancer/Cancer therapy/Cancer immunotherapy Biological sciences/Immunology/Immune evasion KRAS G12 Mutations MHC-I Restriction T Cell Recognition Structural Immunology Neoantigen Presentation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Adoptive T cell therapies, including chimeric antigen receptor (CAR-T) and T cell receptor-engineered T cells (TCR-T), have transformed cancer immunotherapy by enabling precise targeting of tumor specific antigens (TSAs) 1 , 2 . These TSAs typically originate from somatic mutations and are processed into short peptides that are loaded onto major histocompatibility complex class I (MHC-I) molecules and displayed on the surface of tumor cells 3 , 4 . This peptide-MHC (pMHC) complex forms the molecular interface for T cell receptor (TCR) recognition, converting intracellular mutations into immunologically visible epitopes 5 . A growing number of recurrent neoantigens derived from shared oncogenic drivers, such as KRAS, TP53, and PIK3CA, have been identified, offering opportunities for designing off-the-shelf TCRs with broad applicability 6 – 10 . Among these, mutations at glycine 12 (G12) of KRAS represent some of the most common oncogenic alterations across colorectal, pancreatic, and non-small cell lung cancers 11 – 15 . These substitutions lock KRAS in a constitutively active GTP-bound state, driving persistent oncogenic signaling through the MAPK and PI3K-AKT pathways 16 – 19 . TCR-T therapies targeting KRAS G12 mutant peptides have entered early-phase clinical trials and show promise 20 – 22 . However, clinical responses remain variable, particularly in patients harboring the G12D variant, raising critical questions about the structural and immunological determinants of effective antigen presentation 23 , 24 . While most efforts have focused on peptide sequence and HLA allele frequency, relatively little is known about how single residue mutations reshape the conformational landscape of pMHC complexes and modulate their immunogenic potential. This gap is particularly important in the context of HLA polymorphism. The structural compatibility between a given HLA allele and a mutant peptide determines whether a neoantigen will be efficiently presented and recognized by T cells 25 , 26 . HLA-A*11:01 is highly prevalent in East Asian populations and has been shown to present multiple KRAS G12-derived epitopes 27 . Yet even subtle changes in peptide length or side chain orientation can profoundly alter the surface topology of the pMHC complex, affecting both its biophysical properties and downstream TCR engagement 28 – 31 . This structural remodeling may underlie the differential immunogenicity and therapeutic outcomes observed among KRAS G12 variants, especially G12D, which despite its high frequency, often correlates with poor response to T cell-based therapies 32 , 33 . In this study, we systematically interrogate how different KRAS G12 mutations, particularly G12D, modulate the presentation and recognition of mutant epitopes by HLA-A*11:01. Using an integrated structural and biophysical approach combining solution state nuclear magnetic resonance (NMR), X-ray crystallography, molecular dynamics simulations, and TCR binding assays, we reveal how single residue substitutions not only shift peptide conformation but also alter the stability and surface presentation of the resulting pMHC complexes. We find that G12D peptides can be presented as both a 9-mer and a 10-mer, but only the 10-mer adopts a stable conformation conducive to effective TCR recognition. Molecular dynamics simulations and NMR titration experiments further confirm that the 10-mer forms a more compact and energetically favorable complex with HLA-A*11:01. These results uncover an underappreciated layer of structural epitope regulation and offer mechanistic insights into how minimal sequence differences can reshape immune visibility, informing the rational design of next generation TCR-based immunotherapies targeting shared oncogenic mutations. Results Solution NMR reveals proper folding and backbone assignment of the KRAS-HLA-A*11:01 complex Solution nuclear magnetic resonance (NMR) technology represents a potent method for investigating dynamic alterations within proteins, particularly the localized conformational changes that occur in structures upon interaction with various ligands. HLA-A, when presenting mutated peptide segments, forms a heterotrimer composed of HLA-A, peptide, and β2M (Figure S1 A). The extracellular domains of HLA-A*11:01 were refolded in vitro with β2-microglobulin (β2M) and a 10-mer wild-type KRAS peptide (VVVGAGGVGK), corresponding to the G12 position of KRAS. HLA-A*11:01 is one of the most prevalent HLA alleles in East Asian populations. The resulting pMHC-I complex was expressed in E. coli, isotopically labeled, refolded and analyzed using solution-state NMR spectroscopy to assess structural integrity and establish a basis for peptide-specific comparisons. Uniformly 2 H, 15 N, 13 C-labeled HLA-A*11:01 heavy chains were reconstituted with unlabeled β2M and peptide, and subjected to triple-resonance NMR experiments including HNCA, HN(CO)CA, HNCACB, CBCA(CO)NH, and HNCO. These experiments enabled backbone assignments for approximately 75% of non-proline residues (Fig. 1 A). Assigned residues spanned all major secondary structure elements within the α1 and α2 domains, including β-strands forming the peptide-binding groove and adjacent α-helices. Regions that lacked unambiguous assignment were primarily localized to flexible loops, including the α1-α2 loop (residues 75–95) and the C-terminal hinge between α2 and α3 domains. These gaps are likely attributable to intermediate exchange broadening or insufficient signal-to-noise in these dynamic segments. Overall signal dispersion in the 1 H- 15 N TROSY-HSQC spectra indicated a well folded, non-aggregated protein. Notably, residues lining the peptide-binding cleft, including positions in β-sheet 1 (residues 5–12) and α-helix 2 (residues 56–70), showed strong, well-resolved peaks, providing a basis for probing localized changes upon peptide mutation. Secondary structure predictions based on chemical shift data ( 13 Cα, 13 Cβ, 13 C’) using TALOS + revealed a pattern consistent with known crystal structures of HLA-A alleles, including HLA-A*02:01 (Fig. 1 B), affirming that the recombinant complex adopts a native-like conformation in aqueous solution. Comparison of TROSY-HSQC spectra from selectively labeled β2M across complexes with different KRAS G12 variants revealed minimal spectral variation (Fig. S1 B), reinforcing the conclusion that β2M remains structurally stable and does not directly engage peptide residues. Therefore, all subsequent labeling and structural analyses focused on the HLA-A*11:01 heavy chain. Together, these NMR results validate the use of refolded HLA-A*11:01 complexes for high-resolution structural interrogation of KRAS-derived epitopes, establishing a robust platform for comparing peptide specific conformational effects. NMR chemical shift mapping reveals mutation-specific perturbations in the MHC groove To assess whether clinically relevant mutations at the KRAS G12 position affect the conformational landscape of the peptide-HLA complex in solution, we reconstituted HLA-A*11:01 complexes with four mutant KRAS peptides, G12C, G12R, G12V, G12D, and each bearing a single amino acid substitution at the G12 site. All complexes were analyzed using two dimensional 1 H- 15 N TROSY-HSQC spectroscopies under identical conditions (Fig. S2). These variants represent the most frequently observed KRAS mutations across human cancers. Substantial chemical shift perturbations (CSPs) were detected in the HLA-A*11:01 heavy chain across the four mutant complexes, relative to the wild-type (WT) peptide (Fig. 2 A-D). Despite differing by only a single residue at position 12, each KRAS mutant peptide induced notable chemical shift perturbations (CSPs) in the HLA-A*11:01 heavy chain when compared to the wild-type complex. Among the variants, G12C and G12R induced prominent chemical shift changes in residues located within the α2 helix (annotated as “α2-α” in Fig. 2 A-B and highlighted with pink dashed lines in the structural models, Fig. 2 E-F). This helix forms part of the outer wall of the peptide binding groove. In contrast, G12V and G12D triggered broader perturbations that extended beyond the α2-helix into the β sheet floor of the binding groove, particularly affecting residues in the α2-strand (“α2-β”; Fig. 2 C and Fig. 2 G, orange dashed lines). Notably, G12D induced the most pronounced changes within this inner region (Fig. 2 H), suggesting a substantial reorganization of peptide-MHC interactions. These results demonstrate that the side chain properties of different G12 mutations, ranging from polar (Asp, Arg) to nonpolar (Val, Cys), elicit unique conformational responses in the HLA-A*11:01 molecule. The observed residue specific perturbation patterns imply distinct binding topologies and potentially divergent immunogenic properties for each mutant epitope, warranting further investigation into their structural determinants and T cell recognition profiles. Distinct peptide conformations and MHC-I stability profiles among KRAS G12 mutations Following the preliminary NMR chemical shift perturbation results, which indicated that different single point mutations at the KRAS G12 position caused substantial conformational differences in the HLA molecule in solution, we hypothesized that these mutations might alter the binding modes between the peptide and HLA-A*11:01. This structural divergence could underlie the ability of T cell receptors (TCRs) to precisely distinguish between different mutant pMHC complexes. To more intuitively dissect the structural basis of TCR recognition and directly compare the binding modes of different KRAS G12 mutants, we employed X-ray crystallography to solve the structures of HLA-A*11:01 complexes loaded with G12C, G12R, and G12V peptides. For G12D, given that its structure had already been determined in previous studies, we integrated published crystallographic data into the present comparative analysis without repeating structural determination. High quality crystal structures were obtained for the three newly determined G12 variants, with resolutions of 2.3 Å (G12C), 3.1 Å (G12R), and 2.8 Å (G12V), respectively (Fig. 3A-D). Structural analysis revealed that the N- and C-terminal residues of all four peptides, including G12D, occupied highly conserved spatial positions within the A and F pockets of HLA-A*11:01. The backbone polar atoms of the three N-terminal valine residues formed robust hydrogen bonds with residues such as E87 in the A pocket, while the C-terminal lysine residue and the free carboxyl group established multiple interactions with D101, Y108, K170, and others in the F pocket (Fig. S3). This binding mode aligns closely with the canonical peptide presentation sites observed in classical HLA-A molecules, indicating that the primary anchoring regions for different KRAS G12 mutant peptides remain conserved. These findings suggest that the major differences in TCR recognition are unlikely to involve the N- or C-terminal regions of the peptide. In contrast, substantial structural variations were observed near the mutation site at position 12. The side chains of G12C and G12R mutants were both oriented outward toward the solvent (Fig. 3B, 3C) and did not interact directly with the internal α2 domain of HLA. By comparison, the side chains of G12V and G12D mutants adopted distinct conformations, extending inward into the peptide-binding groove and forming strong contacts with both the α2 helix and the β-sheet floor. In the wild-type, G12C, and G12R complexes, no comparable interactions with the β-sheet were observed (Fig. 3D, Fig. S3). These crystallographic findings are highly consistent with the earlier NMR chemical shift perturbation data, further corroborating the notion that different G12 mutations modulate the conformational landscape of HLA-A*11:01 in distinct ways. Detailed epitope analysis revealed that although both G12C and G12R mutants displayed solvent exposed side chains, the spatial and electrostatic properties differed significantly. The G12C side chain is relatively small and neutral, whereas G12R possesses a bulkier, positively charged side chain, which theoretically offers a larger and more distinctive surface for TCR engagement. This structural feature may contribute to the improved immunogenicity observed for G12R compared to G12C 34 . Conversely, although G12D also introduces a highly distinctive side chain in terms of size and charge, its insertion deep into the HLA binding groove rather than exposure to the solvent likely compromises its visibility to TCRs, potentially diminishing its immunogenic potential 33,35 . Given these two markedly distinct epitope presentations among the KRAS G12 mutants, we next asked whether these structural differences would affect the overall stability of the MHC-I complexes, thereby influencing immune recognition (Fig. 3E-F). To address this question, we established monoclonal 293T cell lines stably expressing the KRAS G12C, G12R, G12V, or G12D mutant pMHC-I complexes. Cycloheximide (CHX) was used to block new protein synthesis, and cells were harvested at different time points to monitor the degradation kinetics of the pMHC-I complexes by western blotting. The results revealed that the G12C, G12R, and G12V complexes exhibited comparable degradation rates, whereas the G12D complex degraded substantially faster than the other three variants. Integrating these findings with the crystallographic epitope analysis suggests that KRAS G12D may represent a particularly challenging mutation type for immune targeting, characterized by both suboptimal antigen presentation and reduced MHC-I complex stability. A single residue shift in KRAS G12D reconfigures the HLA epitope for selective TCR recognition Given the potential challenges associated with targeting KRAS G12D mutations in immunotherapy, we next focused on elucidating the structural and biophysical features of this mutation to inform the rational design of TCR-T therapies. In the context of HLA-A*11:01, G12D derived epitopes can be presented in two distinct peptide lengths: a 9-mer (VVGADGVGK) and a 10-mer (VVVGADGVGK). Despite their high sequence similarity and presumed similarity in HLA binding modes, our experimental data revealed unexpectedly divergent TCR recognition profiles between the two. A Jurkat cell line was engineered to stably express a TCR specific for the G12D 10-mer. Using pMHC tetramers constructed with either the 9-mer or 10-mer peptide, we performed flow cytometric analysis to assess binding. Strikingly, the TCR recognized the 10-mer with high specificity, while binding to the 9-mer tetramer was negligible, less than 2% of the signal observed with the 10-mer (Fig. 4 A-B). This pronounced functional discrepancy, despite the presence of only a single residue difference, suggested substantial differences in the overall structure or stability of the respective peptide-MHC complexes. To investigate the underlying structural basis, we solved the crystal structure of the HLA-A*11:01-G12D 9-mer complex and compared it with the previously determined structure of the MHC G12D 10-mer complex (Fig. 4 C). As expected, the N- and C-terminal residues of both peptides aligned well within the canonical A and F pockets of HLA-A*11:01, consistent with the conserved anchoring mode observed across other pMHC structures. However, dramatic structural divergence emerged at the central mutation site. In the 10-mer, the aspartate side chain at position 12 projected inward toward the binding groove, whereas in the 9-mer, the same side chain was solvent exposed. Additionally, residues 4 to 6 in the 9-mer adopted a bent conformation that deviated from the α2 helix and curved toward the α1 helix, establishing a specific electrostatic interaction with HLA residue Thr73. This marked shift in peptide trajectory and surface presentation at the core of the binding groove likely explains why the TCR selectively engages the 10-mer but not the 9-mer. Beyond structural insights, we assessed the relative binding stability of the two peptide-MHC complexes using NMR titration assays. Stepwise titration of excess 10-mer peptide into the 9-mer-MHC complex resulted in progressive chemical shift perturbations in the HSQC spectrum, consistent with competitive displacement of the 9-mer (Fig. 4 D). In contrast, the addition of excess 9-mer peptide into the 10-mer-MHC complex failed to induce comparable spectral shifts (Fig. S4), indicating that the 9-mer was unable to displace the more stably bound 10-mer (Fig. S5A). These results provide complementary evidence that the 10-mer forms a tighter, more stable complex with HLA-A*11:01, whereas the 9-mer binds less stably and is likely presented less efficiently. Such differences in stability and surface topology may underlie the stark contrast in TCR recognition, and further highlight the structural and biophysical constraints involved in identifying TCRs with high specificity toward G12D neoantigens. Molecular dynamics simulation reveals superior stability and binding affinity of G12D 10-mer over 9-mer To further evaluate the energetic and structural differences in how G12D 9-mer and G12D 10-mer peptides engage HLA-A*11:01, we performed all-atom molecular dynamics (MD) simulations using the Desmond software package. The systems were parameterized with the OPLS-AA 2005 force field, solvated in an SPC explicit water model, and charge neutralized with 0.15 M NaCl. Following a 2 ns relaxation protocol, each peptide-MHC complex underwent a 100 ns production simulation under isothermal isobaric (NPT) conditions at 300 K and 1 atm. Trajectory snapshots were recorded every 100 ps for downstream structural and energetic analyses. Analysis of the simulation trajectories revealed that the G12D 10-mer complex exhibited greater conformational stability throughout the simulation. Root mean square deviation (RMSD) analysis of the protein backbone showed that the 10-mer complex stabilized within ~ 50 ns and maintained lower overall fluctuations than the 9-mer complex (Fig. 5 A). To quantitatively assess the binding affinity of the two peptides, we performed Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy calculations on both complexes. From each 100 ns trajectory, 1,000 evenly spaced snapshots were extracted (1 per 100 ps) for energy decomposition. The results demonstrated that the G12D 10-mer exhibited a significantly lower binding free energy (ΔG_bind) compared to the 9-mer, indicating tighter and more thermodynamically stable association with HLA-A*11:01 (Fig. 5 C). These findings are in strong agreement with the NMR titration results described above and further support the notion that the 10-mer peptide is preferentially presented and more stable in the MHC groove, potentially enhancing its immunogenic potential. Interaction profiling revealed that the 10-mer established a larger number of persistent hydrogen bonds and hydrophobic contacts within the HLA binding groove. Moreover, its more compact conformation at the interface likely reduces entropic penalties upon binding, thereby contributing to its superior affinity (Fig. 5 B, S5B-C). Together, these simulation results provide atomic resolution evidence that G12D 10-mer forms a more stable pMHC complex than the 9-mer. These findings offer critical mechanistic insights for peptide selection in TCR-T design and suggest that the 10-mer may serve as a more favorable immunotherapeutic target with respect to both TCR screening and clinical efficacy. Discussion The KRAS G12 mutation represents one of the most prevalent oncogenic alterations across multiple cancer types and has emerged as a prominent target for T cell-based immunotherapy. However, despite the shared mutation site, clinical responses to TCR-engineered T cell therapies targeting KRAS G12 variants have been inconsistent, suggesting a potential structural basis for differential immunogenicity 36 – 38 . In this study, we systematically characterized how distinct KRAS G12 mutations, and in particular the G12D variant, remodel the peptide-HLA-A*11:01 landscape to influence immune recognition. By integrating solution state NMR, X-ray crystallography, and molecular dynamics simulations with cell-based stability assays and functional TCR binding analyses, we demonstrate that single amino acid changes at position 12 not only alter the conformation of the peptide-MHC complex but also significantly impact its structural stability and capacity for TCR engagement. Our findings reveal that G12D peptides, despite their high oncogenic relevance, pose unique challenges for antigen presentation and TCR recognition, underscoring the need to consider structural epitope configurations rather than peptide sequence alone when designing TCR-based immunotherapies. Across all KRAS G12 variants examined, the terminal anchoring of peptides within the A and F pockets of HLA-A*11:01 remained conserved, as evidenced by both crystal structures and NMR chemical shift patterns. This architectural preservation suggests that differences in TCR recognition are unlikely to stem from N- or C-terminal interactions. Instead, our structural analyses consistently pinpointed the central mutation site, position 12, as the primary determinant of epitope conformation and immunogenic potential. While the side chains of G12C and G12R extend outward from the MHC groove and remain solvent accessible, facilitating potential TCR contact, those of G12V and especially G12D adopt inward-facing conformations. The G12D side chain in particular inserts deeply into the groove, forming intramolecular contacts with HLA residues such as R114, thereby masking its identity and minimizing its exposure to the immune repertoire. These divergent orientations, driven by side chain size, charge, and polarity, fundamentally reshape the physicochemical topology of the peptide-MHC surface and likely underlie the sharp functional contrast in TCR recognition observed across variants. This complexity is further compounded by the existence of multiple peptide registers for the same G12D mutation. In the context of HLA-A*11:01, both a 9-mer (VVGADGVGK) and a 10-mer (VVVGADGVGK) can be endogenously presented, yet they give rise to dramatically different immunological outcomes. Despite differing by only a single N-terminal valine, structural and biophysical analyses revealed that these two peptides adopt distinct conformations within the MHC groove. Crystallographic comparison demonstrated that while their terminal anchoring remains aligned, the central region diverges sharply: the 10-mer buries the aspartate side chain within the groove, whereas the 9-mer presents the same residue outward, accompanied by a conformational bend away from the α2 helix toward α1, forming a specific electrostatic contact with Thr73 of the HLA. These shifts generate structurally non-overlapping epitopes and explain why a TCR selected against the 10-mer fails to recognize the 9-mer, despite near-identical sequences. This finding highlights that even subtle differences in peptide length can drive topological reorganization of the pMHC surface, redefining what is accessible for TCR surveillance and thereby shaping the immunogenic hierarchy among candidate epitopes. The marked differences in epitope topology between the G12D 9-mer and 10-mer peptides are further substantiated by their distinct binding stabilities to HLA-A*11:01. Competitive NMR titration experiments revealed that the 10-mer could effectively displace the 9-mer from preformed pMHC complexes, whereas the reverse was not observed, indicating a clear thermodynamic advantage for the longer peptide. Furthermore, MM/GBSA free energy calculations confirmed that the 10-mer forms a more stable and energetically favorable association with HLA-A*11:01. These converging data indicate that the additional N-terminal valine in the 10-mer not only extends peptide-MHC interactions but also induces a more compact, lower entropy binding pose, enhancing both structural stability and immunogenic presentation. From a therapeutic perspective, the superior conformational stability and enhanced TCR engagement profile of the G12D 10-mer strongly advocate for its prioritization in antigen selection and TCR design pipelines. While the G12D mutation is among the most common KRAS alterations, its immunogenicity has been historically difficult to harness, in part due to the ambiguous or unstable nature of its presented epitopes. Our integrated structural and biophysical data provide compelling evidence that not all G12D-derived peptides are equal, minor differences in length and conformation can have major consequences for TCR accessibility and immune activation. These insights highlight the critical importance of resolving pMHC topology at atomic resolution when selecting neoantigen targets. Future strategies incorporating structure-guided TCR engineering, in silico modeling of peptide registers, and machine learning-based TCR affinity prediction will benefit from this framework, enabling more precise targeting of cryptic but therapeutically actionable mutations like KRAS G12D. Materials and Methods Expression and Purification of KRAS-HLA protein complex samples The DNA sequences corresponding to the human HLA-A*11:01 isoform (residues 25–299) and β2M (residues 21–119) were cloned from the human cDNA library and inserted into the Pet28a and Pet21a vector separately. These constructs were then transformed into E. coli strain BL21 (DE3) cells. For NMR sample preparation, cells were cultured in M9 minimal media supplemented with stable isotopes, tailored to the specific NMR experimental requirements. For crystallography, cells were cultured in LB media. Protein expression was induced when the bacteria culture reached an absorbance of ~ 0.8 at 600 nm. Isopropyl β-D-1-thiogalactopyranoside (IPTG) at a concentration of 500 µM was used to induce protein expression for both HLA and β2M constructs at 37°C. Cell pellets were resuspended in Lysis Buffer (50 mM Tris-HCl/pH 8.0, 0.5 mM EDTA, 1 mM DTT, 1 mM PMSF). The cells were sonicated under 300 power cycle twice to achieve complete lysis, using a sonicator (Scientz-IID), and then centrifuged at 40,000 × g for 30 minutes to collect inclusion body pellets. The inclusion bodies were washed three times with PBS buffer (20 mM Phosphate Buffer/pH7.2,150 mM NaCl) and dissolved in Denaturing Buffer (20 mM Tris-HCl/pH8.0, 6M Guanidine-HCl, 0.5 mM EDTA, 1 mM DTT, 0.2 mM PMSF) overnight. Cell debris was removed by another centrifugation step at 40,000 × g for 30 minutes. The peptide powder was synthesized by GenScript. The protein refolding system consisted of 6 mg HLA-A*11:01, 2 mg β2M, and 1 mg peptide. Firstly, these components were mixed together and then slowly added dropwise to 50 mL of Refolding Buffer (100 mM Tris-HCl/pH 8.0, 3 M Urea, 0.4 M Arginine, 0.16% Glutathione reduced, 0.03% Glutathione oxidized and 2mM EDTA). The mixture was placed at 25°C and stirred for three hours. The refolding system was then centrifuged at 40,000 × g for 30 minutes and subsequently subjected to three rounds of dialysis in a 5L buffer system at 4°C. The refolded supernatant was concentrated using the HiTrap Q FF column and further purified by size exclusion using the Increase Superdex-200 10/300GL Cytiva column in FPLC Buffer (20 mM Phosphate Buffer/pH7.2,150 mM NaCl). A standard nuclear magnetic resonance (NMR) sample typically contained approximately 0.5 mM of the target molecules (HLA: β2M: Peptide = 1:1:1) in NMR Buffer (20 mM Phosphate Buffer/pH7.2,150 mM NaCl,10% D2O). The crystal samples were purified and refolded following the same protocol. NMR backbone resonance assignment All NMR data of HLA-A*11:01 TROSY spectra presented with KRAS G12 mutant variants were recorded at 25°C by VnmrJ Biopack on Agilent 800 or 600 MHz spectrometer equipped with cryogenic probes. NMR data were processed and analyzed by NMRPipe 39 , XEASY 40 , and CcpNmr Analysis v.2 41 . Backbone chemical shift assignments of HLA-A*11:01 were carried out using a set of standard triple resonance experiments, including the TROSY version of HNCA, HN(CO)CA, HN(CA)CO, HNCO, and HNCACB, HN(CO)CACB 42 on a ( 15 N, 13 C, 85% 2 H)-labeled sample at a 1 H frequency of 600 MHz. NMR chemical shift perturbation experiment The protein complex between different KRAS G12 mutant peptides, HLA-A*11:01 and β2M were prepared in the same condition and collected a series of TROSY-HSQC spectra on Agilent 800MHz. The combined chemical-shift differences ( \\(\\:\\varDelta\\:{\\delta\\:}_{N}^{i}\\) ) were calculated for each residue using the formula 43 : $$\\:\\varDelta\\:{\\delta\\:}_{comb}^{i}=\\sqrt{{（{\\omega\\:}_{H}\\varDelta\\:{\\delta\\:}_{H}^{i}）}^{2}+{（{\\omega\\:}_{N}\\varDelta\\:{\\delta\\:}_{N}^{i}）}^{2}}$$ where \\(\\:\\varDelta\\:{\\delta\\:}_{H}^{i}\\) and \\(\\:\\varDelta\\:{\\delta\\:}_{N}^{i}\\) are 1 H and 15 N chemical-shift perturbations between KRAS-mutant and KRAS-WT, respectively, and \\(\\:{\\omega\\:}_{H}\\) = 1.00 and \\(\\:{\\omega\\:}_{N}\\) = 0.15 are normalization factors. In the G12D NMR competition experiment, the G12V TROSY-HSQC spectrum was initially collected on Agilent 800 MHz. Subsequently, a tenfold concentration of mutant peptide mixtures, along with the wild-type (WT), was added to the NMR sample and incubated overnight at 4°C. The mixed sample was then purified to remove any excess peptides using size exclusion chromatography with the Increase Superdex-200 10/300GL Cytiva column, following the same protocol as described above. Crystallography The KRAS-HLA-β2M protein complex was incubated on ice for 30 minutes. Subsequently, the sample was prepared for crystallization using the sitting-drop vapor diffusion method at 20°C. The reservoir solution for each protein is as follows: G12C(0.1 M ammonium acetate, 0.1 M Bis-Tris PH5.2, PEG4000 19%), G12R (0.2 M Lithium sulfate, 0.1 M Bis-Tris PH5.8, PEG3350 27%), G12V(0.2 M Lithium sulfate, 0.1 M Bis-Tris PH5.5, PEG3350 27%), G12D 9-mer (27% PEG3350, 0.1 M Bis-Tris, 0.2 M Lithium sulfate, additive 0.1 M Spermidine). The crystals were frozen in liquid nitrogen using a cryo-protectant of mother liquor supplemented with 30% (v/v) glycerol prior to data collection. CHX stability assay MHC-G12 mutations in 293T stable cell lines were cultured to 80%-90% and treated with cycloheximide (CHX, AbMole, #M4879) at a final concentration of 100 µg/mL. Cells were harvested by centrifugation at various time points at 0, 6, 12, 18, 24, 48 and 60 hours. After resuspension in RIPA lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 0.1% SDS, 0.5% sodium deoxycholate, 1% Triton X-100) containing a protease inhibitor (ABclonal, #RM02916), the cells were incubated on ice for 30 min. Cell lysates were centrifuged at 12,000 rpm for 15 mins at 4°C and the supernatant was collected. Protein samples were mixed with 5× Sampling Buffer and denatured in a metal bath at 99°C for 10 minutes. Proteins were separated by SDS-PAGE and transferred to a nitrocellulose membrane (Millipore, #HATF00010). Membranes were blocked with 5% skimmed milk (Sangon Biotech, #A600669) in TBS-T for 1 hr and then rinsed three times with TBS-T. Membranes were incubated with primary antibody (rabbit anti-HA, Abmart, #ABT2041) at 4°C overnight. The next day, the membrane was washed three times with TBS-T and incubated with secondary antibody (HRP anti-rabbit, ABclonal, #AS003) for 1 hour at room temperature. Chemiluminescent signals were detected using ECL substrate (Sigma, #WBKLS0100) and quantified using ImageJ software. MHC-I tetramer preparation The target proteins, MHC G12D 10-mer and MHC G12D 9-mer, were first biotinylated according to a biotinylated reaction system of 50 uM target protein, 50 mM Bicine, 10mM MgCl 2 , 1/100 BirA, 1mM biotin, and 10 mM ATP for 40 minutes at room temperature, and passed through a molecular sieve after the biotinylation reaction was complete. The tetramers were then prepared, which entailed dissolving the G12D 10-mer and G12D 9-mer peptide dry powders in DMSO at a concentration of 10 mM (10 mg/ml). The peptides were further diluted to 400 µM with PBS and stored on ice. Add 20 µL of diluted peptide (400 µM) and 20 µL of target protein (200 µg/ml) to a 96-well plate, mix well and seal the plate; centrifuge the plate at 2500x g for 2 minutes at 4°C and collect the lower layer of liquid. Remove the seal; place the plate on ice and irradiate with a UV lamp for 30 minutes (the UV lamp should be 2–5 cm away from the sample). Seal the plate; incubate at 37°C for 30 minutes in the dark. At the end of incubation, take 30 µL of the displaced monomer into a 1.5ml EP tube, add 3.3 µL of SA-APC, mix well, and place on ice for incubation in the dark. After incubation, add 2.4 µL of blocking buffer to terminate the reaction. The reaction is terminated by the addition of 2.4 µL blocking buffer and then placed in the refrigerator at 4°C overnight (or incubated on ice for 30 minutes). Retroviral production for Jurkat cell transduction Lentiviral supernatants encoding different mutants of MHC G12_ and retroviral supernatants encoding the KRAS G12D TCR were prepared using HEK 293T cells. For lentivirus production, HEK 293T cells were cotransfected with lentiviral plasmids containing the relevant genes, packaging plasmids pSPAX2 and pMD2.G in a ratio of 4:3:1. For retrovirus production, HEK 293T cells were cotransfected with the retroviral plasmid containing the gene of interest and the packaging plasmids gag-pol and VSVG in a 4:3:1 ratio. When the density of HEK 293T cells reached 70–80%, the medium was removed and 5 mL of medium without DMEM was added. Cells were transfected with polyethyleneimine (PEI, PolySciences, Inc., USA) and plasmids at a ratio of 3:1. After 5 hours of incubation at 37°C with 5% CO 2 , cells were supplemented with 10 mL of fresh DMEM containing 10% FBS and 1% penicillin-streptomycin. The virus-containing supernatant was collected 48 hours after transfection, in which the lentivirus supernatant was directly filtered with a 0.45 µm filter and then dispensed and stored at -80°C, while the retrovirus supernatant was filtered with a 0.45 µm filter and then concentrated with PEG800 (PEG800, Yeasen, Shanghai) before dispensing and storing at -80°C. The supernatant was then concentrated with PEG800 (PEG800, Shanghai) and stored at -80°C, and then dispensed and stored at -80°C. Flow cytometry analysis The prepared MHC G12D 10-mer and MHC G12D 9-mer tetramer proteins were mixed with APC-Streptavidin flow cytometry antibody (BioLegend, #405207) in a molar ratio of 1:1 and incubated on ice for 30 min. Jurkat-G12D-TCR stably transfected cells not expressing and expressing G12D 10-mer and G12D 9-mer, respectively, were harvested by centrifugation at 500×g for 3 min and rinsed 2–3 times with 1×PBS. Cells were then resuspended in 100 µL PBS with PE-TCR flow cytometry antibody (BioLegend, #109207) and APC-Streptavidin flow-through antibody incubated with tetramer protein and incubated for 30 min on ice protected from light. After incubation, cells were washed 2–3 times with PBS to remove excess antibody and then centrifuged at 500 x g for 3 minutes. The cell precipitate was resuspended with 500 µL of 1xPBS, and the fluorescent signal was quantified using a flow cytometer, and the data were analyzed using FlowJo software. NMR competition titration NMR samples of 0.2 mM G12D 10-mer and G12D 9-mer were prepared, respectively, in which the MHC A chain was labeled with 15 N and the B chain was not labeled. The dry powders of G12D 9-mer and G12D 10-mer peptides were prepared at the same time. The corresponding mass of G12D 9-mer peptide was added to the G12D 10-mer NMR samples according to the molar ratios of 0:1, 1:1, 2:1, 5:5, and 10:1, respectively. The results of the NMR titration were taken with different concentration gradients using the same experimental conditions, respectively. Similarly, the corresponding mass of G12D 10-mer peptide was added to the G12D 9-mer NMR samples according to the molar ratios of 0:1, 1:1, 2:1, 5:5, and 10:1, respectively, and the corresponding NMR results were taken after being fixed to the same volume. Molecular dynamics simulation The Desmond 2023 package, a freely available academic resource, was employed for conducting molecular dynamics (MD) simulations using the OPLS-AA 2005 force field 44 . The simulations were performed within an orthorhombic box measuring approximately 20 x 20 x 20 Å 3 , with periodic explicit single point charges (SPCs) water molecules and an appropriate number of counter ions to neutralize the system's overall charge. The system was dissolved in a 0.15 M NaCl solution. The MD simulations were carried out with periodic boundary conditions in the NPT ensemble to ensure the conservation of substance quantity (N), pressure (P), and temperature (T). Long-range electrostatic interactions were computed using the Nose-Hoover temperature coupling method 45 with a grid spacing of 0.8 Å. To decrease computation time, the RESPA integrator 46 was employed for reducing the frequency of time-consuming long-range interaction calculations. The real-space component of electrostatic and Van Der Waals interactions was truncated at 9 Å. The simulation process consisted of two stages of molecular dynamics (MD). Initially, a restrained MD simulation was conducted using Desmond's default relax protocol, where the protein and peptide backbone were constrained with a force constant of 100 kCal mol − 1 Å −2 , while the side chains were allowed to move freely. Once the system reached equilibrium, the subsequent stage, referred to as the unrestrained MD, was implemented. This involved a 100 ns NPT production simulation without any constraints. Configurations and interval energy were recorded every 100 ps. Declarations Data and software availability NMR data were acquired using VnmrJ Biopack software from Agilent, and processed using NMRPipe. The NMR pulse sequences used were Agilent Standard Package. Data analysis, including peak picking and resonance assignment, was conducted using XEASY. For chemical shift change analysis, peak intensities were analyzed using CcpNmr. Secondary structure prediction based on secondary chemical shift was carried out using TALOS+. Molecular dynamics simulations were conducted using the Desmond 4.5 package. Visualization and generation of molecular structure figures and images were performed using PyMOL. The crystallography data generated in this study have been deposited in the RCSB protein data bank (PDB) under the accession codes 8K4T (G12C), 8K4V (G12R), 8K50 (G12V), 9UV8 (G12D 9-mer). Accession Numbers The atomic structure coordinate and structural constraints have been deposited in the Protein Data Bank (PDB), accession numbers 8K50 (G12V), 8K4T (G12C), 8K4V (G12R), 9UV8 (G12D 9-mer). Acknowledgements We thank the staff at the Nuclear Magnetic Resonance System at the National Facility for Protein Science in Shanghai, Zhangjiang Laboratory (NFPS, ZJLab), China for providing technical support and assistance in data collection and analysis, and thank staff members at SSRF BL02U1, BL10U2 and BL19U1 for their technical assistance in X-ray diffraction data collection. Funding This work was supported by grants from National Natural Science Foundation of China (32301027), Shanghai Health Commission Clinical Research Special Youth Project (2022YQ079) to L.Z. Author contributions J.Z., Z.C., and L.Z. conceived and designed the study. J.Z., Q.W., X.X., Y.H., and P.L. prepared samples for NMR spectroscopy and X-ray crystallography. L.Z., J.Z., Q.W., and H.X. collected and analyzed NMR data. J.Z. and X.X. performed cell-based assays. K.X. analyzed crystallographic data and solved the crystal structures. S.W. carried out molecular dynamics simulations and subsequent analyses. L.Z. and Z.C. wrote the manuscript. M.W. provided technical support for data processing and analysis. Declaration of Interests The authors declare no conflict of interests. Contributor Information Linlin Zhao, Email: [email protected] . Ke Xu, Email: [email protected] . Shuqing Wang, Email: [email protected] . References June, C.H., O'Connor, R.S., Kawalekar, O.U., Ghassemi, S., and Milone, M.C. (2018). CAR T cell immunotherapy for human cancer. Science 359 , 1361-1365. 10.1126/science.aar6711. Baulu, E., Gardet, C., Chuvin, N., and Depil, S. (2023). TCR-engineered T cell therapy in solid tumors: State of the art and perspectives. Sci Adv 9 , eadf3700. 10.1126/sciadv.adf3700. Schumacher, T.N., Scheper, W., and Kvistborg, P. (2019). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6720638\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":466007451,\"identity\":\"ec72e383-87f5-4b49-b78b-2810ca2957d9\",\"order_by\":0,\"name\":\"Linlin 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Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Quanmeng\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":466007459,\"identity\":\"e09a4331-e987-4097-8cb1-427dc5e54e4f\",\"order_by\":8,\"name\":\"Yuchen He\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yuchen\",\"middleName\":\"\",\"lastName\":\"He\",\"suffix\":\"\"},{\"id\":466007460,\"identity\":\"47780eac-c6a0-45bf-bfff-eae591d96ac3\",\"order_by\":9,\"name\":\"Shuqing Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shuqing\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":466007461,\"identity\":\"85f8f44f-56ea-4d37-9fc3-a6e98de3492f\",\"order_by\":10,\"name\":\"Ke Xu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ke\",\"middleName\":\"\",\"lastName\":\"Xu\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-05-22 03:20:25\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6720638/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6720638/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1038/s42003-025-09285-0\",\"type\":\"published\",\"date\":\"2025-12-03T05:00:00+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":84023483,\"identity\":\"cb761618-c179-43cd-a9e4-3f4e91dabbc2\",\"added_by\":\"auto\",\"created_at\":\"2025-06-05 21:51:57\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1677560,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eNMR investigation of HLA-A*11:01 in presence of KRAS G12 wildtype peptide\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) Backbone resonance assignment of HLA-A*11:01 with β2M and KRAS G12 wildtype peptide (VVVGAGGVGK). 2D \\u003csup\\u003e1\\u003c/sup\\u003eH-\\u003csup\\u003e15\\u003c/sup\\u003eN TROSY-HSQC spectrum of 0.5 mM U- [\\u003csup\\u003e2\\u003c/sup\\u003eH, \\u003csup\\u003e15\\u003c/sup\\u003eN] HLA-A*11:01 was collected at 600 MHz (\\u003csup\\u003e1\\u003c/sup\\u003eH frequency) and 25°C.\\u003c/p\\u003e\\n\\u003cp\\u003e(B) Secondary structure consensus analysis. Structural alignment of HLA-A*11:01 (predicted from chemical shifts) with HLA-A*02:01 (PDB: 1AO7). Ribbon diagrams show sequence-matched secondary elements (α-helices: cylinders; β-strands: arrows). TALOS+-derived predictions (“GOOD”) with characteristic angles (F/Y = -60°/-40°±30°) indicate 80% agreement with crystal structures. Assigned residues marked with filled circles (●).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/08852e35ad7cff3946ba333a.png\"},{\"id\":84023485,\"identity\":\"45b4633d-9614-438e-a932-34646418ea6e\",\"added_by\":\"auto\",\"created_at\":\"2025-06-05 21:51:57\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1810004,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eKRAS G12 mutation-induced structural perturbations in HLA-A*11:01\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A-D) Chemical shift perturbation (ΔCS) analysis. Weighted ΔCS induced by G12X mutants (X = C/R/V/D) relative to WT. Significance threshold: ΔCS \\u0026gt; 0.04 ppm. To note, \\\"α2-α\\\" represents α2 helical outer region, \\\"α2-β\\\" represents α2 strand inner pocket region.\\u003c/p\\u003e\\n\\u003cp\\u003e(E-H) Structural mapping of CSP hotspots. CSP magnitude (ΔCS \\u0026gt; 0.04 ppm) projected onto HLA-A*11:01 crystal structure (PDB: 7OW3). Red spheres: perturbed residues. Dashed outlines: α2-helix (pink), peptide-binding β-sheet (orange).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/3c85d8c2cf4e4e7c2ce0a9e3.png\"},{\"id\":84023823,\"identity\":\"a8c3a49c-741d-4746-ab23-56b0808d109c\",\"added_by\":\"auto\",\"created_at\":\"2025-06-05 21:59:57\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":903292,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDistinct peptide conformations and MHC-I stability profiles among KRAS G12 mutations\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A-D) Different KRAS peptides binding mode on HLA-A*11:01 crystal structure. Left panels, side view from α2 domain side with peptide, position 12 shown as sticks circled with a dash line. Right panels, top-down view with peptide represented as sticks (N-terminus to the left) and HLA molecule shown as solid white surface. (A) WT: VVVGAGGVGK; (B) G12C: VVVGACGVGK; (C) G12R: VVVGARGVGK; (D) G12V: VVVGAVGVGK.\\u003c/p\\u003e\\n\\u003cp\\u003e(E) CHX-chase assay in 293T stable cells expressing MHC complex presenting different KRAS mutations. Cells were treated with 100 μg/mL cycloheximide (CHX) for 0, 6, 12, 18, 24, 48, 60 h. Intensity levels were analyzed by western blot.\\u003c/p\\u003e\\n\\u003cp\\u003e(F) Quantitative analysis of MHC stability. Relative protein remaining was normalized to Vinculin and quantified using ImageJ. **** (two-way ANOVA, n = 3).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/dd220dc1493b9ad695faaa81.png\"},{\"id\":84023487,\"identity\":\"c3d0e579-eeee-4f40-a1ef-4b68057e95c9\",\"added_by\":\"auto\",\"created_at\":\"2025-06-05 21:51:57\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1012892,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDistinct recognition patterns and biophysical characterization of G12D epitope variants\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) TCR binding kinetics analyzed by engineered Jurkat reporter cells. Flow cytometry quantification reveals 50-fold higher binding affinity for 10-mer G12D peptide compared to 9-mer variant.\\u003c/p\\u003e\\n\\u003cp\\u003e(B) Affinity quantification from panel A, presented as median fluorescence intensity (MFI), **** (two-way ANOVA, n = 3).\\u003c/p\\u003e\\n\\u003cp\\u003e(C) Structural basis of length dependent recognition. Crystal structure highlights critical conformational differences between 9-mer (green) and 10-mer (pink) G12D-MHC complexes (see Extended Data Fig. S4).\\u003c/p\\u003e\\n\\u003cp\\u003e(D) Competitive peptide displacement assay. Titration of excess 10-mer peptide (1:1 to 10:1 molar ratio) against 9-mer G12D-MHC monitored by TROSY-HSQC.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/5818faa1944b95b1e451c7f7.png\"},{\"id\":84023486,\"identity\":\"86e7012e-9854-459a-b324-e3450c74dec4\",\"added_by\":\"auto\",\"created_at\":\"2025-06-05 21:51:57\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":689909,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMolecular dynamics reveals enhanced 10-mer stability and interaction networks\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) The Root Mean Square Deviation (RMSD) values of the HLA (left Y-axis) and G12D peptide (Right Y-axis) heavy atoms from their starting positions of the HLA-G12D peptide complex. Left: G12D 10-mer; Right: G12D 9-mer.\\u003c/p\\u003e\\n\\u003cp\\u003e(B) HLA interactions with different G12D peptides monitored throughout the simulation. These interactions are categorized into four types: Hydrogen Bonds, Hydrophobic, Ionic and Water Bridges. G12D 10-mer; Right: G12D 9-mer.\\u003c/p\\u003e\\n\\u003cp\\u003e(C) Binding free energy profiles. MM/PBSA calculations show enhanced 10-mer stability (ΔG = -124 kcal/mol) versus 9-mer (-108 kcal/mol). Shaded regions indicate SEM across 5,000 frame subsampling.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/183de7be461803a679eebfb1.png\"},{\"id\":99676279,\"identity\":\"2d854631-3fa6-406a-bb80-82cf85ca93e7\",\"added_by\":\"auto\",\"created_at\":\"2026-01-07 08:07:26\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":7509832,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/d4d9269d-9f8f-40e4-9c96-a0ffef14e8c7.pdf\"},{\"id\":84023488,\"identity\":\"3c4ccbb6-3bf6-438c-892b-628dbc5b6689\",\"added_by\":\"auto\",\"created_at\":\"2025-06-05 21:51:57\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":3200827,\"visible\":true,\"origin\":\"\",\"legend\":\"Structure-Guided Analysis of KRAS G12 Mutants Reveals a Length-Encoded Immunogenic Advantage in G12D\",\"description\":\"\",\"filename\":\"SupDoc.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6720638/v1/0935e793fed9c333b7befe20.docx\"}],\"financialInterests\":\"There is \\u003cb\\u003eNO\\u003c/b\\u003e Competing Interest.\",\"formattedTitle\":\"Structure-Guided Analysis of KRAS G12 Mutants Reveals a Length-Encoded Immunogenic Advantage in G12D\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eAdoptive T cell therapies, including chimeric antigen receptor (CAR-T) and T cell receptor-engineered T cells (TCR-T), have transformed cancer immunotherapy by enabling precise targeting of tumor specific antigens (TSAs)\\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003e. These TSAs typically originate from somatic mutations and are processed into short peptides that are loaded onto major histocompatibility complex class I (MHC-I) molecules and displayed on the surface of tumor cells\\u003csup\\u003e\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e\\u003c/sup\\u003e. This peptide-MHC (pMHC) complex forms the molecular interface for T cell receptor (TCR) recognition, converting intracellular mutations into immunologically visible epitopes\\u003csup\\u003e\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u003c/sup\\u003e. A growing number of recurrent neoantigens derived from shared oncogenic drivers, such as KRAS, TP53, and PIK3CA, have been identified, offering opportunities for designing off-the-shelf TCRs with broad applicability\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR7 CR8 CR9\\\" citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eAmong these, mutations at glycine 12 (G12) of KRAS represent some of the most common oncogenic alterations across colorectal, pancreatic, and non-small cell lung cancers\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR12 CR13 CR14\\\" citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e. These substitutions lock KRAS in a constitutively active GTP-bound state, driving persistent oncogenic signaling through the MAPK and PI3K-AKT pathways\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR17 CR18\\\" citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u003c/sup\\u003e. TCR-T therapies targeting KRAS G12 mutant peptides have entered early-phase clinical trials and show promise\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR21\\\" citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u003c/sup\\u003e. However, clinical responses remain variable, particularly in patients harboring the G12D variant, raising critical questions about the structural and immunological determinants of effective antigen presentation\\u003csup\\u003e\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e\\u003c/sup\\u003e. While most efforts have focused on peptide sequence and HLA allele frequency, relatively little is known about how single residue mutations reshape the conformational landscape of pMHC complexes and modulate their immunogenic potential.\\u003c/p\\u003e \\u003cp\\u003eThis gap is particularly important in the context of HLA polymorphism. The structural compatibility between a given HLA allele and a mutant peptide determines whether a neoantigen will be efficiently presented and recognized by T cells\\u003csup\\u003e\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e\\u003c/sup\\u003e. HLA-A*11:01 is highly prevalent in East Asian populations and has been shown to present multiple KRAS G12-derived epitopes\\u003csup\\u003e\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e\\u003c/sup\\u003e. Yet even subtle changes in peptide length or side chain orientation can profoundly alter the surface topology of the pMHC complex, affecting both its biophysical properties and downstream TCR engagement\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR29 CR30\\\" citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u003c/sup\\u003e. This structural remodeling may underlie the differential immunogenicity and therapeutic outcomes observed among KRAS G12 variants, especially G12D, which despite its high frequency, often correlates with poor response to T cell-based therapies\\u003csup\\u003e\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eIn this study, we systematically interrogate how different KRAS G12 mutations, particularly G12D, modulate the presentation and recognition of mutant epitopes by HLA-A*11:01. Using an integrated structural and biophysical approach combining solution state nuclear magnetic resonance (NMR), X-ray crystallography, molecular dynamics simulations, and TCR binding assays, we reveal how single residue substitutions not only shift peptide conformation but also alter the stability and surface presentation of the resulting pMHC complexes. We find that G12D peptides can be presented as both a 9-mer and a 10-mer, but only the 10-mer adopts a stable conformation conducive to effective TCR recognition. Molecular dynamics simulations and NMR titration experiments further confirm that the 10-mer forms a more compact and energetically favorable complex with HLA-A*11:01. These results uncover an underappreciated layer of structural epitope regulation and offer mechanistic insights into how minimal sequence differences can reshape immune visibility, informing the rational design of next generation TCR-based immunotherapies targeting shared oncogenic mutations.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSolution NMR reveals proper folding and backbone assignment of the KRAS-HLA-A*11:01 complex\\u003c/h2\\u003e \\u003cp\\u003eSolution nuclear magnetic resonance (NMR) technology represents a potent method for investigating dynamic alterations within proteins, particularly the localized conformational changes that occur in structures upon interaction with various ligands. HLA-A, when presenting mutated peptide segments, forms a heterotrimer composed of HLA-A, peptide, and β2M (Figure \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eA). The extracellular domains of HLA-A*11:01 were refolded in vitro with β2-microglobulin (β2M) and a 10-mer wild-type KRAS peptide (VVVGAGGVGK), corresponding to the G12 position of KRAS. HLA-A*11:01 is one of the most prevalent HLA alleles in East Asian populations. The resulting pMHC-I complex was expressed in E. coli, isotopically labeled, refolded and analyzed using solution-state NMR spectroscopy to assess structural integrity and establish a basis for peptide-specific comparisons.\\u003c/p\\u003e \\u003cp\\u003eUniformly \\u003csup\\u003e\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e\\u003c/sup\\u003eH, \\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003eN, \\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003eC-labeled HLA-A*11:01 heavy chains were reconstituted with unlabeled β2M and peptide, and subjected to triple-resonance NMR experiments including HNCA, HN(CO)CA, HNCACB, CBCA(CO)NH, and HNCO. These experiments enabled backbone assignments for approximately 75% of non-proline residues (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). Assigned residues spanned all major secondary structure elements within the α1 and α2 domains, including β-strands forming the peptide-binding groove and adjacent α-helices. Regions that lacked unambiguous assignment were primarily localized to flexible loops, including the α1-α2 loop (residues 75\\u0026ndash;95) and the C-terminal hinge between α2 and α3 domains. These gaps are likely attributable to intermediate exchange broadening or insufficient signal-to-noise in these dynamic segments.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eOverall signal dispersion in the \\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003eH-\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003eN TROSY-HSQC spectra indicated a well folded, non-aggregated protein. Notably, residues lining the peptide-binding cleft, including positions in β-sheet 1 (residues 5\\u0026ndash;12) and α-helix 2 (residues 56\\u0026ndash;70), showed strong, well-resolved peaks, providing a basis for probing localized changes upon peptide mutation. Secondary structure predictions based on chemical shift data (\\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003eCα, \\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003eCβ, \\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003eC\\u0026rsquo;) using TALOS\\u0026thinsp;+\\u0026thinsp;revealed a pattern consistent with known crystal structures of HLA-A alleles, including HLA-A*02:01 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB), affirming that the recombinant complex adopts a native-like conformation in aqueous solution.\\u003c/p\\u003e \\u003cp\\u003eComparison of TROSY-HSQC spectra from selectively labeled β2M across complexes with different KRAS G12 variants revealed minimal spectral variation (Fig. \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eB), reinforcing the conclusion that β2M remains structurally stable and does not directly engage peptide residues. Therefore, all subsequent labeling and structural analyses focused on the HLA-A*11:01 heavy chain. Together, these NMR results validate the use of refolded HLA-A*11:01 complexes for high-resolution structural interrogation of KRAS-derived epitopes, establishing a robust platform for comparing peptide specific conformational effects.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eNMR chemical shift mapping reveals mutation-specific perturbations in the MHC groove\\u003c/h3\\u003e\\n\\u003cp\\u003eTo assess whether clinically relevant mutations at the KRAS G12 position affect the conformational landscape of the peptide-HLA complex in solution, we reconstituted HLA-A*11:01 complexes with four mutant KRAS peptides, G12C, G12R, G12V, G12D, and each bearing a single amino acid substitution at the G12 site. All complexes were analyzed using two dimensional \\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003eH-\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003eN TROSY-HSQC spectroscopies under identical conditions (Fig. S2). These variants represent the most frequently observed KRAS mutations across human cancers. Substantial chemical shift perturbations (CSPs) were detected in the HLA-A*11:01 heavy chain across the four mutant complexes, relative to the wild-type (WT) peptide (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA-D).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eDespite differing by only a single residue at position 12, each KRAS mutant peptide induced notable chemical shift perturbations (CSPs) in the HLA-A*11:01 heavy chain when compared to the wild-type complex. Among the variants, G12C and G12R induced prominent chemical shift changes in residues located within the α2 helix (annotated as \\u0026ldquo;α2-α\\u0026rdquo; in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA-B and highlighted with pink dashed lines in the structural models, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eE-F). This helix forms part of the outer wall of the peptide binding groove. In contrast, G12V and G12D triggered broader perturbations that extended beyond the α2-helix into the β sheet floor of the binding groove, particularly affecting residues in the α2-strand (\\u0026ldquo;α2-β\\u0026rdquo;; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eC and Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eG, orange dashed lines). Notably, G12D induced the most pronounced changes within this inner region (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eH), suggesting a substantial reorganization of peptide-MHC interactions.\\u003c/p\\u003e \\u003cp\\u003eThese results demonstrate that the side chain properties of different G12 mutations, ranging from polar (Asp, Arg) to nonpolar (Val, Cys), elicit unique conformational responses in the HLA-A*11:01 molecule. The observed residue specific perturbation patterns imply distinct binding topologies and potentially divergent immunogenic properties for each mutant epitope, warranting further investigation into their structural determinants and T cell recognition profiles.\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eDistinct peptide conformations and MHC-I stability profiles among KRAS G12 mutations\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFollowing the preliminary NMR chemical shift perturbation results, which indicated that different single point mutations at the KRAS G12 position caused substantial conformational differences in the HLA molecule in solution, we hypothesized that these mutations might alter the binding modes between the peptide and HLA-A*11:01. This structural divergence could underlie the ability of T cell receptors (TCRs) to precisely distinguish between different mutant pMHC complexes. To more intuitively dissect the structural basis of TCR recognition and directly compare the binding modes of different KRAS G12 mutants, we employed X-ray crystallography to solve the structures of HLA-A*11:01 complexes loaded with G12C, G12R, and G12V peptides. For G12D, given that its structure had already been determined in previous studies, we integrated published crystallographic data into the present comparative analysis without repeating structural determination.\\u003c/p\\u003e\\n\\u003cp\\u003eHigh quality crystal structures were obtained for the three newly determined G12 variants, with resolutions of 2.3 \\u0026Aring; (G12C), 3.1 \\u0026Aring; (G12R), and 2.8 \\u0026Aring; (G12V), respectively (Fig. 3A-D). Structural analysis revealed that the N- and C-terminal residues of all four peptides, including G12D, occupied highly conserved spatial positions within the A and F pockets of HLA-A*11:01. The backbone polar atoms of the three N-terminal valine residues formed robust hydrogen bonds with residues such as E87 in the A pocket, while the C-terminal lysine residue and the free carboxyl group established multiple interactions with D101, Y108, K170, and others in the F pocket (Fig. S3). This binding mode aligns closely with the canonical peptide presentation sites observed in classical HLA-A molecules, indicating that the primary anchoring regions for different KRAS G12 mutant peptides remain conserved. These findings suggest that the major differences in TCR recognition are unlikely to involve the N- or C-terminal regions of the peptide.\\u003c/p\\u003e\\n\\u003cp\\u003eIn contrast, substantial structural variations were observed near the mutation site at position 12. The side chains of G12C and G12R mutants were both oriented outward toward the solvent (Fig. 3B, 3C) and did not interact directly with the internal \\u0026alpha;2 domain of HLA. By comparison, the side chains of G12V and G12D mutants adopted distinct conformations, extending inward into the peptide-binding groove and forming strong contacts with both the \\u0026alpha;2 helix and the \\u0026beta;-sheet floor. In the wild-type, G12C, and G12R complexes, no comparable interactions with the \\u0026beta;-sheet were observed (Fig. 3D, Fig. S3). These crystallographic findings are highly consistent with the earlier NMR chemical shift perturbation data, further corroborating the notion that different G12 mutations modulate the conformational landscape of HLA-A*11:01 in distinct ways.\\u003c/p\\u003e\\n\\u003cp\\u003eDetailed epitope analysis revealed that although both G12C and G12R mutants displayed solvent exposed side chains, the spatial and electrostatic properties differed significantly. The G12C side chain is relatively small and neutral, whereas G12R possesses a bulkier, positively charged side chain, which theoretically offers a larger and more distinctive surface for TCR engagement. This structural feature may contribute to the improved immunogenicity observed for G12R compared to G12C\\u003csup\\u003e34\\u003c/sup\\u003e. Conversely, although G12D also introduces a highly distinctive side chain in terms of size and charge, its insertion deep into the HLA binding groove rather than exposure to the solvent likely compromises its visibility to TCRs, potentially diminishing its immunogenic potential\\u003csup\\u003e33,35\\u003c/sup\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003eGiven these two markedly distinct epitope presentations among the KRAS G12 mutants, we next asked whether these structural differences would affect the overall stability of the MHC-I complexes, thereby influencing immune recognition (Fig. 3E-F). To address this question, we established monoclonal 293T cell lines stably expressing the KRAS G12C, G12R, G12V, or G12D mutant pMHC-I complexes. Cycloheximide (CHX) was used to block new protein synthesis, and cells were harvested at different time points to monitor the degradation kinetics of the pMHC-I complexes by western blotting. The results revealed that the G12C, G12R, and G12V complexes exhibited comparable degradation rates, whereas the G12D complex degraded substantially faster than the other three variants. Integrating these findings with the crystallographic epitope analysis suggests that KRAS G12D may represent a particularly challenging mutation type for immune targeting, characterized by both suboptimal antigen presentation and reduced MHC-I complex stability.\\u003c/p\\u003e\\n\\u003ch3\\u003eA single residue shift in KRAS G12D reconfigures the HLA epitope for selective TCR recognition\\u003c/h3\\u003e\\n\\u003cp\\u003eGiven the potential challenges associated with targeting KRAS G12D mutations in immunotherapy, we next focused on elucidating the structural and biophysical features of this mutation to inform the rational design of TCR-T therapies. In the context of HLA-A*11:01, G12D derived epitopes can be presented in two distinct peptide lengths: a 9-mer (VVGADGVGK) and a 10-mer (VVVGADGVGK). Despite their high sequence similarity and presumed similarity in HLA binding modes, our experimental data revealed unexpectedly divergent TCR recognition profiles between the two. A Jurkat cell line was engineered to stably express a TCR specific for the G12D 10-mer. Using pMHC tetramers constructed with either the 9-mer or 10-mer peptide, we performed flow cytometric analysis to assess binding. Strikingly, the TCR recognized the 10-mer with high specificity, while binding to the 9-mer tetramer was negligible, less than 2% of the signal observed with the 10-mer (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA-B). This pronounced functional discrepancy, despite the presence of only a single residue difference, suggested substantial differences in the overall structure or stability of the respective peptide-MHC complexes.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eTo investigate the underlying structural basis, we solved the crystal structure of the HLA-A*11:01-G12D 9-mer complex and compared it with the previously determined structure of the MHC G12D 10-mer complex (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eC). As expected, the N- and C-terminal residues of both peptides aligned well within the canonical A and F pockets of HLA-A*11:01, consistent with the conserved anchoring mode observed across other pMHC structures. However, dramatic structural divergence emerged at the central mutation site. In the 10-mer, the aspartate side chain at position 12 projected inward toward the binding groove, whereas in the 9-mer, the same side chain was solvent exposed. Additionally, residues 4 to 6 in the 9-mer adopted a bent conformation that deviated from the α2 helix and curved toward the α1 helix, establishing a specific electrostatic interaction with HLA residue Thr73. This marked shift in peptide trajectory and surface presentation at the core of the binding groove likely explains why the TCR selectively engages the 10-mer but not the 9-mer.\\u003c/p\\u003e \\u003cp\\u003eBeyond structural insights, we assessed the relative binding stability of the two peptide-MHC complexes using NMR titration assays. Stepwise titration of excess 10-mer peptide into the 9-mer-MHC complex resulted in progressive chemical shift perturbations in the HSQC spectrum, consistent with competitive displacement of the 9-mer (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eD). In contrast, the addition of excess 9-mer peptide into the 10-mer-MHC complex failed to induce comparable spectral shifts (Fig. S4), indicating that the 9-mer was unable to displace the more stably bound 10-mer (Fig. S5A). These results provide complementary evidence that the 10-mer forms a tighter, more stable complex with HLA-A*11:01, whereas the 9-mer binds less stably and is likely presented less efficiently. Such differences in stability and surface topology may underlie the stark contrast in TCR recognition, and further highlight the structural and biophysical constraints involved in identifying TCRs with high specificity toward G12D neoantigens.\\u003c/p\\u003e\\n\\u003ch3\\u003eMolecular dynamics simulation reveals superior stability and binding affinity of G12D 10-mer over 9-mer\\u003c/h3\\u003e\\n\\u003cp\\u003eTo further evaluate the energetic and structural differences in how G12D 9-mer and G12D 10-mer peptides engage HLA-A*11:01, we performed all-atom molecular dynamics (MD) simulations using the Desmond software package. The systems were parameterized with the OPLS-AA 2005 force field, solvated in an SPC explicit water model, and charge neutralized with 0.15 M NaCl. Following a 2 ns relaxation protocol, each peptide-MHC complex underwent a 100 ns production simulation under isothermal isobaric (NPT) conditions at 300 K and 1 atm. Trajectory snapshots were recorded every 100 ps for downstream structural and energetic analyses. Analysis of the simulation trajectories revealed that the G12D 10-mer complex exhibited greater conformational stability throughout the simulation. Root mean square deviation (RMSD) analysis of the protein backbone showed that the 10-mer complex stabilized within ~\\u0026thinsp;50 ns and maintained lower overall fluctuations than the 9-mer complex (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eTo quantitatively assess the binding affinity of the two peptides, we performed Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy calculations on both complexes. From each 100 ns trajectory, 1,000 evenly spaced snapshots were extracted (1 per 100 ps) for energy decomposition. The results demonstrated that the G12D 10-mer exhibited a significantly lower binding free energy (ΔG_bind) compared to the 9-mer, indicating tighter and more thermodynamically stable association with HLA-A*11:01 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eC). These findings are in strong agreement with the NMR titration results described above and further support the notion that the 10-mer peptide is preferentially presented and more stable in the MHC groove, potentially enhancing its immunogenic potential.\\u003c/p\\u003e \\u003cp\\u003eInteraction profiling revealed that the 10-mer established a larger number of persistent hydrogen bonds and hydrophobic contacts within the HLA binding groove. Moreover, its more compact conformation at the interface likely reduces entropic penalties upon binding, thereby contributing to its superior affinity (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eB, S5B-C). Together, these simulation results provide atomic resolution evidence that G12D 10-mer forms a more stable pMHC complex than the 9-mer. These findings offer critical mechanistic insights for peptide selection in TCR-T design and suggest that the 10-mer may serve as a more favorable immunotherapeutic target with respect to both TCR screening and clinical efficacy.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThe KRAS G12 mutation represents one of the most prevalent oncogenic alterations across multiple cancer types and has emerged as a prominent target for T cell-based immunotherapy. However, despite the shared mutation site, clinical responses to TCR-engineered T cell therapies targeting KRAS G12 variants have been inconsistent, suggesting a potential structural basis for differential immunogenicity\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR37\\\" citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e\\u003c/sup\\u003e. In this study, we systematically characterized how distinct KRAS G12 mutations, and in particular the G12D variant, remodel the peptide-HLA-A*11:01 landscape to influence immune recognition. By integrating solution state NMR, X-ray crystallography, and molecular dynamics simulations with cell-based stability assays and functional TCR binding analyses, we demonstrate that single amino acid changes at position 12 not only alter the conformation of the peptide-MHC complex but also significantly impact its structural stability and capacity for TCR engagement. Our findings reveal that G12D peptides, despite their high oncogenic relevance, pose unique challenges for antigen presentation and TCR recognition, underscoring the need to consider structural epitope configurations rather than peptide sequence alone when designing TCR-based immunotherapies.\\u003c/p\\u003e \\u003cp\\u003eAcross all KRAS G12 variants examined, the terminal anchoring of peptides within the A and F pockets of HLA-A*11:01 remained conserved, as evidenced by both crystal structures and NMR chemical shift patterns. This architectural preservation suggests that differences in TCR recognition are unlikely to stem from N- or C-terminal interactions. Instead, our structural analyses consistently pinpointed the central mutation site, position 12, as the primary determinant of epitope conformation and immunogenic potential. While the side chains of G12C and G12R extend outward from the MHC groove and remain solvent accessible, facilitating potential TCR contact, those of G12V and especially G12D adopt inward-facing conformations. The G12D side chain in particular inserts deeply into the groove, forming intramolecular contacts with HLA residues such as R114, thereby masking its identity and minimizing its exposure to the immune repertoire. These divergent orientations, driven by side chain size, charge, and polarity, fundamentally reshape the physicochemical topology of the peptide-MHC surface and likely underlie the sharp functional contrast in TCR recognition observed across variants.\\u003c/p\\u003e \\u003cp\\u003eThis complexity is further compounded by the existence of multiple peptide registers for the same G12D mutation. In the context of HLA-A*11:01, both a 9-mer (VVGADGVGK) and a 10-mer (VVVGADGVGK) can be endogenously presented, yet they give rise to dramatically different immunological outcomes. Despite differing by only a single N-terminal valine, structural and biophysical analyses revealed that these two peptides adopt distinct conformations within the MHC groove. Crystallographic comparison demonstrated that while their terminal anchoring remains aligned, the central region diverges sharply: the 10-mer buries the aspartate side chain within the groove, whereas the 9-mer presents the same residue outward, accompanied by a conformational bend away from the α2 helix toward α1, forming a specific electrostatic contact with Thr73 of the HLA. These shifts generate structurally non-overlapping epitopes and explain why a TCR selected against the 10-mer fails to recognize the 9-mer, despite near-identical sequences. This finding highlights that even subtle differences in peptide length can drive topological reorganization of the pMHC surface, redefining what is accessible for TCR surveillance and thereby shaping the immunogenic hierarchy among candidate epitopes.\\u003c/p\\u003e \\u003cp\\u003eThe marked differences in epitope topology between the G12D 9-mer and 10-mer peptides are further substantiated by their distinct binding stabilities to HLA-A*11:01. Competitive NMR titration experiments revealed that the 10-mer could effectively displace the 9-mer from preformed pMHC complexes, whereas the reverse was not observed, indicating a clear thermodynamic advantage for the longer peptide. Furthermore, MM/GBSA free energy calculations confirmed that the 10-mer forms a more stable and energetically favorable association with HLA-A*11:01. These converging data indicate that the additional N-terminal valine in the 10-mer not only extends peptide-MHC interactions but also induces a more compact, lower entropy binding pose, enhancing both structural stability and immunogenic presentation.\\u003c/p\\u003e \\u003cp\\u003eFrom a therapeutic perspective, the superior conformational stability and enhanced TCR engagement profile of the G12D 10-mer strongly advocate for its prioritization in antigen selection and TCR design pipelines. While the G12D mutation is among the most common KRAS alterations, its immunogenicity has been historically difficult to harness, in part due to the ambiguous or unstable nature of its presented epitopes. Our integrated structural and biophysical data provide compelling evidence that not all G12D-derived peptides are equal, minor differences in length and conformation can have major consequences for TCR accessibility and immune activation. These insights highlight the critical importance of resolving pMHC topology at atomic resolution when selecting neoantigen targets. Future strategies incorporating structure-guided TCR engineering, in silico modeling of peptide registers, and machine learning-based TCR affinity prediction will benefit from this framework, enabling more precise targeting of cryptic but therapeutically actionable mutations like KRAS G12D.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eExpression and Purification of KRAS-HLA protein complex samples\\u003c/h2\\u003e \\u003cp\\u003eThe DNA sequences corresponding to the human HLA-A*11:01 isoform (residues 25–299) and β2M (residues 21–119) were cloned from the human cDNA library and inserted into the Pet28a and Pet21a vector separately. These constructs were then transformed into E. coli strain BL21 (DE3) cells. For NMR sample preparation, cells were cultured in M9 minimal media supplemented with stable isotopes, tailored to the specific NMR experimental requirements. For crystallography, cells were cultured in LB media. Protein expression was induced when the bacteria culture reached an absorbance of ~ 0.8 at 600 nm. Isopropyl β-D-1-thiogalactopyranoside (IPTG) at a concentration of 500 µM was used to induce protein expression for both HLA and β2M constructs at 37°C. Cell pellets were resuspended in Lysis Buffer (50 mM Tris-HCl/pH 8.0, 0.5 mM EDTA, 1 mM DTT, 1 mM PMSF). The cells were sonicated under 300 power cycle twice to achieve complete lysis, using a sonicator (Scientz-IID), and then centrifuged at 40,000 × g for 30 minutes to collect inclusion body pellets. The inclusion bodies were washed three times with PBS buffer (20 mM Phosphate Buffer/pH7.2,150 mM NaCl) and dissolved in Denaturing Buffer (20 mM Tris-HCl/pH8.0, 6M Guanidine-HCl, 0.5 mM EDTA, 1 mM DTT, 0.2 mM PMSF) overnight. Cell debris was removed by another centrifugation step at 40,000 × g for 30 minutes. The peptide powder was synthesized by GenScript. The protein refolding system consisted of 6 mg HLA-A*11:01, 2 mg β2M, and 1 mg peptide. Firstly, these components were mixed together and then slowly added dropwise to 50 mL of Refolding Buffer (100 mM Tris-HCl/pH 8.0, 3 M Urea, 0.4 M Arginine, 0.16% Glutathione reduced, 0.03% Glutathione oxidized and 2mM EDTA). The mixture was placed at 25°C and stirred for three hours. The refolding system was then centrifuged at 40,000 × g for 30 minutes and subsequently subjected to three rounds of dialysis in a 5L buffer system at 4°C. The refolded supernatant was concentrated using the HiTrap Q FF column and further purified by size exclusion using the Increase Superdex-200 10/300GL Cytiva column in FPLC Buffer (20 mM Phosphate Buffer/pH7.2,150 mM NaCl). A standard nuclear magnetic resonance (NMR) sample typically contained approximately 0.5 mM of the target molecules (HLA: β2M: Peptide = 1:1:1) in NMR Buffer (20 mM Phosphate Buffer/pH7.2,150 mM NaCl,10% D2O). The crystal samples were purified and refolded following the same protocol.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eNMR backbone resonance assignment\\u003c/h2\\u003e \\u003cp\\u003eAll NMR data of HLA-A*11:01 TROSY spectra presented with KRAS G12 mutant variants were recorded at 25°C by VnmrJ Biopack on Agilent 800 or 600 MHz spectrometer equipped with cryogenic probes. NMR data were processed and analyzed by NMRPipe\\u003csup\\u003e\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u003c/sup\\u003e, XEASY\\u003csup\\u003e\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u003c/sup\\u003e, and CcpNmr Analysis v.2\\u003csup\\u003e41\\u003c/sup\\u003e. Backbone chemical shift assignments of HLA-A*11:01 were carried out using a set of standard triple resonance experiments, including the TROSY version of HNCA, HN(CO)CA, HN(CA)CO, HNCO, and HNCACB, HN(CO)CACB\\u003csup\\u003e\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e\\u003c/sup\\u003e on a (\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003eN, \\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003eC, 85% \\u003csup\\u003e2\\u003c/sup\\u003eH)-labeled sample at a \\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003eH frequency of 600 MHz.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eNMR chemical shift perturbation experiment\\u003c/h2\\u003e \\u003cp\\u003eThe protein complex between different KRAS G12 mutant peptides, HLA-A*11:01 and β2M were prepared in the same condition and collected a series of TROSY-HSQC spectra on Agilent 800MHz. The combined chemical-shift differences (\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:\\\\varDelta\\\\:{\\\\delta\\\\:}_{N}^{i}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e) were calculated for each residue using the formula\\u003csup\\u003e\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e\\u003c/sup\\u003e:\\u003c/p\\u003e\\u003cdiv id=\\\"Equa\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equa\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\:\\\\varDelta\\\\:{\\\\delta\\\\:}_{comb}^{i}=\\\\sqrt{{（{\\\\omega\\\\:}_{H}\\\\varDelta\\\\:{\\\\delta\\\\:}_{H}^{i}）}^{2}+{（{\\\\omega\\\\:}_{N}\\\\varDelta\\\\:{\\\\delta\\\\:}_{N}^{i}）}^{2}}$$\\u003c/div\\u003e\\u003c/div\\u003e\\u003cp\\u003e\\u003c/p\\u003e \\u003cp\\u003ewhere \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:\\\\varDelta\\\\:{\\\\delta\\\\:}_{H}^{i}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:\\\\varDelta\\\\:{\\\\delta\\\\:}_{N}^{i}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e are \\u003csup\\u003e\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u003c/sup\\u003eH and \\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003eN chemical-shift perturbations between KRAS-mutant and KRAS-WT, respectively, and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{\\\\omega\\\\:}_{H}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e = 1.00 and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{\\\\omega\\\\:}_{N}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e = 0.15 are normalization factors.\\u003c/p\\u003e \\u003cp\\u003eIn the G12D NMR competition experiment, the G12V TROSY-HSQC spectrum was initially collected on Agilent 800 MHz. Subsequently, a tenfold concentration of mutant peptide mixtures, along with the wild-type (WT), was added to the NMR sample and incubated overnight at 4°C. The mixed sample was then purified to remove any excess peptides using size exclusion chromatography with the Increase Superdex-200 10/300GL Cytiva column, following the same protocol as described above.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCrystallography\\u003c/h2\\u003e \\u003cp\\u003eThe KRAS-HLA-β2M protein complex was incubated on ice for 30 minutes. Subsequently, the sample was prepared for crystallization using the sitting-drop vapor diffusion method at 20°C. The reservoir solution for each protein is as follows: G12C(0.1 M ammonium acetate, 0.1 M Bis-Tris PH5.2, PEG4000 19%), G12R (0.2 M Lithium sulfate, 0.1 M Bis-Tris PH5.8, PEG3350 27%), G12V(0.2 M Lithium sulfate, 0.1 M Bis-Tris PH5.5, PEG3350 27%), G12D 9-mer (27% PEG3350, 0.1 M Bis-Tris, 0.2 M Lithium sulfate, additive 0.1 M Spermidine). The crystals were frozen in liquid nitrogen using a cryo-protectant of mother liquor supplemented with 30% (v/v) glycerol prior to data collection.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCHX stability assay\\u003c/h2\\u003e \\u003cp\\u003eMHC-G12 mutations in 293T stable cell lines were cultured to 80%-90% and treated with cycloheximide (CHX, AbMole, #M4879) at a final concentration of 100 µg/mL. Cells were harvested by centrifugation at various time points at 0, 6, 12, 18, 24, 48 and 60 hours. After resuspension in RIPA lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 0.1% SDS, 0.5% sodium deoxycholate, 1% Triton X-100) containing a protease inhibitor (ABclonal, #RM02916), the cells were incubated on ice for 30 min. Cell lysates were centrifuged at 12,000 rpm for 15 mins at 4°C and the supernatant was collected. Protein samples were mixed with 5× Sampling Buffer and denatured in a metal bath at 99°C for 10 minutes. Proteins were separated by SDS-PAGE and transferred to a nitrocellulose membrane (Millipore, #HATF00010). Membranes were blocked with 5% skimmed milk (Sangon Biotech, #A600669) in TBS-T for 1 hr and then rinsed three times with TBS-T. Membranes were incubated with primary antibody (rabbit anti-HA, Abmart, #ABT2041) at 4°C overnight. The next day, the membrane was washed three times with TBS-T and incubated with secondary antibody (HRP anti-rabbit, ABclonal, #AS003) for 1 hour at room temperature. Chemiluminescent signals were detected using ECL substrate (Sigma, #WBKLS0100) and quantified using ImageJ software.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMHC-I tetramer preparation\\u003c/h2\\u003e \\u003cp\\u003eThe target proteins, MHC G12D 10-mer and MHC G12D 9-mer, were first biotinylated according to a biotinylated reaction system of 50 uM target protein, 50 mM Bicine, 10mM MgCl\\u003csub\\u003e2\\u003c/sub\\u003e, 1/100 BirA, 1mM biotin, and 10 mM ATP for 40 minutes at room temperature, and passed through a molecular sieve after the biotinylation reaction was complete. The tetramers were then prepared, which entailed dissolving the G12D 10-mer and G12D 9-mer peptide dry powders in DMSO at a concentration of 10 mM (10 mg/ml). The peptides were further diluted to 400 µM with PBS and stored on ice. Add 20 µL of diluted peptide (400 µM) and 20 µL of target protein (200 µg/ml) to a 96-well plate, mix well and seal the plate; centrifuge the plate at 2500x g for 2 minutes at 4°C and collect the lower layer of liquid. Remove the seal; place the plate on ice and irradiate with a UV lamp for 30 minutes (the UV lamp should be 2–5 cm away from the sample). Seal the plate; incubate at 37°C for 30 minutes in the dark. At the end of incubation, take 30 µL of the displaced monomer into a 1.5ml EP tube, add 3.3 µL of SA-APC, mix well, and place on ice for incubation in the dark. After incubation, add 2.4 µL of blocking buffer to terminate the reaction. The reaction is terminated by the addition of 2.4 µL blocking buffer and then placed in the refrigerator at 4°C overnight (or incubated on ice for 30 minutes).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRetroviral production for Jurkat cell transduction\\u003c/h2\\u003e \\u003cp\\u003eLentiviral supernatants encoding different mutants of MHC G12_ and retroviral supernatants encoding the KRAS G12D TCR were prepared using HEK 293T cells. For lentivirus production, HEK 293T cells were cotransfected with lentiviral plasmids containing the relevant genes, packaging plasmids pSPAX2 and pMD2.G in a ratio of 4:3:1. For retrovirus production, HEK 293T cells were cotransfected with the retroviral plasmid containing the gene of interest and the packaging plasmids gag-pol and VSVG in a 4:3:1 ratio. When the density of HEK 293T cells reached 70–80%, the medium was removed and 5 mL of medium without DMEM was added. Cells were transfected with polyethyleneimine (PEI, PolySciences, Inc., USA) and plasmids at a ratio of 3:1. After 5 hours of incubation at 37°C with 5% CO\\u003csub\\u003e2\\u003c/sub\\u003e, cells were supplemented with 10 mL of fresh DMEM containing 10% FBS and 1% penicillin-streptomycin. The virus-containing supernatant was collected 48 hours after transfection, in which the lentivirus supernatant was directly filtered with a 0.45 µm filter and then dispensed and stored at -80°C, while the retrovirus supernatant was filtered with a 0.45 µm filter and then concentrated with PEG800 (PEG800, Yeasen, Shanghai) before dispensing and storing at -80°C. The supernatant was then concentrated with PEG800 (PEG800, Shanghai) and stored at -80°C, and then dispensed and stored at -80°C.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eFlow cytometry analysis\\u003c/h2\\u003e \\u003cp\\u003eThe prepared MHC G12D 10-mer and MHC G12D 9-mer tetramer proteins were mixed with APC-Streptavidin flow cytometry antibody (BioLegend, #405207) in a molar ratio of 1:1 and incubated on ice for 30 min. Jurkat-G12D-TCR stably transfected cells not expressing and expressing G12D 10-mer and G12D 9-mer, respectively, were harvested by centrifugation at 500×g for 3 min and rinsed 2–3 times with 1×PBS. Cells were then resuspended in 100 µL PBS with PE-TCR flow cytometry antibody (BioLegend, #109207) and APC-Streptavidin flow-through antibody incubated with tetramer protein and incubated for 30 min on ice protected from light. After incubation, cells were washed 2–3 times with PBS to remove excess antibody and then centrifuged at 500 x g for 3 minutes. The cell precipitate was resuspended with 500 µL of 1xPBS, and the fluorescent signal was quantified using a flow cytometer, and the data were analyzed using FlowJo software.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eNMR competition titration\\u003c/h2\\u003e \\u003cp\\u003eNMR samples of 0.2 mM G12D 10-mer and G12D 9-mer were prepared, respectively, in which the MHC A chain was labeled with \\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003eN and the B chain was not labeled. The dry powders of G12D 9-mer and G12D 10-mer peptides were prepared at the same time. The corresponding mass of G12D 9-mer peptide was added to the G12D 10-mer NMR samples according to the molar ratios of 0:1, 1:1, 2:1, 5:5, and 10:1, respectively. The results of the NMR titration were taken with different concentration gradients using the same experimental conditions, respectively. Similarly, the corresponding mass of G12D 10-mer peptide was added to the G12D 9-mer NMR samples according to the molar ratios of 0:1, 1:1, 2:1, 5:5, and 10:1, respectively, and the corresponding NMR results were taken after being fixed to the same volume.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMolecular dynamics simulation\\u003c/h2\\u003e \\u003cp\\u003eThe Desmond 2023 package, a freely available academic resource, was employed for conducting molecular dynamics (MD) simulations using the OPLS-AA 2005 force field\\u003csup\\u003e\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e\\u003c/sup\\u003e. The simulations were performed within an orthorhombic box measuring approximately 20 x 20 x 20 Å\\u003csup\\u003e\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u003c/sup\\u003e, with periodic explicit single point charges (SPCs) water molecules and an appropriate number of counter ions to neutralize the system's overall charge. The system was dissolved in a 0.15 M NaCl solution.\\u003c/p\\u003e \\u003cp\\u003eThe MD simulations were carried out with periodic boundary conditions in the NPT ensemble to ensure the conservation of substance quantity (N), pressure (P), and temperature (T). Long-range electrostatic interactions were computed using the Nose-Hoover temperature coupling method\\u003csup\\u003e\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e\\u003c/sup\\u003e with a grid spacing of 0.8 Å. To decrease computation time, the RESPA integrator\\u003csup\\u003e\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e\\u003c/sup\\u003e was employed for reducing the frequency of time-consuming long-range interaction calculations. The real-space component of electrostatic and Van Der Waals interactions was truncated at 9 Å.\\u003c/p\\u003e \\u003cp\\u003eThe simulation process consisted of two stages of molecular dynamics (MD). Initially, a restrained MD simulation was conducted using Desmond's default relax protocol, where the protein and peptide backbone were constrained with a force constant of 100 kCal mol\\u003csup\\u003e− 1\\u003c/sup\\u003eÅ\\u003csup\\u003e−2\\u003c/sup\\u003e, while the side chains were allowed to move freely. Once the system reached equilibrium, the subsequent stage, referred to as the unrestrained MD, was implemented. This involved a 100 ns NPT production simulation without any constraints. Configurations and interval energy were recorded every 100 ps.\\u003c/p\\u003e \\u003c/div\\u003e \"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eData and software availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNMR data were acquired using VnmrJ Biopack software from Agilent, and processed using NMRPipe. The NMR pulse sequences used were Agilent Standard Package. Data analysis, including peak picking and resonance assignment, was conducted using XEASY. For chemical shift change analysis, peak intensities were analyzed using CcpNmr. Secondary structure prediction based on secondary chemical shift was carried out using TALOS+. Molecular dynamics simulations were conducted using the Desmond 4.5 package. Visualization and generation of molecular structure figures and images were performed using PyMOL. The crystallography data generated in this study have been deposited in the RCSB protein data bank (PDB) under the accession codes 8K4T (G12C), 8K4V (G12R), 8K50 (G12V), 9UV8 (G12D 9-mer). \\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAccession Numbers \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe atomic structure coordinate and structural constraints have been deposited in the Protein Data Bank (PDB), accession numbers 8K50 (G12V), 8K4T (G12C), 8K4V (G12R), 9UV8 (G12D 9-mer).\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe thank the staff at the Nuclear Magnetic Resonance System at the National Facility for Protein Science in Shanghai, Zhangjiang Laboratory (NFPS, ZJLab), China for providing technical support and assistance in data collection and analysis, and thank staff members at SSRF BL02U1, BL10U2 and BL19U1 for their technical assistance in X-ray diffraction data collection. \\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported by grants from National Natural Science Foundation of China (32301027), Shanghai Health Commission Clinical Research Special Youth Project (2022YQ079) to L.Z.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eJ.Z., Z.C., and L.Z. conceived and designed the study. J.Z., Q.W., X.X., Y.H., and P.L. prepared samples for NMR spectroscopy and X-ray crystallography. L.Z., J.Z., Q.W., and H.X. collected and analyzed NMR data. J.Z. and X.X. performed cell-based assays. K.X. analyzed crystallographic data and solved the crystal structures. S.W. carried out molecular dynamics simulations and subsequent analyses. L.Z. and Z.C. wrote the manuscript. M.W. provided technical support for data processing and analysis.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of Interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no conflict of interests.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eContributor Information\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLinlin Zhao, Email: lzhao@tongji.edu.cn.\\u003c/p\\u003e\\n\\u003cp\\u003eKe Xu, Email: kx2129@tongji.edu.cn.\\u003c/p\\u003e\\n\\u003cp\\u003eShuqing Wang, Email: wangshuqing@tmu.edu.cn.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eJune, C.H., O\\u0026apos;Connor, R.S., Kawalekar, O.U., Ghassemi, S., and Milone, M.C. (2018). CAR T cell immunotherapy for human cancer. Science \\u003cem\\u003e359\\u003c/em\\u003e, 1361-1365. 10.1126/science.aar6711.\\u003c/li\\u003e\\n\\u003cli\\u003eBaulu, E., Gardet, C., Chuvin, N., and Depil, S. (2023). 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Phys Rev Lett \\u003cem\\u003e68\\u003c/em\\u003e, 2496-2499. 10.1103/PhysRevLett.68.2496.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"nature-portfolio\",\"isNatureJournal\":true,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Nature Portfolio\",\"twitterHandle\":\"\",\"acdcEnabled\":false,\"dfaEnabled\":false,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"KRAS G12 Mutations, MHC-I Restriction, T Cell Recognition, Structural Immunology, Neoantigen Presentation\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6720638/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6720638/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eKRAS G12 mutations are frequent oncogenic drivers, yet their differential immunogenicity complicates T cell-based therapies. Here, we integrate structural, biophysical, and functional analyses to examine how KRAS G12 variants remodel peptide-MHC-I (pMHC) architecture and T cell receptor (TCR) recognition. Using HLA-A*11:01, we show that single residue substitutions at position 12 induce distinct conformational changes in the MHC groove, with G12D uniquely destabilizing the complex through a buried aspartate side chain. Notably, G12D peptides adopt two registers, a 9-mer and a 10-mer, that diverge sharply in structure and immunogenicity. The 10-mer forms a compact, stable pMHC with a TCR-accessible surface, while the 9-mer adopts a bent conformation incompatible with recognition. Molecular dynamics and NMR titration confirm the superior stability and binding affinity of the 10-mer. These results highlight how peptide length and conformation critically shape immune visibility, offering mechanistic insight for optimizing TCR-T therapies against elusive neoantigens like KRAS G12D.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Structure-Guided Analysis of KRAS G12 Mutants Reveals a Length-Encoded Immunogenic Advantage in G12D\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-05 21:51:52\",\"doi\":\"10.21203/rs.3.rs-6720638/v1\",\"editorialEvents\":[],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"communications-biology\",\"isNatureJournal\":true,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"commsbio\",\"sideBox\":\"Learn more about [Communications Biology](http://www.nature.com/commsbio/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Communications Biology\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"Communications Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"ad5e7c3c-90f6-4763-a906-72bb4d6a09e5\",\"owner\":[],\"postedDate\":\"June 5th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":49474955,\"name\":\"Biological sciences/Cancer/Cancer therapy/Cancer immunotherapy\"},{\"id\":49474956,\"name\":\"Biological sciences/Immunology/Immune evasion\"}],\"tags\":[],\"updatedAt\":\"2026-01-07T08:07:17+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6720638\",\"link\":\"https://doi.org/10.1038/s42003-025-09285-0\",\"journal\":{\"identity\":\"communications-biology\",\"isVorOnly\":false,\"title\":\"Communications Biology\"},\"publishedOn\":\"2025-12-03 05:00:00\",\"publishedOnDateReadable\":\"December 3rd, 2025\"},\"versionCreatedAt\":\"2025-06-05 21:51:52\",\"video\":\"\",\"vorDoi\":\"10.1038/s42003-025-09285-0\",\"vorDoiUrl\":\"https://doi.org/10.1038/s42003-025-09285-0\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6720638\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6720638\",\"identity\":\"rs-6720638\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}