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The T-cell receptor (TCR) recognizes an antigenic peptide presented by MHC molecule (pMHC). Molecular modeling of ternary TCR-pMHC complexes (TC) makes it possible to distinguish antigenic epitopes by computing dG/SASA across the dissociation interface. The computational study used data for the specificity of a set of neoantigen-reactive T-lymphocytes obtained using TetTCR-seq approach.[1] Methods. All energy estimates were made using REF2015 score function [2]. Models of T-cell receptors were obtained using TCRmodel, and models for epitopes buried into HLA-A*02 were built by minimizing Levenstein's distance across PDB using RosettaCM framework. We performed docking in PatchDock and 5 best scoring poses for each TC were consequently refined and mutated using FastRelax and FastDesign. We computed ddG(2) (when mutating the 6 central amino acids to Ala) across each 5 models for a TC and used the largest for analysis. 1. dG = (ETCR + EpMHC - ETCR-pMHC)/dSASA, [REU/nm2] 2. ddG = dG6*A - dGWT 3. d = ddGB - ddGNB • H0: There is no difference, on average, between the change in TCR-pMHC dissociation energy upon mutation of central positions of an epitope to alanines for models of TC complexed with native and random epitopes. (H0: d = 0) • H1: Models of native TCs change their dissociation energy more strongly when their binding epitope is mutated to alanine in comparison to TC with random non-binding peptides. (H1: d> 0) Results. When the binding epitope was replaced by a random one, the relative difference in changes in dissociation energies upon mutation of central positions into alanines was μd=7.209 × 10-2 REU/nm2, 95% CI [3.938 × 10-2, 1.047 × 10-1], σd=2.03 × 10-1, Cohen's d=0.4. The value of the paired one-sided t-test is t(200)=4.35 and p =1.1 × 10-5, hence the hypothesis can be rejected. Conclusion. We show here that the modeling approach is able to distinguish between models of T-cell receptors in complex with binder and non-binder antigenic epitopes. The further research will examine effect of increased conformational sampling. The T-cell receptor (TCR) recognizes an antigenic peptide presented by MHC molecule (pMHC). Molecular modeling of ternary TCR-pMHC complexes (TC) makes it possible to distinguish antigenic epitopes by computing dG/SASA across the dissociation interface. The computational study used data for the specificity of a set of neoantigen-reactive T-lymphocytes obtained using TetTCR-seq approach.[1] Methods. All energy estimates were made using REF2015 score function [2]. Models of T-cell receptors were obtained using TCRmodel, and models for epitopes buried into HLA-A*02 were built by minimizing Levenstein's distance across PDB using RosettaCM framework. We performed docking in PatchDock and 5 best scoring poses for each TC were consequently refined and mutated using FastRelax and FastDesign. We computed ddG(2) (when mutating the 6 central amino acids to Ala) across each 5 models for a TC and used the largest for analysis. 1. dG = (ETCR + EpMHC - ETCR-pMHC)/dSASA, [REU/nm2] 2. ddG = dG6*A - dGWT 3. d = ddGB - ddGNB H0: There is no difference, on average, between the change in TCR-pMHC dissociation energy upon mutation of central positions of an epitope to alanines for models of TC complexed with native and random epitopes. (H0: d = 0) H1: Models of native TCs change their dissociation energy more strongly when their binding epitope is mutated to alanine in comparison to TC with random non-binding peptides. (H1: d> 0) Results. When the binding epitope was replaced by a random one, the relative difference in changes in dissociation energies upon mutation of central positions into alanines was μd=7.209 × 10-2 REU/nm2, 95% CI [3.938 × 10-2, 1.047 × 10-1], σd=2.03 × 10-1, Cohen's d=0.4. The value of the paired one-sided t-test is t(200)=4.35 and p =1.1 × 10-5, hence the hypothesis can be rejected. Conclusion. We show here that the modeling approach is able to distinguish between models of T-cell receptors in complex with binder and non-binder antigenic epitopes. The further research will examine effect of increased conformational sampling.