Rational Optimization Of Tumor Epitopes Using In Silico Analysis Assisted Substitution Of TCR Contact Residues

Induction of antigen-specific cytotoxic T lymphocytes (CTL) by therapeutic peptide vaccination is a promising approach for cancer immunotherapy. The specific cellular immune response starts from recognition by TCR of an immunogenic epitope presented in the context of the class I major histocompatibility complex (MHC-I) molecules. Thus, modulation of CTL response by manipulating T cell epitopes is a particularly attractive approach for cancer immunotherapy, because peptides from cancer cells are usually poorly immunogenic and often induce immune-tolerance. Vaccination with altered peptide ligands (APLs), which can be generated by appropriate amino acid substitutions at certain T cell epitopes, has become an attractive strategy to enhance specific T cell responses to tumors. This strategy can be achieved by two general approaches: 1) by increasing the affinity between the epitope and the MHC through substitution in the MHC anchor residues; or 2) by enhancing the interactions between the TCR and peptide-MHC (pMHC) complex through alteration at the TCR contact residues.Although APLs with altered MHC contact residues can efficiently activate tumor-specific T cells in vitro, vaccination with this kind of APLs has generally failed to elicit an effective anti-tumor CTL response that can lead to clinical tumor regression. APLs with increased pMHC complex affinity for the TCR molecule, which are designed by modifications at the TCR contact sites rather than the MHC anchor residues, have unexpected potency to induce stronger T cell responses and may even covert cross-reactive T cells from a tolerance state. According to the structure of the TCR/pMHC complex established by X-ray crystallography, recognition of an epitope by T cells is controlled by a few exposed TCR contact residues within the peptide. Several recent investigations have found that subtle changes at the TCR contact positions can dramatically alter the downstream signaling events that can lead to effects that can be in a range from induction of T cell anergy to enhancement of T cell functions, indicating that the analogue with substitution at TCR contact sites may provide considerable benefit in super-agonists or antagonist vaccine development. To date, there is no convenient method to guide the modification of TCR contact residues of T cell epitopes to change the affinity between pMHC and the TCR. In the past, only a few APLs were identified by methods such as eluting naturally occurring mutant peptides from tumor cells, high-throughput screening of synthetic combinatorial peptides libraries, and random phage displayed peptides libraries; however, these methods are costly and time consuming. It is thus necessary to develop a novel rational approach to guide such substitution.There have been many successful studies on evaluating the design of APLs for increased MHC binding affinity through the calculation of pMHC interaction energies using in silico techniques. We reasoned that calculation of the interaction energy between TCR and pMHC using computer-aided methods could be applied in the design of APLs for enhanced TCR engagement. However, the prediction of the interaction energy between TCR and pMHC is much more difficult than calculating pMHC interaction energies. Only a few theoretical approaches such as the free energy perturbation (FEP) method, regression method, and the statistical mechanics method have been developed to predict protein-protein binding affinity. In a FEP method-based study performed by Michielin and Karplus, the computed free energy difference in the binding of a particular TCR (A6) with a HLA-A2 restricted wild-type peptide (Tax) and a mutant peptide (Tax P6A) was shown in good agreement with the experimental value. Although this study has shed new light on the application of a molecular simulation approach to guide peptide modifications for alteration of TCR-ligand binding, the large computational burden made the application of the FEP method only applicable to established facility. In a recent study, Lai et al. applied a statistical mechanics method termed PMFScore, which is based on the potential of mean force (PMF), to calculate protein-protein interaction energies precisely and efficiently and here we aimed to test the feasibility of the application of PMF-based in silico approach in order to develop a more applicable approach for peptide modifications.The HLA-A*0201 restricted T cell epitope NY-ESO-1157–165 has been indicated as a promising candidate for T cell-based tumor vaccination strategies, however, several studies have revealed its defects in stability and bioavailability and its frequent failure to elicit robust anti-tumor CTL response. It has been demonstrated that a cysteine-to-valine substitution at position 9 in the NY-ESO-1 157–165 epitope can increase its immunogenicity due to markedly enhanced peptide binding to the MHC peptide binding grove. Although this MHC anchor residue substitution was also shown to possess slightly improved interactions with TCR than analogue peptides, the study did not specifically focus on the TCR contact residues.In this study, we generated an agonist analogue NY-ESO-1157–1655F9V with a tryptophane to phenylalanine substitution at TCR contact residue of NY-ESO-1157–165 based on a cysteine-to-valine substitution at position 9. This designed APL can elicit a stronger CTL response with cross-reactivity with the WT peptide. In conclusion, our findings demonstrated that the in silico method based on PMFScore could predict and guide T cell epitope modification of the TCR contact residues based on the structural information of TCR/pMHC triple complex. Our results provide important insights into the enhanced immunogenicity of epitopes through substitution at the TCR contact sites and revealed a novel molecular simulation approach for rational design of agonist peptides. It will be of interest to further examine the immunological effects of the 5F9V agonist in order to make this peptide to be applicable for antitumor vaccine design.