以PD-1抗体为代表的免疫检查点抑制剂作为新兴的癌症治疗方法在临床上取得了巨大的成功，成为癌症研究的热点。BTLA和HVEM作为免疫检查点蛋白的成员，是潜在的抗癌药物靶点，但其复杂的相互作用界面与多样的结合模式限制了抑制剂的开发。本项目拟针对BTLA，通过特异性靶向其与HVEM的结合界面，利用噬菌体展示技术结合理性设计，筛选并优化阻断两者相互作用的新型多肽抑制剂。利用基于结合界面多肽片段的突变文库和随机文库，通过竞争性的筛选方法筛选出特异性的候选多肽；在此基础上，使用计算机模拟分析候选多肽与BTLA的作用机理与构效关系，并结合理性设计，利用化学修饰进一步改造候选多肽，从而提高其结合强度和抑制效果；最后，测定候选多肽与BTLA结合的动力学参数，验证其作用通路及对T细胞的激活效果，从而鉴定出高效、高特异性的多肽抑制剂，为开发临床可用的阻断BTLA/HVEM相互作用的新型多肽抑制剂药物奠定基础。

Immune checkpoint inhibitors like PD-1 antibodies have achieved great success as a novel anti-cancer therapy in clinic and the study has become a research hotspot. BTLA and HVEM as other members of immune checkpoints are potential targets for anti-cancer drugs. However, the complicated interfaces with multiple proteins limit the inhibitor development against them. In this proposal, we are going to target the specific interface of BTLA and HVEM and develop new peptide inhibitors using phage display together with rational design. Here we choose the mutants library based on the peptide fragments on the interface in HVEM and a totally random library to screen highly specific inhibitors binding to the interface by using competitive screen method. The candidate peptides will be analyzed for the structure-activity relationship and then optimized by chemical modifications to improve their specificity and affinity. The binding kinetics of optimized the candidates will be measured and their effects to corresponding pathways will be determined. At last, the re-activation of T cells by the peptides will be evaluated to confirm the efficacy. In sum, we aim to develop highly effective and specific peptide inhibitors to block the interaction of BTLA and HVEM, hoping that they could be good leading peptides for anti-cancer drugs used in clinic.