Optimisation and design of T cell receptors through artificial evolution

新型T细胞受体（TCRs）的设计已经成为开发新型免疫疗法的一种新兴策略，特别是对于癌症患者的治疗。通过精心选择和修饰某些氨基酸，结构导向的合理设计已被证明可以产生具有改变抗原结合亲和力和特异性的TCR结构。该项目的目的是通过开发一种优化算法来人工进化tcr种群，从而推广这种合理的设计过程。TCR的特性将通过随机的氨基酸突变而改变，最有希望的候选者将在计算模拟自然选择的过程中被保留以进行进一步的进化。结果应该是一群新的tcr，它们识别特定抗原的能力得到了增强。

The design of novel T cell receptors (TCRs) has become an emergent strategy for developing new forms of immunotherapy, particularly for the treatment of patients with cancer. Structure-guided rational design through the careful selection and modification of certain amino acids has previously been shown to produce TCR structures with altered antigen binding affinities and specificities. The aim of this project is to generalise this rational design process by developing an optimisation algorithm to artificially evolve populations of TCRs. TCR properties will be altered through random amino acid mutation, and the most promising candidates will be retained for further evolution in a process that computationally mimics natural selection. The output should be a new population of TCRs that have been enhanced in their ability to recognise a given antigen.