Optimisation and design of T cell receptors through artificial evolution

新型T细胞受体（TCR）的设计已成为开发新形式免疫疗法的紧急策略，特别是用于治疗癌症患者。通过仔细选择和修饰某些氨基酸的结构引导的合理设计先前已显示产生具有改变的抗原结合亲和力和特异性的TCR结构。本项目的目的是通过开发一种优化算法来人工进化TCR群体，从而推广这种合理的设计过程。TCR特性将通过随机氨基酸突变来改变，最有希望的候选者将被保留，以便在计算模拟自然选择的过程中进一步进化。输出应该是新的TCR群体，其识别给定抗原的能力已经增强。

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.