Bioinformatics tools for T-cell receptor based drugs

目的和目的我们开发了一系列用于分析抗体序列和结构的软件和数据库。特别是，abysis在网上被广泛使用，并成功地出售给公司供内部使用。随着新的治疗方法和相关的T细胞受体(TCR)正在被开发，抗体已经显示出巨大的成功。我们希望改变我们开发的用于TCR的抗体的方法，并开发新的方法和进行新的分析。将开发软件对TCR进行标准编号，以便分析序列和结构特征。将开发工具来存储和分析公共序列和结构数据，以期产生可用于基于TCR的药物开发的软件。将分析晶体结构以查看可用于改进TCR建模的结构域堆积。然后，将采用存储序列数据、分析残基分布和添加注释、在每一步对序列进行分类以减少不必要分析的大数据方法来分析庞大的NextGen TCR序列数据集。分类将包括筛选出非常不寻常的序列，以及那些可能存在免疫原性或发展性问题的序列。将开发一个基本的网络界面，以便能够探索数据和分析新的序列。

Aims and Objectives We have developed a range of software and databases for analysis of antibody sequence and structure. In particular, abYsis is widely used online and is successfully sold to companies for in-house use. Antibodies have shown a huge degree of success as novel therapeutics and the related T-Cell Receptors (TCRs) are now being exploited. We wish to repurpose methods we have developed for antibodies for use with TCRs as well as developing new approaches and performing new analyses. Software will be developed to apply standard numbering to TCRs, such that sequence and structure features can be analyzed. Tools will be developed to store and analyze public sequence and structure data with a view to producing software that can be used in the development of TCR-based drugs.Crystal structures will be analyzed to look at domain packing which can be exploited to improve TCR modelling. Huge nextgen TCR sequence datasets will then be analyzed taking a 'big data' approach storing sequence data, analyzing residue distributions and adding annotations, triaging sequences at each step to reduce unnecessary analysis. Triage will include screening out very unusual sequences and those with likely immunogenicity or developability issues. A basic web interface will be developed to allow the data to be explored and new sequences to be analyzed.