Bioinformatics tools for T-cell receptor based drugs

基于 T 细胞受体的药物的生物信息学工具

• 批准号: 2563845
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2563845
• 关键词: Bioinformatics; tools; cell; receptor; based

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.

目的和目标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 在网上得到广泛使用，并成功出售给公司供内部使用。随着新型疗法和相关 T 细胞受体 (TCR) 的开发，抗体已经取得了巨大的成功。我们希望重新利用我们为 TCR 开发的抗体方法，并开发新方法并进行新分析。将开发软件以将标准编号应用于 TCR，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，以期生产可用于开发基于 TCR 的药物的软件。将分析晶体结构以查看可用于改进 TCR 建模的域包装。然后，将采用“大数据”方法来分析巨大的下一代 TCR 序列数据集，存储序列数据，分析残基分布并添加注释，在每个步骤中对序列进行分类，以减少不必要的分析。分类将包括筛选出非常不寻常的序列以及可能具有免疫原性或可开发性问题的序列。将开发一个基本的网络界面，以允许探索数据和分析新序列。