Computational Design, Bioinformatics & Screening

该核心的目标是提供计算，生物信息学和高通量筛选 支持这三个项目。计算支持将包括持续的计算机辅助设计 新的和/或改进的SARS-CoV抑制剂SCLpro的合成及其QSAR分析 抑制剂结构和活性，为合成设计提供指导（项目3）。PLpro三维结构理论模型的生物信息学开发将用作PLpro结构-功能研究（项目1），酶促机制研究（项目2）和潜在先导化合物的大型化学库的计算机筛选（项目）的初始基础。高通量实验筛选将用于项目3的PLpro抑制剂的初步先导发现;高通量测定将用于项目2的酶机制分析。蛋白质底物和蛋白质-抑制剂相互作用的生物信息学分析和建模将用于建议用于酶活性和机制的假设检验的特定突变（项目1和2），并预测最不受突变“逃避”影响的抑制剂设计。因此，该核心将为所有三个项目提供集中的计算和高通量检测筛选。

The objective of this Core is to provide computational, bioinformatics and high throughput screening support for all three Projects. Computational support will include continued computer-aided design of new and/or improved inhibitors against SARS-CoV SCLpro and QSAR analysis of SCLpro inhibitor structures and activities to provide guidance in synthetic design (Project 3). Bioinformatics development of theoretical models for the 3-D structure of PLpro will be used as an initial foundation for PLpro structure-function studies (Project 1), for enzymatic mechanistic studies (Project 2) and for in silico screening of large chemical libraries for potential lead compounds (Projects). High throughput experimental screening will be used for initial lead discovery of PLpro inhibitors for Project 3; high throughput assays will be used for analysis of enzymatic mechanisms in Project 2. Bioinformatic analysis and modeling of protein substrate and protein-inhibitor interactions will be used to suggest particular mutations for hypothesis testing for enzymatic activity and mechanisms (Projects 1 and 2), and to predict inhibitor designs that will be least subject to mutational 'evasion'. This Core will thus provide centralized computational and high throughput assay screening for all three Projects.