Extending the power of structure-guided fragment-based drug discovery (FBDD)

扩展基于结构引导的片段药物发现 (FBDD) 的能力

• 批准号: 2600437
• 金额: --
• 依托单位: University of Cambridge
• 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-2600437
• 关键词: Extending; power; structure; guided; fragment

The aims of this project are to extend the power of structure-guided fragment-based drug discovery (FBDD) to develop rapid, robust, and effective methods to create antibiotics against Mycobacterium abscessus. I will therefore: 1. Optimise chemical scaffold-target selection, by (i) phenotypic screening of hit-finding fragment libraries created using diversity oriented synthesis, and then (ii) identifying targets through photochemical cross-linking, whole cell thermal shift assay, whole genome sequencing of escape mutants, and screening against existing arrayed inducible CRISPR-dCas9 hypomorphs; 2. Define the chemical rules for bacterial permeation, retention, and metabolism, using machine-learning cheminformatic analysis of LC-MS-based compound screening; and 3. Exploit these new datasets for optimising drug target and chemical selection, binding site exploitation, and chemical elaboration to (i) pursue a fragment-based drug discovery campaign (guided by X-ray crystallography) and (ii) implement ultra-large in silico screening of make-on demand compounds to deliver instant antimicrobial drug-like molecules.

该项目的目的是扩展基于结构指导片段的药物发现（FBDD）的能力，以开发快速，稳健和有效的方法来创建针对结核分枝杆菌的抗生素。因此，我将：1。优化化学支架-靶标选择，通过（i）使用多样性定向合成创建的命中发现片段文库的表型筛选，然后（ii）通过光化学交联、全细胞热位移测定、逃逸突变体的全基因组测序和针对现有阵列诱导型CRISPR-dCas 9亚型的筛选来鉴定靶标; 2.使用基于LC-MS的化合物筛选的机器学习化学信息学分析来定义细菌渗透、保留和代谢的化学规则;以及3.利用这些新数据集来优化药物靶点和化学选择、结合位点利用和化学精制，以（i）开展基于片段的药物发现活动（由X射线晶体学指导）和（ii）实施超大规模的计算机模拟筛选按需制造的化合物，以提供即时的抗微生物药物样分子。