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A Multi-pronged Computational Approach to Advance Kinase Drug Discovery

促进激酶药物发现的多管齐下的计算方法

基本信息

批准号：
10348133
负责人：
Jana Shen
金额：
$ 34.5万
依托单位：
UNIVERSITY OF MARYLAND BALTIMORE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10348133
关键词：
Affinity Amber Area Attenuated Autoimmune Binding Chemicals Collaborations Coupling Data Databases Development Disease Drug Design Free Energy Goals Imatinib Inflammatory Kinetics Knowledge Letters Link MAPK11 gene Malignant Neoplasms Methods Modeling Molecular Molecular Conformation Oncogenic Opioid Receptor Outcome Study Pathway interactions Pharmaceutical Preparations Phosphotransferases Pilot Projects Process Proteins Proteome Protocols documentation Protons Reaction Scanning Site Solvents Speed Structure Testing Time Titrations Toxic effect Validation Work base cancer therapy computational platform computerized tools design drug discovery druggable target improved inhibitor insight kinase inhibitor molecular dynamics new therapeutic target novel p38 Mitogen Activated Protein Kinase prospective protein protein interaction quantum rapid growth rational design residence simulation small molecule therapeutic target tool tool development ubiquitin-protein ligase

项目摘要

Project Summary/Abstract In recent years, computing speed has exponentially increased; however, the potential of computational ap- proaches to accelerate drug discovery has not been fully realized. Our long-term goal is to develop and ap- ply computational tools to advance structure-based drug design. The objective of this proposal is to apply new computational protocols based on the cutting-edge molecular simulation and quantum calculation tools to tackle several critical topics in the rational design of reversible and targeted covalent inhibitors (TCI) of kinases. Kinases phosphorylate a third of the proteome and deregulation of kinase functions is a major strategy to modulate cancer, autoimmune and inﬂammatory conditions. In recent years, reversible and covalent kinase inhibitors are gaining FDA approvals at a rapidly growing speed. Supported by our new tool developments, pilot studies, unpublished preliminary data, as well as working hypothe- ses, we will pursue three speciﬁc aims: 1) conduct kinome and proteome wide computational proﬁling studies to identify covalent targetable sites; 2) elucidate the reaction mechanisms and structure-reversibility relationships for chemical warhead design; and 3) elucidate the mechanisms controlling selectivity and kinetics of reversible kinase inhibitors. The outcomes of the studies will guide the current efforts in TCI discovery for kinases and the search for new druggable targets; provide detailed knowledge for attenuating reactivity and reversibility of chemical warheads to minimize toxicity; and offer new strategies to improve selectivity and kinetic parameters of reversible inhibitors. Successful completion of the project will allow us to build a computational platform to advance structure-based drug design and expand the current therapeutic target space.

项目总结/文摘