Research Initiation Award: Exploring Class A G-Protein Coupled Receptors (GPCRs)-Ligand Interaction through Machine Learning Approaches

研究启动奖：通过机器学习方法探索 A 类 G 蛋白偶联受体 (GPCR)-配体相互作用

• 批准号: 2300475
• 负责人: Konda Reddy Karnati
• 金额: $ 30万
• 依托单位: Bowie State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2300475&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Exploring; Class

HBCU-UP’s Research Initiation Awards provide support for STEM faculty to pursue research activities to further their research capabilities and effectiveness and help enhance research and teaching at HBCUs. This award to Bowie State University has the potential to identify new drugs using machine learning (ML) methods and provide interdisciplinary training to students. The project focuses on identifying bonding ligands for Class A G protein-coupled receptors (GPCRs), which are the targets for 40-50% of all pharmaceuticals. The project aims to make significant contributions to drug discovery and provide training in emerging fields for HBCU undergraduate students. This project seeks to develop new molecular models and a machine learning approach pipeline for rapidly and accurately building 3D structural models of individual inhibitor/GPCR complexes without experimental structures. ML tools will be used to extract binding features from all complexes and deep learning models will be generated using GPCR protein-ligand complexes to identify novel molecules that target Class A GPCRs. The project has the potential to develop valuable tools for optimizing the potency and selectivity of new drugs at lower costs and higher efficiency. The project will build new opportunities for students in interdisciplinary science using ML techniques and contribute to developing a more diverse workforce.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

HBCU-UP 的研究启动奖为 STEM 教师开展研究活动提供支持，以提高他们的研究能力和有效性，并帮助加强 HBCU 的研究和教学。该奖项授予鲍伊州立大学有潜力利用机器学习 (ML) 识别新药。该项目的重点是识别 A 类 G 蛋白偶联受体 (GPCR) 的结合配体，这是 40-50% 的药物的目标。为药物发现做出重大贡献，并为 HBCU 本科生提供新兴培训。该项目旨在开发新的分子模型和机器学习方法管道，以便在没有实验结构的情况下快速准确地构建单个抑制剂/GPCR 复合物的 3D 结构模型。将用于从所有复合物中提取结合特征，并使用 GPCR 蛋白-配体复合物生成深度学习模型，以识别针对 A 类 GPCR 的新型分子。该项目有潜力开发有价值的工具来优化新的效力和选择性。该项目将为使用机器学习技术的跨学科科学领域的学生创造新的机会，并有助于培养更加多元化的劳动力队伍。该奖项是 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持。以及更广泛的影响审查标准。