MODELING ENZYME STRUCTURE AND FUNCTION

酶结构和功能建模

• 批准号: 8171848
• 负责人: TROY WYMORE
• 金额: $ 0.14万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8171848
• 关键词: Acceleration; Biochemical Reaction; Biomedical Research; Catalysis; Communities; Computer Retrieval of Information on Scientific Projects Database; Computer Simulation; Computing Methodologies; Development; Disease; Enzymes; Funding; Future; Grant; Hybrids; Information Theory; Institution; Methods; Modeling; Potential Energy; Prevention strategy; Research; Research Personnel; Resources; Science; Source; Structure-Activity Relationship; United States National Institutes of Health; base; enzyme structure; improved; insight; knowledge base; protein structure prediction; quantum; structural biology; theories; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. My current research and future research plans revolve around advancing computational methods and applying them to better understand two key subjects in computational structural biology; the source of rate accelerations in enzymatic reactions and the prediction of protein structure from its primary sequence. Advances in theory and computer simulations; particularly through the use of hybrid Quantum/Classical potential energy functions, are providing new insights into the many sources of enzyme catalysis (Science, 2003, 303:186-195). Advances in information theory, knowledge-based energy functions and refinement methods are providing the basis to construct advanced tools for protein structure prediction (Science, 2001, 294:93-96). Yet there is still a critical need in the biomedical research community to make these methods more accurate and more generally applicable. Improving these methods will have great relevance to structure-function relationships and the development of new strategies for the prevention and treatment of disease.

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