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.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 我目前的研究和未来的研究计划围绕着推进计算方法，并将其应用于更好地理解计算结构生物学中的两个关键主题;酶促反应中速率加速的来源和从其一级序列预测蛋白质结构。 理论和计算机模拟的进展，特别是通过使用混合量子/经典势能函数，为酶催化的许多来源提供了新的见解（Science，2003，303：186-195）。 信息论、基于知识的能量函数和精化方法的进展为构建蛋白质结构预测的先进工具提供了基础（Science，2001，294：93-96）。 然而，生物医学研究界仍然迫切需要使这些方法更准确，更普遍适用。 改进这些方法将对结构-功能关系以及预防和治疗疾病的新策略的发展具有重要意义。