Algorithms for the simulation of short and long time dynamics of proteins

模拟蛋白质短期和长期动态的算法

• 批准号: 0316551
• 负责人: John Straub
• 金额: $ 40.5万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0316551&HistoricalAwards=false
• 关键词: Algorithms; simulation; short; long; time

John Straub of Boston University is co-supported by a grant from the Theoretical and Computational Chemistry and Molecular Biophysics Programs to continue his efforts at developing computational methods that enable the accurate description of protein dynamics on both long and short time scales. Such techniques must identify and isolate thermodynamically important low lying energy basins and effectively sample those basins and move between them in a way that produces exact thermodynamic averages. A current emphasis is on improving the means for proper accounting of solvation energies that influence protein configurational distributions. Two specific applications are studied. First, with respect to vibrational energy flow, current interest is on exploring the nature of heme cooling as function of protein type and solvent environment. Second, a coarse-grained potential energy function is being improved to enable studies on lysozyme folding dynamics. Methods used for these studies include Monte Carlo simulations, path-integral methods, molecular dynamics and quantum-chemical methodsThe ability to computationally understand biological processes requires methods that can accurately describe processes that occur on vibrational time scales and protein folding which requires longer time scales. Predictive capabilities on the vibrational time scale allows one to predict relaxation kinetics and directly test such predictions by comparing aspects of theoretically deduced vibrational spectra to experimentally determined results. Computational deduction of protein-folding mechanisms and pathways requires accurate and efficient coarse-grained models that are significantly more complex then those that are currently available. The new techniques being developed and advanced by Straub are beginning to be used for simulating chemical and biophysical processes. Further improvements will significantly impact the field of computational biology.

波士顿大学的John Straub得到了理论和计算化学以及分子生物物理学项目的资助，继续努力开发计算方法，以便在长时间和短时间尺度上准确描述蛋白质动力学。 这种技术必须识别和隔离具有重要意义的低洼能源盆地，并有效地对这些盆地进行采样，并以产生精确热力学平均值的方式在它们之间移动。 目前的重点是改善的手段，适当的会计溶剂化能影响蛋白质的构型分布。两个具体的应用程序进行了研究。 首先，相对于振动能量流，目前的兴趣是探索血红素冷却的性质作为蛋白质类型和溶剂环境的函数。其次，一个粗粒度的势能函数正在改进，使溶菌酶折叠动力学的研究。 用于这些研究的方法包括Monte Carlo模拟，路径积分方法，分子动力学和量子化学方法计算理解生物过程的能力需要能够准确描述振动时间尺度和蛋白质折叠过程的方法，这需要更长的时间尺度。 振动时间尺度上的预测能力允许人们预测弛豫动力学，并通过比较理论推导的振动光谱与实验确定的结果来直接测试这种预测。 蛋白质折叠机制和途径的计算推导需要精确和高效的粗粒度模型，这些模型比目前可用的模型要复杂得多。Straub开发和推进的新技术开始用于模拟化学和生物物理过程。进一步的改进将对计算生物学领域产生重大影响。