Rapid Solvation Thermodynamics Calculations for Proteins

蛋白质的快速溶剂化热力学计算

• 批准号: 1709310
• 负责人: B. Montgomery Pettitt
• 金额: $ 45.21万
• 依托单位: University of Texas Medical Branch at Galveston
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1709310&HistoricalAwards=false
• 关键词: Rapid; Solvation; Thermodynamics; Calculations; Proteins

Montgomery Pettitt of The University of Texas Medical Branch (UTMB) is supported by an award from the Chemistry of Life Processes Program in the Chemistry Division to create a new set of computational tools for simulating and understanding the fundamental properties of proteins in solution, with application to protein design and the development of new materials and biotechnologies. Some of the most challenging systems in biotechnology applications are those involving liquids, particularly mixtures of biopolymers in water. Professor Pettitt is developing a new computational framework for the molecular design of proteins based on current theories of how liquids behave. Solutions of proteins, which serve as structural components and perform catalytic chemistry, are central to much of biotechnology. This study will enable the rapid screening of proposed protein modifications computationally with greatly improved accuracy compared to existing methods. Codes, scripts, and documentation developed in this project are being made freely-available to the simulation community, and can be interfaced to widely-used molecular dynamics simulation codes. The project is recruiting several students each year for a 10-week internship in computational biology in Professor Pettitt's laboratory, through outreach efforts at local HBCU and Hispanic-serving institutions and the ACS SEED and R. A. Welch Summer Scholar high school programs. There is close cooperation with the UTMB Sealy Center for Structural Biology, which provides a venue for student research presentations at research symposia and conferences, and opportunities for research collaborations using the new methodology and to provide feedback on future enhancements.The mechanisms governing recognition between proteins, ligands and the transition of proteins from their unfolded state to their native state remain as fundamental chemical questions. Those equilibria are governed by free energy differences in solution. The calculation of solvation free energies by explicit computer simulations can be accurate, but is computationally expensive and essentially prohibitive for entire proteins, even on large supercomputing systems. This project is developing precomputed solvent distributions ("proximal (radial) distribution functions", or pDFs) extracted from benchmark all-atom molecular dynamics simulations to produce a near neighbor approximation to the solvation density profile about arbitrary protein solutes. The initial libraries of pDFs are being developed for the widely-used CHARMM force field. The principal goals of the research are to (1) generate pDF libraries for all naturally-occurring amino acids and additional important functional groups, (2) develop efficient methods based on the pDFs to compute total and relative solvation free energies, and (3) extend the method to multicomponent solutions. The third goal includes experimental collaboration to test the methodology against solution thermodynamic measurements. Given the precomputed nature of the pDFs, the evaluation of thermodynamic averages as integrals over the precomputed distribution is computationally very efficient. These fast and accurate methods can be generally applied to protein systems where the understanding of the recognition, self-recognition, or folding process is essential. This results of this project have far-reaching applications to the fields of computer-aided molecular design, structural analysis, and biotechnology. The code and scripts developed for the research are being disseminated as open source and can be readily extended to interface to widely-used molecular dynamics simulation codes and force fields.

德克萨斯大学医学分支（UTMB）的蒙哥马利佩蒂特（Montgomery Pettitt）获得了化学部生命过程计划化学的奖项，以创建一套新的计算工具，用于模拟和理解溶液中蛋白质的基本性质，并应用于蛋白质设计和新材料和生物技术的开发。 生物技术应用中一些最具挑战性的系统涉及液体，特别是生物聚合物在水中的混合物。 Pettitt教授正在开发一种新的计算框架，用于基于当前液体行为理论的蛋白质分子设计。 蛋白质溶液作为结构成分并执行催化化学，是许多生物技术的核心。这项研究将使快速筛选建议的蛋白质修饰计算大大提高了准确性相比，现有的方法。 在这个项目中开发的代码，脚本和文档正在免费提供给模拟社区，并可以连接到广泛使用的分子动力学模拟代码。 该项目每年招募几名学生在佩蒂特教授的实验室进行为期10周的计算生物学实习，通过在当地HBCU和西班牙裔服务机构以及ACS SEED和R的推广工作。A.韦尔奇夏季奖学金高中项目。 与UTMB西利结构生物学中心有着密切的合作，该中心为学生在研究研讨会和会议上进行研究报告提供了场所，并为使用新方法的研究合作提供了机会，并为未来的改进提供了反馈。蛋白质，配体之间的识别机制以及蛋白质从未折叠状态到天然状态的转变仍然是基本的化学问题。这些平衡由溶液中的自由能差决定。通过显式计算机模拟计算溶剂化自由能可以是准确的，但即使在大型超级计算系统上，计算成本也很高，并且对于整个蛋白质来说基本上是禁止的。 该项目正在开发从基准全原子分子动力学模拟中提取的预先计算的溶剂分布（“近端（径向）分布函数”，或pDF），以产生任意蛋白质溶质的溶剂化密度分布的近邻近似。目前正在为广泛使用的CHARMM力场开发pDF的初始库。 该研究的主要目标是（1）生成所有天然氨基酸和其他重要官能团的pDF库，（2）开发基于pDF的有效方法来计算总溶剂化自由能和相对溶剂化自由能，以及（3）将该方法扩展到多组分溶液。 第三个目标包括实验合作，以测试的方法对解决方案的热力学测量。 考虑到pDF的预先计算的性质，将热力学平均值评估为预先计算的分布上的积分在计算上是非常有效的。这些快速而准确的方法通常可以应用于蛋白质系统，其中对识别，自我识别或折叠过程的理解是必不可少的。 本计画之研究成果，在电脑辅助分子设计、结构分析、生物技术等领域，都有深远的应用。 为研究开发的代码和脚本正在作为开放源代码传播，并且可以随时扩展到广泛使用的分子动力学模拟代码和力场的接口。

项目成果

Correction to “Free Energy Calculations Based on Coupling Proximal Distribution Functions and Thermodynamic Cycles”

对“基于近端分布函数和热力学循环耦合的自由能计算”的修正

• DOI: 10.1021/acs.jctc.9b00927
• 发表时间: 2019
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Ou, Shu-Ching;Pettitt, B. Montgomery
• 通讯作者: Pettitt, B. Montgomery

Free Energy Calculations Based on Coupling Proximal Distribution Functions and Thermodynamic Cycles

基于近端分布函数与热力循环耦合的自由能计算

• DOI: 10.1021/acs.jctc.8b01157
• 发表时间: 2019
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Ou, Shu-Ching;Pettitt, B. Montgomery
• 通讯作者: Pettitt, B. Montgomery