Level-Set Variational Implicit-Solvent Approach to Biomolecular Interactions

生物分子相互作用的水平集变分隐式溶剂法

• 批准号: 8045568
• 负责人: Bo Li
• 金额: $ 29.9万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8045568
• 关键词: Affect; Arts; Biological Process; Capillarity; Collaborations; Complex; Computational Molecular Biology; Computer Assisted; Couples; Docking; Drug Design; Drug Industry; Electrostatics; Free Energy; Goals; Hydrophobic Interactions; Industry; Lead; Life; Mathematics; Methods; Modeling; Performance; Process; Property; Research; Research Personnel; Solutions; Solvents; Speed; Structure; Students; System; Technology; Theoretical model; Training; Work; aqueous; computer program; cost; drug discovery; evaporation; experience; improved; molecular mechanics; molecular recognition; novel; programs; protein folding; public health relevance; research study; small molecule; solute; success; theories

DESCRIPTION (provided by applicant): This project develops a conceptually novel theory and robust computational technologies to investigate biomolecular interactions in aqueous solutions. Such interactions influence significantly protein folding, molecular recognition, and many other biological processes. One of the crucial properties of such interactions is the capillarity evaporation or dewetting that can affect critically the solvation free energy and biomolecular structures. The goal of this project is to better understand such hydrophobic interactions in biomolecular systems and to create a state-of-the-art computational program for molecular recognition. The new variational model couples all the dispersive, non-polar, and polar interactions to local geometry in a free-energy functional. This theoretical model and the level-set numerical method can well describe the hydrophobic interaction and complex free-energy landscapes of biomolecular systems that are generally not correctly captured in established implicit-solvent models. Sophisticated numerical methods for electrostatics are developed to couple with the level-set method. Further model refinement to include solute molecular mechanics and stochastic effects can lead to a new computer program for molecular recognition that will significantly improve the existing ones whose unsatisfactory performances have been widely recognized. The success of the project will reduce the high cost for experiments and speed up the process of drug discovery. The natural collaborations among mathematics, biosciences, and pharmaceutical industry in the proposed research make it convenient to transform the mathematical research into the life-saving reality. This highly interdisciplinary project brings exciting opportunities for students and postdoctoral researchers to receive training in mathematical bioscientific research and to gain experience of working in biomedical industry. The project also provides material for an urgently needed course on mathematical and computational molecular biology. PUBLIC HEALTH RELEVANCE: One of the central objectives of computer-aided drug design is to dock efficiently and accurately small molecules to a target, large biomolecule in solution. This project provides a sophisticated way of such docking, and hence a better drug design program.

描述（由申请人提供）：该项目开发了一种概念新颖的理论和强大的计算技术，以研究水溶液中的生物分子相互作用。这种相互作用显著影响蛋白质折叠、分子识别和许多其他生物过程。这种相互作用的关键性质之一是毛细蒸发或去湿，可以严重影响溶剂化自由能和生物分子结构。该项目的目标是更好地理解生物分子系统中的疏水相互作用，并创建一个最先进的分子识别计算程序。 新的变分模型耦合所有的色散，非极性和极性的相互作用，局部几何的自由能功能。该理论模型和水平集数值方法可以很好地描述生物分子系统的疏水相互作用和复杂的自由能景观，这些生物分子系统通常不能正确地捕获在已建立的隐式溶剂模型中。发展了用于静电学的复杂数值方法以与水平集方法耦合。进一步的模型改进，包括溶质分子力学和随机效应，可以导致一个新的计算机程序的分子识别，将显着改善现有的，其不令人满意的性能已被广泛认可。 该项目的成功将降低高昂的实验成本，加快药物发现的进程。在拟议的研究中，数学，生物科学和制药工业之间的自然合作使数学研究很容易转化为拯救生命的现实。这个高度跨学科的项目为学生和博士后研究人员带来了令人兴奋的机会，可以接受数学生物科学研究的培训，并获得在生物医学行业工作的经验。该项目还为急需的数学和计算分子生物学课程提供了材料。 公共卫生相关性：计算机辅助药物设计的中心目标之一是将小分子有效且准确地对接到溶液中的目标大生物分子。该项目提供了一种复杂的对接方式，从而提供了一个更好的药物设计方案。