Level-Set Variational Implicit-Solvent Approach to Biomolecular Interactions

描述(由申请人提供)：该项目开发了一种概念新颖的理论和稳健的计算技术来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。这种相互作用的一个重要性质是毛细作用、蒸发或去湿，这会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了解生物分子系统中的这种疏水相互作用，并创建一种最先进的分子识别计算程序。 新的变分模型将所有的色散、非极和极相互作用耦合到自由能泛函中的局域几何。这种理论模型和Level-Set数值方法能够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，而这些通常在已有的隐式溶剂模型中是无法正确捕捉的。发展了复杂的静电学数值方法，与Level-Set方法相结合。进一步的模型改进，包括溶质、分子力学和随机效应，可以产生一个新的分子识别计算机程序，它将显着改善现有的分子识别程序，这些程序的性能并不令人满意。 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。数学、生物科学和制药行业在所提出的研究中的自然合作，为将数学研究转化为救生现实提供了便利。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，他们可以接受数学生物科学研究方面的培训，并获得在生物医药行业工作的经验。该项目还为一门迫切需要的数学和计算分子生物学课程提供了材料。 与公共健康相关：计算机辅助药物设计的中心目标之一是有效和准确地将小分子对接到溶液中的目标生物大分子上。该项目提供了一种复杂的对接方式，因此是一种更好的药物设计方案。

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.