A New Paradigm for Biomolecular Simulations

描述(由申请人提供)：本申请涉及广泛的挑战领域(06)使能技术和具体的挑战主题06-GM-103：分子结构、识别和配体相互作用预测方法的发展。生物医学计算已经成为了解生物特性和功能的有力工具。计算生物学的目标是以化学的精度对生化过程进行定量预测，即绝对量在1kcal/mol以内，相对量在1kcal/mol以内。鉴于细胞环境中生物分子系统的复杂性和规模，这是一项艰巨的任务，我们距离实现这一重要目标还有很长的路要走。分子计算的核心是描述体系中分子间相互作用的势能函数，而通常是势能面的准确性决定了模拟结果的可靠性。虽然目前的分子力力场在过去的40年里由于在参数化方面的巨大努力而在生物分子模拟中取得了非常成功的成就，但自20世纪60年代末以来，泛函形式几乎没有改变。在这个项目中，我们建议开发一种基于电子结构的量子力学力场，称为显式极化(X-Pol)势，用于获得含有蛋白质的生物分子系统的势能面。这代表着一个重大的范式变化，超越了当前的经典模型，进入了生物医学计算的量子力学领域。X-Pol势基于一系列近似，这些近似可以用半经验或从头算分子轨道理论或密度泛函理论来发展。证明了这种显式量子力学力场的可行性。这项研究为提高生物医学模拟中的计算精度提供了一个巨大的机会，这项工作中开发的计算工具将对蛋白质工程和抑制剂设计具有普遍的重要性。 公共健康相关性：生物医学计算已成为了解生物特性和功能的有力工具。这项建议中描述的研究旨在开发一种新的计算方法，它代表了我们描述分子间相互作用的方式的范式变化，并有望显着提高计算结果的准确性。这反过来可以帮助设计抑制剂，并为生物医学和工业应用设计专门的蛋白质。

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (06) Enabling Technologies and specific Challenge Topic, 06-GM-103: Development of predictive methods for molecular structure, recognition, and ligand interaction. Biomedical computation has become a powerful tool for understanding biological properties and function. The goal of computational biology is to make quantitative predictions of biochemical processes with chemical accuracy, i.e., to within one kcal/mol for absolute quantities and 1 kcal/mol for relative quantities. This is a daunting task in view of the complexity and size of biomolecular systems in a cellular environment, and we are still far from achieving this important goal. At the heart of molecular calculation is the potential energy function that describes intermolecular interactions in the system, and often it is the accuracy of the potential energy surface that determines the reliability of the simulation results. Although the current molecular mechanics force fields have been very successful in biomolecular modeling thanks to tremendous efforts in parameterization in the past forty years, the functional forms have hardly changed since the late 1960s. In this project, we propose to develop an electronic structure-based quantum mechanical force field, called the explicit polarization (X-Pol) potential, for obtaining the potential energy surfaces of biomolecular systems containing proteins. This represents a major paradigm change, going beyond the current classical models to the quantum mechanical realm of biomedical computing. The X-Pol potential is based on a hierarchy of approximations that can be developed using semiempirical or ab initio molecular orbital theory or density functional theory. The feasibility of such an explicit quantum mechanical force field has been demonstrated. The proposed research offers a great opportunity for a quantum leap in improving computational accuracy in biomedical simulation, and the computational tools developed in this work will be of general importance to protein engineering and inhibitor design. PUBLIC HEALT RELEVANCE: Biomedical computation has become a powerful tool for understanding biological properties and function. The research described in this proposal aims at the development of a novel computational approach that represents a paradigm change in the way that we describe intermolecular interactions and it is expected to significantly increase the accuracy of computational results. This in turn can help design inhibitors and engineer specialized proteins for biomedical and industrial applications.