Algorithmic improvements in large scale polarizable QM/MM simulations

项目摘要 在蛋白质口袋和复杂溶剂等非均质环境中的化学反应性建模 是药物发现工作流程的重要组成部分。然而，由于大型系统，这种建模是具有挑战性的。 环境自由度广泛抽样的规模和必要性。该项目的目标是 开发一套基于可极化量子力学的高效、准确和可扩展的计算工具， 动力学/有效碎片势（QM/EFP）方法，将为学术界和私营企业提供 为用户提供快速和强大的软件，用于化学自由能分布的计算表征 复杂凝聚相体系中的反应。该项目的第二阶段建立在一个成功的成果之上- 第一阶段的全面完成，在这一阶段，研究小组已经开发出了算法和计算机代码， 采用快速多极子方法（FMM），减少了EFP和QM/EFP模拟的计算量。 在第二阶段，该团队将通过实施鲁棒的参数来进一步提高FMM-QM/EFP代码的效率。 搜索算法。分析核技术的发展将使化学转变的建模成为可能。 梯度和二阶导数。此外，FMM-QM/EFP将与可极化连续体接口 模型（PCM）并扩展到周期性边界条件，为用户提供免费工具 用于模拟远程静电和极化相互作用。新方法将在 建立和新兴的数据机制和能量的溶液相和酶促反应。

Project Summary Modeling of chemical reactivity in heterogeneous environments such as protein pockets and complex solvents is an essential part of a drug discovery workflow. However, such modeling is challenging, due to large system sizes and necessity of extensive sampling of environment degrees of freedom. The goal of this project is to develop a suite of efficient, accurate and scalable computational tools based on the polarizable quantum me- chanics / effective fragment potential (QM/EFP) methodology that will provide academic and private industry users with fast and robust software for the computational characterization of free energy profiles of chemical reactions in complex condensed phase systems. Phase II of this project builds upon the outcomes of a success- ful completion of Phase I, in which the team has developed algorithms and computer codes that dramatically decrease the computational cost of EFP and QM/EFP simulations by employing fast multipole method (FMM). In Phase II the team will further improve the efficiency of FMM-QM/EFP codes by implementing robust par- allel algorithms. Modeling of chemical transformations will be enabled by development of analytic nuclear gradients and second derivatives. Additionally, FMM-QM/EFP will be interfaced with polarizable continuum models (PCM) and extended to periodic boundary conditions that will provide users with complimentary tools for modeling long-range electrostatic and polarization interactions. New methodology will be validated on established and emerging data for mechanisms and energetics of solution-phase and enzymatic reactions.