Algorithmic improvements in large scale polarizable QM/MM simulations

项目摘要 蛋白质袋和复杂溶剂等非均相环境中化学反应的模拟 是flow药物发现工作的重要组成部分。然而，由于系统庞大，这样的建模具有挑战性 环境自由度的大小和广泛抽样的必要性。这个项目的目标是 开发了一套基于可极化量子模型的EFfi有效、精确和可伸缩的计算工具。 Chanics/有效碎片潜力(QM/EFP)方法，将为学术界和私营行业提供 用户使用快速和强大的软件来计算化学自由能过程的特征 复杂凝聚相体系中的反应。该项目的第二阶段建立在成功成果的基础上- 圆满完成第一阶段，在这一阶段中，该团队开发了算法和计算机代码， 通过使用快速多极子方法(FMM)，降低了EFP和QM/EFP模拟的计算量。 在第二阶段，团队将通过实施稳健的fi-QM/EFP码来进一步提高FMM-QM/EFP码的效率。 Allel算法。分析核的发展将使化学变化的模拟成为可能 梯度和二阶导数。此外，FMM-QM/EFP将与可极化连续体对接 模型(PCM)，并扩展到周期性边界条件，将为用户提供免费工具 用于对远程静电和极化相互作用进行建模。新方法将在以下方面进行验证 关于溶液和酶反应的机理和能量学的既定数据和新兴数据。

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.