Next Generation Methods for Advanced Condensed Phase Simulations in Q-Chem

项目总结 Q-Chem高级凝聚相模拟的新一代方法 生物物理系统存在于浓缩阶段，这是它们 属性应该是计算机建模的。描述电子的正确理论是用从头算 从头算(AI)量子力学(QM)，而核运动需要分子动力学(MD)。这个 因此，AIMD组合是生物物理模拟的合适工具。在使用AIMD时 比具有经验潜力的MD贵得多，但它仍然是理想的标准 致。AIMD能够正确处理反应过程的键断裂，以及准确的 对决定溶剂化和构象偏好的非键相互作用的描述。 此第二阶段提案的目标是将生产级AIMD代码引入Q-Chem 软件包。建议工作的关键JUSTIfi阳离子，以及由此产生的潜在价值 产品的特点是它将汇集任何其他AIMD代码中没有的功能。 周期边界的密度泛函理论实现之间有价值的协同作用 条件(DFT-PBC)，以及用于科学、准确地传播MD IS的EFfi的先进算法 这个项目的核心创新之处在于。 对于dft-pbc(first specific Aim)，重点是实现高精度、高性能。 具有高级泛函的离散傅里叶变换关键部件的EFfi算法。我们的代码将 支持包含非局部的最新元广义梯度近似(MGGA) 范德华密度泛函，迄今在DFT-PBC代码中不可用。我们将增加- ALI提供对距离分离的精确交换的支持，fi效率高。这些能力将 伴随着能量和梯度而来。我们的软件框架也可以实现全电子计算 根据需要，例如用于依赖于原子核的电子密度的核磁共振性质。我们的模块 代码将支持有效的fi节点上并行。 为了科学稳定地传播MD effi(第二种fi目标)，我们采用了两种创新的统计方法-- 已在传统MD中得到验证但尚不可用的物理力学(SM)算法 在任何产品AIMD代码中。首先，我们推广了惯性扩展拉格朗日自洽 fiELD(IEL/SCF)方法与AIMD一起稳健而有效地工作，建立在充满希望的阶段 通过将其与随机等速积分(SII)方案相结合来实现单个BUT 较大的MD时间步长。第二，我们将探索IEL/SCF-SII与多时间- 将探索QM力的不同分量是否可以更新的步进方法 在AIMD的不同时间尺度上。 在fiNAL目标3中，我们在生物物理应用上测试了组合的密度泛函和超临界流体力学性能。 水溶液和分子晶体中的阳离子，包括两性离子甘氨酸和缬氨酸肽。 1

PROJECT SUMMARY Next Generation Methods for Advanced Condensed Phase Simulations in Q-Chem Biophysical systems exist in the condensed phase, and that is the environment in which their properties should be computer-modeled. The correct theory to describe the electrons is using ab initio (AI) quantum mechanics (QM), whilst nuclear motion requires molecular dynamics (MD). The combination, AIMD, is thus the appropriate tool for biophysical simulations. While use of AIMD is vastly more expensive than MD with empirical potentials, it is nonetheless the standard to aspire to. AIMD enables correct treatment of bond-breaking for reactive processes, as well an accurate description of the non-bonded interactions that determine solvation and conformational preferences. This Phase II proposal has the objective of bringing a production level AIMD code to the Q-Chem software package. The key justification for the proposed work, and the potential value of the resulting product is that it will bring together capabilities that are not found jointly in any other AIMD code. The valuable synergy between the density functional theory implementation for periodic boundary conditions (DFT-PBC), and advanced algorithms for efficiently and accurate propagating the MD is the core innovation of this project. With regard to DFT-PBC (the first specific aim), the focus is on implementing high precision, high efficiency algorithms for the critical components of DFT with advanced functionals. Our code will support the latest meta-generalized gradient approximations (mGGAs), with inclusion of non-local van der Waals density functionals, that are not available in DFT-PBC codes to date. We will addition- ally provide support for range-separated exact exchange, with high efficiency. These capabilities will come with energies and gradients. Our software framework can also permit all-electron calculations as needed e.g. for NMR properties that depend on the electron density at the nucleus. Our modular code will support efficient on-node parallelism. To propagate MD efficiently and stably (the second specific aim), we employ two innovative statis- tical mechanics (SM) algorithms that have been proven in conventional MD, but are not yet available in any production AIMD code. First, we are extending the inertial extended Lagrangian self-consistent field (iEL/SCF) method to work robustly and efficiently with AIMD, building upon promising Phase I results, by combining it with a stochastic-isokinetic integration (SII) scheme to enable a single but larger MD time step. Second, we will explore the combination of iEL/SCF-SII with a multiple time- stepping method in which will explore whether different components of the QM force can be updated on different timescales in the AIMD. In final Aim 3 we test the combined DFT-PBC and iEL/SCF-SII capabilities on biophysical appli- cations including zwitterionic glycine and valine peptides in aqueous solution and molecular crystals. 1