金属酶反应强相关校正范围分离局部杂化官能团的评价。

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL
Andrew M M Kai, Tiffany T Nguyen, Robin Grotjahn
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引用次数: 0

摘要

准确地模拟金属酶活性位点的复杂电子结构仍然是密度泛函理论(DFT)面临的重大挑战。MME55试验装置[J]。化学。Theory computer . 2023, 19,8365]是一个最新的基准,为多达116个原子的大型实际相关金属酶模型提供了高水平的DLPNO-CCSD(T)/CBS参考值。到目前为止,表现最好的4级杂交种是MPW1B95-D3(BJ),平均绝对误差(MAE)为2.67 kcal/mol, ωB97M-V (2.78 kcal/mol)。这项工作的重点是距离分离的局部杂化(RSLHs),这是一类最新的4阶泛函,它使用了依赖于实空间和依赖于电子间距离的精确(Hartree-Fock-like)交换的混合。本文还对基于实空间非动态相关模型的强相关校正RSLHs (scRSLHs)进行了评价。性能最好的是scRSLH ωLH23tdB-D4, MAE为2.46 kcal/mol。总体而言,结果反映了从LH到RSLH再到scRSLH的功能发展序列中准确性的系统性提高。然而,我们的分析还表明,实际空间非动态相关模型并不是这种改进的主要驱动因素,而是由功能设计的其他特征主导的。此外,我们还研究了(sc)(RS)LHs在酶催化反应中的作用,包括无金属活性位点模型和酶催化反应的净反应能的ECR20基准。1.45和0.63 kcal/mol的MAEs证实ωLH23tdB-D4是这些装置中性能最好的函数之一。由于原始CCSD(T)/aug-cc-pVDZ + [SCS-MP2/aug-cc-pVTZ - SCS-MP2/aug-cc-pVDZ]参考值不准确,我们使用基于aug-cc-pVXZ (X = D, T, Q)的基集外推法设计了新的规范CCSD(T)/CBS参考值。由于scrslh是最近才出现的,因此这项基准研究伴随着对其作为实用工具的使用的关键评估。我们分析了它们在Turbomole中半数值实现的网格依赖性,并评估了使用多达192个物理CPU内核的共享内存OpenMP架构的计算成本和并行扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of Strong-Correlation Corrected Range-Separated Local Hybrid Functionals for Metalloenzyme Reactions.

Accurately modeling the complex electronic structure of metalloenzyme active sites remains a significant challenge for density functional theory (DFT). The MME55 test set [J. Chem. Theory Comput. 2023, 19, 8365] is a recent benchmark providing high-level DLPNO-CCSD(T)/CBS reference values for large, practically relevant metalloenzyme models with up to 116 atoms. So far, the best-performing rung-4 hybrids were MPW1B95-D3(BJ) with a mean absolute error (MAE) of 2.67 kcal/mol and ωB97M-V (2.78 kcal/mol). This work focuses on range-separated local hybrids (RSLHs), a recent class of rung-4 functionals that use both a real-space dependent and interelectronic distance dependent admixture of exact (Hartree-Fock-like) exchange. Strong-correlation corrected RSLHs (scRSLHs) based on real-space nondynamical correlation models are also assessed. The best-performing functional is the scRSLH ωLH23tdB-D4 with an MAE of 2.46 kcal/mol. Overall, the results reflect a systematic improvement in accuracy along the functional development series from LH to RSLH to scRSLH. However, our analysis also indicates that the real-space nondynamical correlation model is not the primary driver of this improvement, which is instead dominated by other features of the functional design. Additionally, we studied (sc)(RS)LHs for the ENZYMES22 set of enzyme reactions comprising metal-free active site models as well as the ECR20 benchmark of net reaction energies of enzyme-catalyzed reactions. MAEs of 1.45 and 0.63 kcal/mol confirm ωLH23tdB-D4 as one of the top-performing functionals for these sets. Due to inaccuracies in the original CCSD(T)/aug-cc-pVDZ + [SCS-MP2/aug-cc-pVTZ - SCS-MP2/aug-cc-pVDZ] reference values for the ECR20 set, we devise new canonical CCSD(T)/CBS reference values using an aug-cc-pVXZ (X = D, T, Q)-based basis set extrapolation. Because scRSLHs have only very recently emerged, this benchmark study is accompanied by critical assessments of their use as a practical tool. We analyze the grid dependence of their seminumerical implementation in Turbomole and evaluate the computational cost and parallel scaling on a shared-memory OpenMP architecture using up to 192 physical CPU cores.

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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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