Lian Duan, Kowit Hengphasatporn, Ryuhei Harada, Yasuteru Shigeta
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引用次数: 0
Abstract
Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations are essential for elucidating complex biochemical reaction mechanisms. However, conventional enhanced sampling methods, such as umbrella sampling and metadynamics, often face limitations in computational cost, sampling completeness, and reliance on predefined reaction coordinates. To address these challenges, we developed Parallel Cascade Selection QM/MM MD (PaCS-Q) simulation, a novel strategy that efficiently explores reaction pathways by iteratively identifying high-potential structures for configurational transitions without predefined biases or external constraints. PaCS-Q directly tracks changes in bond distances over time, enabling the identification of transition states and intermediates. Validation of the Claisen rearrangement in chorismate mutase and the peptidyl aldehyde reaction in the Zika virus NS2B/NS3 serine protease demonstrated accurate pathway capture, reduced computational costs, and efficient sampling. With its user-friendly workflow, PaCS-Q broadens accessibility for computational and experimental researchers, offering a robust tool for studying enzymatic mechanisms with high accuracy and efficiency.
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Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere.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.