ArticleJournal of chemical theory and computation2021
Accelerated Computation of Free Energy Profile at
Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Transferability of MACE Graph Neural Network for Range Corrected Δ-Machine Learning Potential QM/MM Applications.The journal of physical chemistry. B · 2025Article
- Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions.Journal of chemical theory and computation · 2025Article
- Convergence criteria for single-step free-energy calculations: the relation between the Π bias measure and the sample variance.Chemical science · 2024Article
- Relative cooperativity in neutral and charged molecular clusters using QM/MM calculations.The Journal of chemical physics · 2024Article
- Adaptive-Partitioning Multilayer Dynamics Simulations: 2. Implementations of the Permuted and Interpolated Adaptive-Partitioning Gradients.The journal of physical chemistry. A · 2023Article
- Perspective: Reference-Potential Methods for the Study of Thermodynamic Properties in Chemical Processes: Theory, Applications, and Pitfalls.The journal of physical chemistry letters · 2023Review
- Exploring Routes to Enhance the Calculation of Free Energy Differences via Non-Equilibrium Work SQM/MM Switching Simulations Using Hybrid Charge Intermediates between MM and SQM Levels of Theory or Non-Linear Switching Schemes.Molecules (Basel, Switzerland) · 2023Article
- Multireference Generalization of the Weighted Thermodynamic Perturbation Method.The journal of physical chemistry. A · 2022Article
- AcceleratingThe journal of physical chemistry. B · 2022Article
- Factors That Determine the Variation of Equilibrium and Kinetic Properties of QM/MM Enzyme Simulations: QM Region, Conformation, and Boundary Condition.Journal of chemical theory and computation · 2022Article
- Quantum Vibrational Spectroscopy of Explicitly Solvated Thymidine in Semiclassical Approximation.The journal of physical chemistry letters · 2022Article
- AffordableThe journal of physical chemistry. A · 2021Article
- Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions.Journal of chemical theory and computation · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Although quantum mechanical/molecular mechanics (QM/MM) methods are now routinely applied to the studies of chemical reactions in condensed phases and enzymatic reactions, they may experience technical difficulties when the reactive region is varying over time. For instance, when the solvent molecules are directly participating in the reaction, the exchange of water molecules between the QM and MM regions may occur on a time scale comparable to the reaction time. To cope with this situation, several adaptive QM/MM schemes have been proposed. However, these methods either add significantly to the computational cost or introduce artificial restraints to the system. In this work, we developed a novel adaptive QM/MM scheme and applied it to the study of a nucleophilic addition reaction. In this scheme, the configuration sampling was performed with a small QM region (without solvent molecules), and the thermodynamic properties under another potential energy function with a larger QM region (with a certain number of solvent molecules and/or different levels of QM theory) are computed via extrapolation using the reference-potential method. Our simulation results show that this adaptive QM/MM scheme is numerically stable, at least for the case studied in this work. Furthermore, this method also offers an inexpensive way to examine the convergence of the QM/MM calculation with respect to the size of the QM region.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.