ArticleJournal of chemical theory and computation2022
Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Evaluating Mechanical-Embedding ML/MM for Predicting Mutation Effects in Chorismate Mutase Catalysis.Journal of chemical theory and computation · 2026Article
- Quantum-Centric Alchemical Free Energy Calculations.Journal of chemical theory and computation · 2026Article
- Simulating enzyme catalysis with electrostatically embedded machine learning potentials.Chemical science · 2026Article
- FE-ToolKit: A Versatile Software Suite for Analysis of High-Dimensional Free Energy Surfaces and Alchemical Free Energy Networks.Journal of chemical information and modeling · 2025Article
- Transferability of MACE Graph Neural Network for Range Corrected Δ-Machine Learning Potential QM/MM Applications.The journal of physical chemistry. B · 2025Article
- DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.Journal of chemical information and modeling · 2025Article
- Method and Implementation of Projected Hybrid Orbitals for Treating Multiple Covalent Bonds in Combined QM/MM Calculations.Journal of chemical theory and computation · 2024Article
- Software Infrastructure for Next-Generation QM/MM-ΔMLP Force Fields.The journal of physical chemistry. B · 2024Article
- Electronic and Nuclear Quantum Effects on Proton Transfer Reactions of Guanine-Thymine (G-T) Mispairs Using Combined Quantum Mechanical/Molecular Mechanical and Machine Learning Potentials.Molecules (Basel, Switzerland) · 2024Article
- Surface-Accelerated String Method for Locating Minimum Free Energy Paths.Journal of chemical theory and computation · 2024Article
- Electrostatics as a Guiding Principle in Understanding and Designing Enzymes.Journal of chemical theory and computation · 2024Review
- Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development.ACS omega · 2024Review
- DeePMD-kit v2: A software package for deep potential models.The Journal of chemical physics · 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
- Does a Machine-Learned Potential Perform Better Than an Optimally Tuned Traditional Force Field? A Case Study on Fluorohydrins.Journal of chemical information and modeling · 2023Article
- Estimation of frequency factors for the calculation of kinetic isotope effects from classical and path integral free energy simulations.The Journal of chemical physics · 2023Article
- Modern semiempirical electronic structure methods and machine learning potentials for drug discovery: Conformers, tautomers, and protonation states.The Journal of chemical physics · 2023Article
- Electrostatic Embedding of Machine Learning Potentials.Journal of chemical theory and computation · 2023Article
- QDπ: A Quantum Deep Potential Interaction Model for Drug Discovery.Journal of chemical theory and computation · 2023Article
- Multireference Generalization of the Weighted Thermodynamic Perturbation Method.The journal of physical chemistry. A · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
We present a fast, accurate, and robust approach for determination of free energy profiles and kinetic isotope effects for RNA 2'-O-transphosphorylation reactions with inclusion of nuclear quantum effects. We apply a deep potential range correction (DPRc) for combined quantum mechanical/molecular mechanical (QM/MM) simulations of reactions in the condensed phase. The method uses the second-order density-functional tight-binding method (DFTB2) as a fast, approximate base QM model. The DPRc model modifies the DFTB2 QM interactions and applies short-range corrections to the QM/MM interactions to reproduce
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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.