ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2021
Uncertainty quantification in classical molecular dynamics.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed.
- Molecular Dynamics Workflows to Compute Large-Scale Sets of Absolute Binding Free Energies Aiding Drug Candidate and Binding Pose Selection.Journal of chemical theory and computation · 2026Article
- Simulation of Mass Transport and Phase Transition through Anodic Alumina Membranes Using a Lattice Boltzmann Method.Langmuir : the ACS journal of surfaces and colloids · 2026Article
- Uncertainty Quantification forChemical reviews · 2026Review
- Plant fucosyltransferase FUT11 distorts the sugar acceptor to catalyze via a transient oxocarbenium intermediate mechanism.Nature communications · 2026Article
- Molecular Dynamics Simulations and Current Trends in Designing New Antivirals Targeting Proteases: A Review from 2018 to 2025.Current drug targets · 2026Review
- Development and Bayesian Uncertainty Quantification of Coarse-Grained Models of Metals Based on Embedded Atom Method Potentials.Journal of chemical theory and computation · 2025Article
- Effects of doping and functionalization on black phosphorus nanosheets for enhanced quercetin delivery.RSC advances · 2025Article
- Frontier advances in molecular dynamics simulations for the design and optimization of oil-displacement polymers.RSC advances · 2025Review
- Lessons Learned on Obtaining Reliable Dynamic Properties for Ionic Liquids.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025Article
- Rapid, Accurate and Reproducible Prediction of the Glass Transition Temperature Using Ensemble-Based Molecular Dynamics Simulation.Journal of chemical theory and computation · 2025Article
- Modeling Heterogeneous Catalysis Using Quantum Computers: An Academic and Industry Perspective.Journal of chemical information and modeling · 2025Review
- Multiscale Responsive Kinetic Modeling: Quantifying Biomolecular Reaction Flux under Varying Electrochemical Conditions.Journal of chemical theory and computation · 2025Article
- Representing Structural Isomer Effects in a Coarse-Grain Model of Poly(Ether Ketone Ketone).Polymers · 2025Article
- Demonstrating the Absence of Correlation Between Molecular Docking and in vitro Cytotoxicity in Anti-Breast Cancer Research: Root Causes and Practical Resolutions.Breast cancer (Dove Medical Press) · 2025Review
- An Entropy Dynamics Approach to Inferring Fractal-Order Complexity in the Electromagnetics of Solids.Entropy (Basel, Switzerland) · 2024Article
- Article
- Repurposing raltegravir for reducing inflammation and treating cancer: a bioinformatics analysis.Scientific reports · 2024Article
- Molecular Insights into the COACS omega · 2024Article
- Multiscale Responsive Kinetic Modeling: Quantifying Biomolecular Reaction Flux under Varying Electrochemical Conditions.bioRxiv : the preprint server for biology · 2024Article
- Uncertainty quantification of the lattice Boltzmann method focussing on studies of human-scale vascular blood flow.Scientific reports · 2024Article
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3 authors.
Funding
Abstract
Molecular dynamics simulation is now a widespread approach for understanding complex systems on the atomistic scale. It finds applications from physics and chemistry to engineering, life and medical science. In the last decade, the approach has begun to advance from being a computer-based means of rationalizing experimental observations to producing apparently credible predictions for a number of real-world applications within industrial sectors such as advanced materials and drug discovery. However, key aspects concerning the reproducibility of the method have not kept pace with the speed of its uptake in the scientific community. Here, we present a discussion of uncertainty quantification for molecular dynamics simulation designed to endow the method with better error estimates that will enable it to be used to report actionable results. The approach adopted is a standard one in the field of uncertainty quantification, namely using ensemble methods, in which a sufficiently large number of replicas are run concurrently, from which reliable statistics can be extracted. Indeed, because molecular dynamics is intrinsically chaotic, the need to use ensemble methods is fundamental and holds regardless of the duration of the simulations performed. We discuss the approach and illustrate it in a range of applications from materials science to ligand-protein binding free energy estimation. This article is part of the theme issue 'Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification
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