ArticleJournal of chemical theory and computation2023
OneOPES, a Combined Enhanced Sampling Method to Rule Them All.
Article in Journal of chemical theory and computation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Adaptive Normal Mode Sampling (aMDeNM) Enhances Exploration of Protein Conformational Space and Reveals the Functional Role of Frequency Coupling.Journal of chemical theory and computation · 2026Article
- AI-Physics-Experiment Trinity for Integrated Protein Dynamics Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Convergence is not correctness: context-dependent performance of enhanced-sampling methods across biological complexity.Nature communications · 2026Article
- Deep learning insights into β-lactamase dynamics and resistance evolution.The Biochemical journal · 2026Review
- Umbrella Sampling Workflows for Fast-Converging PMF Calculations without Artificial WHAM Constraints.Journal of chemical theory and computation · 2026Article
- Computational engineering of the polyester hydrolase PHL7 for efficient poly(ethylene terephthalate) degradation in biocatalytic recycling processes.Nature communications · 2026Article
- Transient tertiary structure in intrinsically disordered proteins revealed by multithermal enhanced sampling.Nature communications · 2026Article
- A Transferable and Robust Computational Framework for Class A GPCR Activation Free Energies.The journal of physical chemistry letters · 2026Article
- Integrated Computer-Aided Drug Design: Advances in GPCR Natural Ligand Discovery.Cell biochemistry and biophysics · 2026Review
- Mechanistic Insights into G Protein-Biased κ-Opioid Receptor Signaling Using Dual-Charged Naltrexamine Amides.Journal of medicinal chemistry · 2026Article
- Decoding Allosteric Inhibition in MALT1: The Hidden Role of Conformational Plasticity in Metastable States via Biased MD and Deep Learning.The journal of physical chemistry. B · 2026Article
- Proposal of metagenomic-origin LRA-5 as a precursor of active β-lactamases through Tyr69Gln and Val166Glu amino acid substitutions: a functional and structural analysis.Antimicrobial agents and chemotherapy · 2026Article
- Reinforced molecular dynamics: Physics-infused generative machine learning model simulates protein motion.PNAS nexus · 2026Article
- The Arch from the Stones: Understanding Protein Folding Energy Landscapes via Bioinspired Collective Variables.The journal of physical chemistry letters · 2025Article
- RNA G-quadruplexes emerge from a compacted coil-like ensemble via multiple pathways.Nucleic acids research · 2025Article
- Enhanced Sampling and Tailored Collective Variables Yield Reproducible Free Energy Landscapes of Beta-1 Adrenergic Receptor Activation.Journal of chemical theory and computation · 2025Article
- Recent computational advances in the identification of cryptic binding sites for drug discovery.Bioinformatics advances · 2025Review
- Binding Modes and Water-Mediation of Polyelectrolyte Adsorption to a Neutral CaCOLangmuir : the ACS journal of surfaces and colloids · 2024Article
- Host-Guest Binding Free Energies à la Carte: An Automated OneOPES Protocol.Journal of chemical theory and computation · 2024Article
- Investigating Ligand-Mediated Conformational Dynamics of Pre-miR21: A Machine-Learning-Aided Enhanced Sampling Study.Journal of chemical information and modeling · 2024Article
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4 authors.
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Abstract
Enhanced sampling techniques have revolutionized molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom called collective variables (CVs) to accelerate a system's dynamics and recover the original system's statistics. However, encoding all the relevant degrees of freedom in a limited number of CVs is challenging, particularly in large biophysical systems. Another category of techniques, such as parallel tempering, simulates multiple replicas of the system in parallel, without requiring CVs. However, these methods may explore less relevant high-energy portions of the phase space and become computationally expensive for large systems. To overcome the limitations of both approaches, we propose a replica exchange method called OneOPES that combines the power of multireplica simulations and CV-based enhanced sampling. This method efficiently accelerates the phase space sampling without the need for ideal CVs, extensive parameters fine tuning nor the use of a large number of replicas, as demonstrated by its successful applications to protein-ligand binding and protein folding benchmark systems. Our approach shows promise as a new direction in the development of enhanced sampling techniques for molecular dynamics simulations, providing an efficient and robust framework for the study of complex and unexplored problems.
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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.