ArticleFrontiers in molecular biosciences2022
Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 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
- Structural Insights and Bioactivity Correlations of Heteroleptic Zn(II)/Cd(II) Complexes: Experimental Characterization, Theoretical Modelling, and Evaluation of Antimicrobial, Anticancer, and Lipase Inhibitory Potentials.Applied biochemistry and biotechnology · 2026Article
- Generation of Pathway Signatures by Combining Normal Modes with Weighted Ensemble Simulations.bioRxiv : the preprint server for biology · 2026Article
- Free energy calculations in molecular modeling: from classical methods to machine learning.Journal of molecular modeling · 2026Review
- A Computationally Efficient Method to Generate Plausible Conformers for Ensemble Docking and Binding Free Energy Calculations.Journal of chemical information and modeling · 2025Article
- Exploring the Intrinsic Structural Plasticity and Conformational Dynamics of Human Beta Coronavirus Spike Glycoproteins.Journal of chemical information and modeling · 2025Article
- Dissection of an Anaerobic Fungal Cellulosomal Endoglucanase: Impact of the Dockerin Module on Activity, Thermostability, and Flexibility.ACS omega · 2025Article
- dyphAI dynamic pharmacophore modeling with AI: a tool for efficient screening of new acetylcholinesterase inhibitors.Frontiers in chemistry · 2025Article
- Extended Sampling of Macromolecular Conformations from Uniformly Distributed Points on Multidimensional Normal Mode Hyperspheres.Journal of chemical theory and computation · 2024Article
- Exploration of Cryptic Pockets Using Enhanced Sampling Along Normal Modes: A Case Study of KRASJournal of chemical information and modeling · 2024Article
- Exploring Protein Conformational Changes Using a Large-Scale Biophysical Sampling Augmented Deep Learning Strategy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Structural and quantum chemical basis for OCP-mediated quenching of phycobilisomes.Science advances · 2024Article
- Investigating Potential Cancer Therapeutics: Insight into Histone Deacetylases (HDACs) Inhibitions.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Interactions of the male contraceptive target EPPIN with semenogelin-1 and small organic ligands.Scientific reports · 2023Article
- AI-Aided Search for New HIV-1 Protease Ligands.Biomolecules · 2023Article
- Cooperative mechanics of PR65 scaffold underlies the allosteric regulation of the phosphatase PP2A.Structure (London, England : 1993) · 2023Article
- Reweighting methods for elucidation of conformation ensembles of proteins.Current opinion in structural biology · 2022Review
- Cryo-electron microscopy unveils unique structural features of the human Kir2.1 channel.Science advances · 2022Article
- ABCG2/BCRP transport mechanism revealed through kinetically excited targeted molecular dynamics simulations.Computational and structural biotechnology journal · 2022Article
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Authors and funding
10 authors.
Funding
Abstract
Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.
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