ReviewFrontiers in bioengineering and biotechnology2015
Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review.
Review in Frontiers in bioengineering and biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Adaptive CVgen: Leveraging reinforcement learning for advanced sampling in protein folding and chemical reactions.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Accelerating Elastic Property Prediction in Fe-C Alloys through Coupling of Molecular Dynamics and Machine Learning.Materials (Basel, Switzerland) · 2024Article
- Multiscale modelling of claudin-based assemblies: A magnifying glass for novel structures of biological interfaces.Computational and structural biotechnology journal · 2022Review
- Review
- Article
- Molecular Modeling of the Catalytic Domain of CyaA Deepened the Knowledge of Its Functional Dynamics.Toxins · 2017Review
- Article
- The allosteric switching mechanism in bacteriophage MS2.The Journal of chemical physics · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.
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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.