ArticleThe Journal of chemical physics2011
Force-momentum-based self-guided Langevin dynamics: a rapid sampling method that approaches the canonical ensemble.
Article in The Journal of chemical physics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Self-Guided Molecular Simulation Methods.International journal of molecular sciences · 2025Review
- Alisol A, the Eye-Entering Ingredient ofDrug design, development and therapy · 2024Article
- Reformulation of the self-guided molecular simulation method.The Journal of chemical physics · 2020Article
- Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy.Acta crystallographica. Section F, Structural biology communications · 2019Review
- On the convergence of multi-scale free energy simulations.Molecular simulation · 2018Article
- Mapping the Drude polarizable force field onto a multipole and induced dipole model.The Journal of chemical physics · 2017Article
- Self-guided Langevin dynamics via generalized Langevin equation.Journal of computational chemistry · 2016Article
- A Virtual Mixture Approach to the Study of Multistate Equilibrium: Application to Constant pH Simulation in Explicit Water.PLoS computational biology · 2015Article
- Constant pH Molecular Dynamics in Explicit Solvent with Enveloping Distribution Sampling and Hamiltonian Exchange.Journal of chemical theory and computation · 2014Article
- Phosphoproteomic analysis reveals regulatory mechanisms at the kidney filtration barrier.Journal of the American Society of Nephrology : JASN · 2014Article
- Targeted conformational search with map-restrained self-guided Langevin dynamics: application to flexible fitting into electron microscopic density maps.Journal of structural biology · 2013Article
- pH-dependent dynamics of complex RNA macromolecules.Journal of chemical theory and computation · 2013Article
- Accurate high-throughput structure mapping and prediction with transition metal ion FRET.Structure (London, England : 1993) · 2013Article
- Enhanced Sampling in Free Energy Calculations: Combining SGLD with the Bennett's Acceptance Ratio and Enveloping Distribution Sampling Methods.Journal of chemical theory and computation · 2012Article
- Replica exchanging self-guided Langevin dynamics for efficient and accurate conformational sampling.The Journal of chemical physics · 2012Article
- Efficient and Unbiased Sampling of Biomolecular Systems in the Canonical Ensemble: A Review of Self-Guided Langevin Dynamics.Advances in chemical physics · 2012Article
- Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review.Molecular simulationArticle
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2 authors.
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Abstract
The self-guided Langevin dynamics (SGLD) is a method to accelerate conformational searching. This method is unique in the way that it selectively enhances and suppresses molecular motions based on their frequency to accelerate conformational searching without modifying energy surfaces or raising temperatures. It has been applied to studies of many long time scale events, such as protein folding. Recent progress in the understanding of the conformational distribution in SGLD simulations makes SGLD also an accurate method for quantitative studies. The SGLD partition function provides a way to convert the SGLD conformational distribution to the canonical ensemble distribution and to calculate ensemble average properties through reweighting. Based on the SGLD partition function, this work presents a force-momentum-based self-guided Langevin dynamics (SGLDfp) simulation method to directly sample the canonical ensemble. This method includes interaction forces in its guiding force to compensate the perturbation caused by the momentum-based guiding force so that it can approximately sample the canonical ensemble. Using several example systems, we demonstrate that SGLDfp simulations can approximately maintain the canonical ensemble distribution and significantly accelerate conformational searching. With optimal parameters, SGLDfp and SGLD simulations can cross energy barriers of more than 15 kT and 20 kT, respectively, at similar rates for LD simulations to cross energy barriers of 10 kT. The SGLDfp method is size extensive and works well for large systems. For studies where preserving accessible conformational space is critical, such as free energy calculations and protein folding studies, SGLDfp is an efficient approach to search and sample the conformational space.
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