ArticleJournal of chemical theory and computation2015
Efficient Determination of Free Energy Landscapes in Multiple Dimensions from Biased Umbrella Sampling Simulations Using Linear Regression.
Article in Journal of chemical theory and computation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Ligand-Binding Free Energy Simulations of Membrane Proteins.Advances in experimental medicine and biology · 2026Review
- Unraveling the GMACS bio & med chem Au · 2025Article
- Article
- Disulfide bridge-dependent dimerization triggers FGF2 membrane translocation into the extracellular space.eLife · 2024Article
- Computational Evaluation of Peptide-Protein Binding Affinities: Application of Potential of Mean Force Calculations to SH2 Domains.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Cholesterol promotes clustering of PI(4,5)P2 driving unconventional secretion of FGF2.The Journal of cell biology · 2022Article
- Review
- Fighting Against Bacterial Lipopolysaccharide-Caused Infections through Molecular Dynamics Simulations: A Review.Journal of chemical information and modeling · 2021Review
- Plausible compounds drawn from plants as curative agents for neurodegeneration: An in-silico approach.Journal of computer-aided molecular design · 2020Article
- Stratified UWHAM and Its Stochastic Approximation for Multicanonical Simulations Which Are Far from Equilibrium.Journal of chemical theory and computation · 2017Article
- Locally weighted histogram analysis and stochastic solution for large-scale multi-state free energy estimation.The Journal of chemical physics · 2016Article
- A Stochastic Solution to the Unbinned WHAM Equations.The journal of physical chemistry letters · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The weighted histogram analysis method (WHAM) is a standard protocol for postprocessing the information from biased umbrella sampling simulations to construct the potential of mean force with respect to a set of order parameters. By virtue of the WHAM equations, the unbiased density of state is determined by satisfying a self-consistent condition through an iterative procedure. While the method works very effectively when the number of order parameters is small, its computational cost grows rapidly in higher dimension. Here, we present a simple and efficient alternative strategy, which avoids solving the self-consistent WHAM equations iteratively. An efficient multivariate linear regression framework is utilized to link the biased probability densities of individual umbrella windows and yield an unbiased global free energy landscape in the space of order parameters. It is demonstrated with practical examples that free energy landscapes that are comparable in accuracy to WHAM can be generated at a small fraction of the cost.
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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.