ArticleJournal of chemical theory and computation2017
Stratified UWHAM and Its Stochastic Approximation for Multicanonical Simulations Which Are Far from Equilibrium.
Article in Journal of chemical theory and computation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Biomolecular dynamics in the 21st century.Biochimica et biophysica acta. General subjects · 2024Review
- Hydrophobicity of arginine leads to reentrant liquid-liquid phase separation behaviors of arginine-rich proteins.Nature communications · 2022Article
- Protein Loop Conformational Free Energy Changes via an Alchemical Path without Reaction Coordinates.The journal of physical chemistry letters · 2021Article
- The UWHAM and SWHAM Software Package.Scientific reports · 2019Article
- The Excess Chemical Potential of Water at the Interface with a Protein from End Point Simulations.The journal of physical chemistry. B · 2018Article
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4 authors.
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Abstract
We describe a new analysis tool called Stratified unbinned Weighted Histogram Analysis Method (Stratified-UWHAM), which can be used to compute free energies and expectations from a multicanonical ensemble when a subset of the parallel simulations is far from being equilibrated because of barriers between free energy basins which are only rarely (or never) crossed at some states. The Stratified-UWHAM equations can be obtained in the form of UWHAM equations but with an expanded set of states. We also provide a stochastic solver, Stratified RE-SWHAM, for Stratified-UWHAM to remove its computational bottleneck. Stratified-UWHAM and Stratified RE-SWHAM are applied to study three test topics: the free energy landscape of alanine dipeptide, the binding affinity of a host-guest binding complex, and path sampling for a two-dimensional double well potential. The examples show that when some of the parallel simulations are only locally equilibrated, the estimates of free energies and equilibrium distributions provided by the conventional UWHAM (or MBAR) solutions exhibit considerable biases, but the estimates provided by Stratified-UWHAM and Stratified RE-SWHAM agree with the benchmark very well. Lastly, we discuss features of the Stratified-UWHAM approach which is based on coarse-graining in relation to two other maximum likelihood-based methods which were proposed recently, that also coarse-grain the multicanonical data.
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