ArticleThe Journal of chemical physics2012
Towards the prediction of order parameters from molecular dynamics simulations in proteins.
Article in The Journal of chemical physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- Thermodynamic and Kinetic Analysis of Molecular Conformational Dynamics in a Riemannian Framework.The journal of physical chemistry. A · 2026Article
- The limits of human mobility traces to predict the spread of COVID-19: A transfer entropy approach.PNAS nexus · 2023Article
- Modeling Functional Motions of Biological Systems by Customized Natural Moves.Biophysical journal · 2016Article
- Computational Recipe for Efficient Description of Large-Scale Conformational Changes in Biomolecular Systems.Journal of chemical theory and computation · 2014Article
- Quantification of Drive-Response Relationships Between Residues During Protein Folding.Journal of chemical theory and computation · 2013Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A molecular understanding of how protein function is related to protein structure requires an ability to understand large conformational changes between multiple states. Unfortunately these states are often separated by high free energy barriers and within a complex energy landscape. This makes it very difficult to reliably connect, for example by all-atom molecular dynamics calculations, the states, their energies, and the pathways between them. A major issue needed to improve sampling on the intermediate states is an order parameter--a reduced descriptor for the major subset of degrees of freedom--that can be used to aid sampling for the large conformational change. We present a method to combine information from molecular dynamics using non-linear time series and dimensionality reduction, in order to quantitatively determine an order parameter connecting two large-scale conformationally distinct protein states. This new method suggests an implementation for molecular dynamics calculations that may be used to enhance sampling of intermediate states.
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Registered trials
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