Towards the prediction of order parameters from molecular dynamics simulations in proteins

Juan R. Perilla, Thomas B. Woolf

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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.

Original languageEnglish (US)
Article number164101
JournalJournal of Chemical Physics
Issue number16
StatePublished - Apr 28 2012

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry


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