title: Identifying and correcting non-Markov states in peptide conformational dynamics.
abstract: Conformational transitions in proteins define their biological activity and can be investigated in detail using the Markov state model. The fundamental assumption on the transitions between the states, their Markov property, is critical in this framework. We test this assumption by analyzing the transitions obtained directly from the dynamics of a molecular dynamics simulated peptide valine-proline-alanine-leucine and states defined phenomenologically using clustering in dihedral space. We find that the transitions are Markovian at the time scale of approximately 50 ps and longer. However, at the time scale of 30-40 ps the dynamics loses its Markov property. Our methodology reveals the mechanism that leads to non-Markov behavior. It also provides a way of regrouping the conformations into new states that now possess the required Markov property of their dynamics.
authors.affiliation: Department of Chemistry, Unilever Centre for Molecular Sciences Informatics, Cambridge University, CB2 1EW Cambridge, United Kingdom. dn232@cam.ac.uk
authors.forename: Dmitry
authors.initials: D
authors.lastname: Nerukh
authors.forename: Christian H
authors.initials: CH
authors.lastname: Jensen
authors.forename: Robert C
authors.initials: RC
authors.lastname: Glen
mesh_terms: D008390:Markov Chains; D056004:Molecular Dynamics Simulation; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation
chemical_list: D010455:Peptides