Work

Improvements in Markov State Model Construction Reveal Many Non-Native Interactions in the Folding of NTL9

Year: 2013

Type: article

Abstract: Markov State Models (MSMs) provide an automated framework to investigate the dynamical properties of high-dimensional molecular simulations. These models can provide a human-comprehensible picture of the underlying process and have been successfully used to study protein folding, protein aggregation, protein ligand binding, and other biophysical systems. The MSM requires the construction of a discrete state-space such that two points are in the same state if they can interconvert rapidly. In the following, we suggest an improved method, which utilizes second order Independent Component Analysis (also known as time-structure based Independent Component Analysis, or tICA), to construct the state-space. We apply this method to simulations of NTL9 (provided by Lindorff-Larsen et al. Science 2011, 334, 517–520) and show that the MSM is an improvement over previously built models using conventional distance metrics. Additionally, the resulting model provides insight into the role of non-native contacts by revealing many slow time scales associated with compact, non-native states.

Source: Journal of Chemical Theory and Computation

DOI: 10.1021/ct300878a

Authors: Christian R. Schwantes, Vijay S. Pande

Institution: Stanford University

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, National Institute of General Medical Sciences

Awards: Enabling long timestep molecular dynamics on parallel CPU and GPU environments, Folding@Home: Simulating Folding on the Millisecond to Second Timescale