Elucidating molecular mechanisms of functional conformational changes of proteins via Markov state models. (April 2021)

• Record Type: Journal Article
• Authors: Wang, Xiaowei; Unarta, Ilona Christy; Cheung, Peter Pak-Hang; Huang, Xuhui
• Is Part Of: Current opinion in structural biology. Volume 67(2021)
• Page Start: 69
• Page End: 77
• Publication Date: 2021-04
• Subjects: Molecular biology -- Periodicals; 570
• DOI: 10.1016/j.sbi.2020.10.005
• Languages: English
• ISSNs: 0959-440X

Abstract

Highlights: We introduce a state-of-the-art protocol to build the MSM. We recommend spectral oASIS to automatically select physical features. We review applications of MSM on studying protein functional conformational changes. We discuss the perspective of quasi-MSM and deep learning methods for MSM. Abstract : Functional conformational changes of proteins can facilitate numerous biological events in cells. The Markov state model (MSM) built from molecular dynamics simulations provide a powerful approach to study them. We here introduce a protocol that is tailor-made for constructing MSMs to study the functional conformational changes of proteins. In this protocol, one of the important steps is to select proper molecular features that can collectively describe the slowest timescales of conformational changes of interest. We recommend spectral oASIS, the modified version of oASIS, as a promising approach for automatic feature selection. Recently developed deep learning methods could also serve efficient approaches for selecting features and finding collective variables. Using DNA repair enzymes and RNA polymerases as examples, we review recent applications of MSMs to elucidate molecular mechanisms of functional conformational changes. Finally, we discuss remaining challenges and future perspectives for constructing MSMs to study functional conformational changes of proteins.