Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Tatiana Maximova, Ryan Moffatt, Buyong Ma, Ruth Nussinov, Amarda Shehu*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

Original languageEnglish
Article numbere1004619
JournalPLoS Computational Biology
Volume12
Issue number4
DOIs
StatePublished - Apr 2016

Funding

FundersFunder number
National Cancer InstituteZIABC010442

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