Principal component and clustering analysis on molecular dynamics data of the ribosomal L11·23S subdomain.

ABSTRACT: With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria's L11·23S

SUBMITTER: Wolf A 

PROVIDER: S-EPMC3592554 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature