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CAMERRA: An analysis tool for the computation of conformational dynamics by evaluating residue–residue associations
Author(s) -
Johnson Quentin R.,
Lindsay Richard J.,
Shen Tongye
Publication year - 2018
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.25192
Subject(s) - principal component analysis , computer science , computation , cartesian coordinate system , visualization , molecular dynamics , allosteric regulation , covariance , graphics , biological system , algorithm , theoretical computer science , chemistry , computational chemistry , mathematics , data mining , artificial intelligence , biochemistry , statistics , geometry , biology , enzyme , computer graphics (images)
A computational method which extracts the dominant motions from an ensemble of biomolecular conformations via a correlation analysis of residue–residue contacts is presented. The algorithm first renders the structural information into contact matrices, then constructs the collective modes based on the correlated dynamics of a selected set of dynamic contacts. Associated programs can bridge the results for further visualization using graphics software. The aim of this method is to provide an analysis of conformations of biopolymers from the contact viewpoint. It may assist a systematical uncovering of conformational switching mechanisms existing in proteins and biopolymer systems in general by statistical analysis of simulation snapshots. In contrast to conventional correlation analyses of Cartesian coordinates (such as distance covariance analysis and Cartesian principal component analysis), this program also provides an alternative way to locate essential collective motions in general. Herein, we detail the algorithm in a stepwise manner and comment on the importance of the method as applied to decoding allosteric mechanisms. © 2018 Wiley Periodicals, Inc.