Premium
Cluster analysis of molecular simulation trajectories for systems where both conformation and orientation of the sampled states are important
Author(s) -
Abramyan Tigran M.,
Snyder James A.,
Thyparambil Aby A.,
Stuart Steven J.,
Latour Robert A.
Publication year - 2016
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.24416
Subject(s) - cluster analysis , cluster (spacecraft) , hierarchical clustering , orientation (vector space) , biomolecule , molecular dynamics , biological system , computer science , data mining , chemistry , computational chemistry , artificial intelligence , mathematics , biology , geometry , programming language , biochemistry
Clustering methods have been widely used to group together similar conformational states from molecular simulations of biomolecules in solution. For applications such as the interaction of a protein with a surface, the orientation of the protein relative to the surface is also an important clustering parameter because of its potential effect on adsorbed‐state bioactivity. This study presents cluster analysis methods that are specifically designed for systems where both molecular orientation and conformation are important, and the methods are demonstrated using test cases of adsorbed proteins for validation. Additionally, because cluster analysis can be a very subjective process, an objective procedure for identifying both the optimal number of clusters and the best clustering algorithm to be applied to analyze a given dataset is presented. The method is demonstrated for several agglomerative hierarchical clustering algorithms used in conjunction with three cluster validation techniques. © 2016 Wiley Periodicals, Inc.