CapsidMaps: protein-protein interaction pattern discovery platform for the structural analysis of virus capsids using Google Maps.

Authors:
Dr. Mauricio Carrillo-Tripp, PhD
Dr. Mauricio Carrillo-Tripp, PhD
Biomolecular Diversity Laboratory, Cinvestav
Associate Profesor
Computational Biophysics
Irapuato, Guanajuato | México
Charles L Brooks
Charles L Brooks
University of Michigan
United States
Vijay S Reddy
Vijay S Reddy
The Scripps Research Institute
United States

J Struct Biol 2015 Apr 16;190(1):47-55. Epub 2015 Feb 16.

Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.

Structural analysis and visualization of protein-protein interactions is a challenging task since it is difficult to appreciate easily the extent of all contacts made by the residues forming the interfaces. In the case of viruses, structural analysis becomes even more demanding because several interfaces coexist and, in most cases, these are formed by hundreds of contacting residues that belong to multiple interacting coat proteins. CapsidMaps is an interactive analysis and visualization tool that is designed to benefit the structural virology community. Developed as an improved extension of the φ-ψ Explorer, here we describe the details of its design and implementation. We present results of analysis of a spherical virus to showcase the features and utility of the new tool. CapsidMaps also facilitates the comparison of quaternary interactions between two spherical virus particles by computing a similarity (S)-score. The tool can also be used to identify residues that are solvent exposed and in the process of locating antigenic epitope regions as well as residues forming the inside surface of the capsid that interact with the nucleic acid genome. CapsidMaps is part of the VIPERdb Science Gateway, and is freely available as a web-based and cross-browser compliant application at http://viperdb.scripps.edu.

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Source
http://dx.doi.org/10.1016/j.jsb.2015.02.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4750372PMC

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April 2015
20 Reads
1 PubMed Central Citation(source)
3.23 Impact Factor

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