Craig, Ian (2011) PocketAnalyzerPCA. Project is software (source code) to be "published" as download from a website.

Abstract

PocketAnalyzerPCA is a software tool for detecting and analysing pocket shapes in large sets of protein structures. A particular strength is the use of Principal Component Analysis to characterise the dominant changes in pocket shape within a set of structures, and to thus map out the pocket conformational distribution. This analysis provides a novel perspective on protein flexibility from which to interpret and exploit Molecular Dynamics (MD) simulations. The tool may also be useful for investigating the increasing volume of experimentally-derived protein structural information derived from techniques such as high-throughput crystallography.

This submission contains the Python source code for PocketAnalyzerPCA, which is to be distributed under the open-source BSD license. Also included are a manual, some examples, and an additional Python script for clustering the PocketAnalyzerPCA output using the CLARA algorithm implement in R. Amongst other things, the latter is useful for selecting a small number of diverse pocket conformations from a large biostructural dataset. Such a subset presents medicinal chemistry with an opportunity to explore different regions of chemical space, and may also be used to account for protein flexibility in other structure-based drug design methods.

Item Type:	Article
Date Deposited:	13 Oct 2015 13:15
Last Modified:	13 Oct 2015 13:15
URI:	https://oak.novartis.com/id/eprint/3521