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J Chem Theory Comput. 2014 Nov 11;10(11):5047-5056. Epub 2014 Sep 29.

POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics.

Author information

1
Department of Chemistry & Biochemistry, University of California San Diego , La Jolla, California 92093, United States ; National Biomedical Computation Resource, Center for Research in Biological Systems, University of California San Diego , La Jolla, California 92093, United States.
2
Department of Chemistry & Biochemistry, University of California San Diego , La Jolla, California 92093, United States.

Abstract

Analysis of macromolecular/small-molecule binding pockets can provide important insights into molecular recognition and receptor dynamics. Since its release in 2011, the POVME (POcket Volume MEasurer) algorithm has been widely adopted as a simple-to-use tool for measuring and characterizing pocket volumes and shapes. We here present POVME 2.0, which is an order of magnitude faster, has improved accuracy, includes a graphical user interface, and can produce volumetric density maps for improved pocket analysis. To demonstrate the utility of the algorithm, we use it to analyze the binding pocket of RNA editing ligase 1 from the unicellular parasite Trypanosoma brucei, the etiological agent of African sleeping sickness. The POVME analysis characterizes the full dynamics of a potentially druggable transient binding pocket and so may guide future antitrypanosomal drug-discovery efforts. We are hopeful that this new version will be a useful tool for the computational- and medicinal-chemist community.

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