PocketGraph : graph representation of binding site volumes

  • The representation of small molecules as molecular graphs is a common technique in various fields of cheminformatics. This approach employs abstract descriptions of topology and properties for rapid analyses and comparison. Receptor-based methods in contrast mostly depend on more complex representations impeding simplified analysis and limiting the possibilities of property assignment. In this study we demonstrate that ligand-based methods can be applied to receptor-derived binding site analysis. We introduce the new method PocketGraph that translates representations of binding site volumes into linear graphs and enables the application of graph-based methods to the world of protein pockets. The method uses the PocketPicker algorithm for characterization of binding site volumes and employs a Growing Neural Gas procedure to derive graph representations of pocket topologies. Self-organizing map (SOM) projections revealed a limited number of pocket topologies. We argue that there is only a small set of pocket shapes realized in the known ligand-receptor complexes.

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Metadaten
Author:Martin Weisel, Jan M. Kriegl, Gisbert SchneiderORCiDGND
URN:urn:nbn:de:hebis:30-66680
DOI:https://doi.org/10.1186/1752-153X-3-S1-P66
ISSN:1752-153X
Parent Title (English):Chemistry central journal
Publisher:BioMed Central
Place of publication:London
Document Type:Article
Language:English
Date of Publication (online):2009/08/26
Date of first Publication:2009/06/05
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Contributing Corporation:4th German Conference on Chemoinformatics Goslar, Germany. 9–11 November 2008
Release Date:2009/08/26
Volume:3
Issue:(Suppl 1):P66
Page Number:1
First Page:1
Last Page:1
Note:
© 2009 Weisel et al; licensee BioMed Central Ltd.
Source:4th German Conference on Chemoinformatics Goslar, Germany. 9–11 November 2008 ; Chemistry Central Journal 2009, 3(Suppl 1):P66 ; doi:10.1186/1752-153X-3-S1-P66 ; http://www.journal.chemistrycentral.com/content/3/S1/P66
HeBIS-PPN:215152123
Institutes:Biochemie, Chemie und Pharmazie / Biochemie und Chemie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
Licence (German):License LogoDeutsches Urheberrecht