Literature DB >> 20148971

A hybrid clustering of protein binding sites.

Gábor Iván1, Zoltán Szabadka, Vince Grolmusz.   

Abstract

The Protein Data Bank contains the description of approximately 27 000 protein-ligand binding sites. Most of the ligands at these sites are biologically active small molecules, affecting the biological function of the protein. The classification of their binding sites may lead to relevant results in drug discovery and design. Clusters of similar binding sites were created here by a hybrid, sequence and spatial structure-based approach, using the OPTICS clustering algorithm. A dissimilarity measure was defined: a distance function on the amino acid sequences of the binding sites. All the binding sites were clustered in the Protein Data Bank according to this distance function, and it was found that the clusters characterized well the Enzyme Commission numbers of the entries. The results, carefully color coded by the Enzyme Commission numbers of the proteins, containing the 20 967 binding sites clustered, are available as html files in three parts at http://pitgroup.org/seqclust/.

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Year:  2010        PMID: 20148971     DOI: 10.1111/j.1742-4658.2010.07578.x

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  3 in total

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Journal:  BMC Struct Biol       Date:  2014-10-18

2.  Sequence-based prediction of physicochemical interactions at protein functional sites using a function-and-interaction-annotated domain profile database.

Authors:  Min Han; Yifan Song; Jiaqiang Qian; Dengming Ming
Journal:  BMC Bioinformatics       Date:  2018-06-01       Impact factor: 3.169

3.  SCARF: a biomedical association rule finding webserver.

Authors:  Balázs Szalkai; Vince Grolmusz
Journal:  J Integr Bioinform       Date:  2022-02-04
  3 in total

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