Literature DB >> 16563002

sc-PDB: an annotated database of druggable binding sites from the Protein Data Bank.

Esther Kellenberger1, Pascal Muller, Claire Schalon, Guillaume Bret, Nicolas Foata, Didier Rognan.   

Abstract

The sc-PDB is a collection of 6 415 three-dimensional structures of binding sites found in the Protein Data Bank (PDB). Binding sites were extracted from all high-resolution crystal structures in which a complex between a protein cavity and a small-molecular-weight ligand could be identified. Importantly, ligands are considered from a pharmacological and not a structural point of view. Therefore, solvents, detergents, and most metal ions are not stored in the sc-PDB. Ligands are classified into four main categories: nucleotides (< 4-mer), peptides (< 9-mer), cofactors, and organic compounds. The corresponding binding site is formed by all protein residues (including amino acids, cofactors, and important metal ions) with at least one atom within 6.5 angstroms of any ligand atom. The database was carefully annotated by browsing several protein databases (PDB, UniProt, and GO) and storing, for every sc-PDB entry, the following features: protein name, function, source, domain and mutations, ligand name, and structure. The repository of ligands has also been archived by diversity analysis of molecular scaffolds, and several chemoinformatics descriptors were computed to better understand the chemical space covered by stored ligands. The sc-PDB may be used for several purposes: (i) screening a collection of binding sites for predicting the most likely target(s) of any ligand, (ii) analyzing the molecular similarity between different cavities, and (iii) deriving rules that describe the relationship between ligand pharmacophoric points and active-site properties. The database is periodically updated and accessible on the web at http://bioinfo-pharma.u-strasbg.fr/scPDB/.

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Year:  2006        PMID: 16563002     DOI: 10.1021/ci050372x

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  59 in total

1.  Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

Authors:  Albert R Cunningham; C Alex Carrasquer; Shahid Qamar; Jon M Maguire; Suzanne L Cunningham; John O Trent
Journal:  Carcinogenesis       Date:  2012-06-07       Impact factor: 4.944

2.  PDB ligand conformational energies calculated quantum-mechanically.

Authors:  Markus Sitzmann; Iwona E Weidlich; Igor V Filippov; Chenzhong Liao; Megan L Peach; Wolf-Dietrich Ihlenfeldt; Rajeshri G Karki; Yulia V Borodina; Raul E Cachau; Marc C Nicklaus
Journal:  J Chem Inf Model       Date:  2012-02-21       Impact factor: 4.956

Review 3.  A cheminformatic toolkit for mining biomedical knowledge.

Authors:  Gus R Rosania; Gordon Crippen; Peter Woolf; David States; Kerby Shedden
Journal:  Pharm Res       Date:  2007-03-24       Impact factor: 4.200

Review 4.  In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling.

Authors:  S Ekins; J Mestres; B Testa
Journal:  Br J Pharmacol       Date:  2007-06-04       Impact factor: 8.739

Review 5.  Chemogenomic approaches to rational drug design.

Authors:  D Rognan
Journal:  Br J Pharmacol       Date:  2007-05-29       Impact factor: 8.739

6.  Lessons for fragment library design: analysis of output from multiple screening campaigns.

Authors:  I-Jen Chen; Roderick E Hubbard
Journal:  J Comput Aided Mol Des       Date:  2009-06-03       Impact factor: 3.686

7.  Automated identification of binding sites for phosphorylated ligands in protein structures.

Authors:  Dario Ghersi; Roberto Sanchez
Journal:  Proteins       Date:  2012-07-07

8.  A benchmark driven guide to binding site comparison: An exhaustive evaluation using tailor-made data sets (ProSPECCTs).

Authors:  Christiane Ehrt; Tobias Brinkjost; Oliver Koch
Journal:  PLoS Comput Biol       Date:  2018-11-08       Impact factor: 4.475

9.  Ligand-binding site prediction of proteins based on known fragment-fragment interactions.

Authors:  Kota Kasahara; Kengo Kinoshita; Toshihisa Takagi
Journal:  Bioinformatics       Date:  2010-05-13       Impact factor: 6.937

Review 10.  The chemical basis of pharmacology.

Authors:  Michael J Keiser; John J Irwin; Brian K Shoichet
Journal:  Biochemistry       Date:  2010-11-12       Impact factor: 3.162

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