title: Identification of binding sites and favorable ligand binding moieties by virtual screening and self-organizing map analysis.
abstract: BACKGROUND
  Identifying druggable cavities on a protein surface is a crucial step in structure based drug design. The cavities have to present suitable size and shape, as well as appropriate chemical complementarity with ligands.
  
  
  RESULTS
  We present a novel cavity prediction method that analyzes results of virtual screening of specific ligands or fragment libraries by means of Self-Organizing Maps. We demonstrate the method with two thoroughly studied proteins where it successfully identified their active sites (AS) and relevant secondary binding sites (BS). Moreover, known active ligands mapped the AS better than inactive ones. Interestingly, docking a naive fragment library brought even more insight. We then systematically applied the method to the 102 targets from the DUD-E database, where it showed a 90% identification rate of the AS among the first three consensual clusters of the SOM, and in 82% of the cases as the first one. Further analysis by chemical decomposition of the fragments improved BS prediction. Chemical substructures that are representative of the active ligands preferentially mapped in the AS.
  
  
  CONCLUSIONS
  The new approach provides valuable information both on relevant BSs and on chemical features promoting bioactivity.
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. emna.harigua@pasteur.fr.|Laboratory of Molecular Epidemiology and Experimental Pathology - LR11IPT04, Institut Pasteur de Tunis, Université Tunis el Manar - Tunisia, 13, Place Pasteur, Tunis, 1002, Tunisia. emna.harigua@pasteur.fr.|University of Carthage, Faculty of sciences of Bizerte - Tunisia, Jarzouna, 7021, Tunisia. emna.harigua@pasteur.fr.
authors.forename: Emna
authors.initials: E
authors.lastname: Harigua-Souiai
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. isidro.cortes@pasteur.fr.
authors.forename: Isidro
authors.initials: I
authors.lastname: Cortes-Ciriano
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. nathan@pasteur.fr.
authors.forename: Nathan
authors.initials: N
authors.lastname: Desdouits
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. terez@pasteur.fr.
authors.forename: Thérèse E
authors.initials: TE
authors.lastname: Malliavin
authors.affiliation: Laboratory of Molecular Epidemiology and Experimental Pathology - LR11IPT04, Institut Pasteur de Tunis, Université Tunis el Manar - Tunisia, 13, Place Pasteur, Tunis, 1002, Tunisia. ikram.guizani@pasteur.rns.tn.
authors.forename: Ikram
authors.initials: I
authors.lastname: Guizani
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. nilges@pasteur.fr.
authors.forename: Michael
authors.initials: M
authors.lastname: Nilges
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. ablondel@pasteur.fr.
authors.forename: Arnaud
authors.initials: A
authors.lastname: Blondel
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, 25, rue du Dr Roux, Paris, 75015, France. guillaume.bouvier@pasteur.fr.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Bouvier
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D015195:Drug Design; D054303:HIV Reverse Transcriptase / Q000737:chemistry / Q000378:metabolism; D008024:Ligands; D062105:Molecular Docking Simulation / Q000379:methods*; D016315:Proto-Oncogene Proteins c-abl / Q000737:chemistry / Q000378:metabolism
chemical_list: D008024:Ligands; D016315:Proto-Oncogene Proteins c-abl; C514824:reverse transcriptase, Human immunodeficiency virus 1; D054303:HIV Reverse Transcriptase