title: Best Matching Protein Conformations and Docking Programs for a Virtual Screening Campaign Against SMO Receptor.
abstract: SMO receptor is one of the main components of the Hedgehog biochemical pathway. In the last decades compelling body of evidence demonstrated that this receptor is a pertinent target for the treatment of various types of solid tumors. Recently, the X-ray determination of the three-dimensional structure of SMO in complex with different antagonists opened up the way for the structure-based design of new antagonists for this receptor that could possibly overcome the limitations connected with the induction of acquired tumor resistance. Herein, taking advantage of three different docking software (namely Glide, PLANTS, and Vina) and of the available SMO structures we set up a retrospective virtual screening (VS) protocol. A database, made up by known SMO antagonists and compounds with no alleged activity against the receptor was created and screened against the different SMO structures. To evaluate the performance of the ranking in VS calculations different statistical metrics (EF, AUAC and BEDROC) were employed allowing to identify the best performing VS docking protocol. Results of these studies will serve as a platform for the application of structure-based VS against the pharmaceutically relevant SMO receptor.
authors.affiliation: DiSTABiF, Seconda Università degli Studi di Napoli, Via Vivaldi 43, 81100, Caserta, Italy.
authors.forename: Giorgio
authors.initials: G
authors.lastname: Amendola
authors.affiliation: Istituto Nazionale di Fisica Nucleare (INFN), sezione di Pisa, Largo Bruno Pontecorvo 3, 56127, Pisa, Italy.|Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126, Pisa, Italy.
authors.forename: Danilo
authors.initials: D
authors.lastname: Di Maio
authors.affiliation: Dipartimento di Farmacia, Università di Napoli "Federico II", Via D. Montesano 49, 80131 Naples, Italy.
authors.forename: Valeria
authors.initials: V
authors.lastname: La Pietra
authors.affiliation: DiSTABiF, Seconda Università degli Studi di Napoli, Via Vivaldi 43, 81100, Caserta, Italy . sandro.cosconati@unina2.it.
authors.forename: Sandro
authors.initials: S
authors.lastname: Cosconati
mesh_terms: D000465:Algorithms; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D062105:Molecular Docking Simulation / Q000379:methods; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011485:Protein Binding / Q000502:physiology; D011487:Protein Conformation; D012189:Retrospective Studies; D000072086:Smoothened Receptor / Q000037:antagonists & inhibitors*; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D008024:Ligands; D004364:Pharmaceutical Preparations; C491023:SMO protein, human; D000072086:Smoothened Receptor
keywords: Glide; PLANTS; SMO; Vina; docking; enrichment factor; virtual screening