title: Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors.
abstract: A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-alpha converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.
authors.affiliation: Pharmacy Department, Faculty of Technology and Engineering, The M. S. University of Baroda, Vadodara, Gujarat, 390 001, India.
authors.forename: Prashant Revan
authors.initials: PR
authors.lastname: Murumkar
authors.forename: Vishal Prakash
authors.initials: VP
authors.lastname: Zambre
authors.forename: Mange Ram
authors.initials: MR
authors.lastname: Yadav
mesh_terms: D051722:ADAM Proteins / Q000037:antagonists & inhibitors*; D000072198:ADAM17 Protein; D001665:Binding Sites / Q000187:drug effects; D015195:Drug Design; D008956:Models, Chemical; D008958:Models, Molecular; D011480:Protease Inhibitors / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D054852:Small Molecule Libraries / Q000138:chemical synthesis; D055672:Static Electricity
chemical_list: D011480:Protease Inhibitors; D054852:Small Molecule Libraries; D051722:ADAM Proteins; D000072198:ADAM17 Protein