title: Virtual screening for SARS-CoV protease based on KZ7088 pharmacophore points.
abstract: Pharmacophore modeling can provide valuable insight into ligand-receptor interactions. It can also be used in 3D (dimensional) database searching for potentially finding biologically active compounds and providing new research ideas and directions for drug-discovery projects. To stimulate the structure-based drug design against SARS (severe acute respiratory syndrome), a pharmacophore search was conducted over 3.6 millions of compounds based on the atomic coordinates of the complex obtained by docking KZ7088 (a derivative of AG7088) to SARS CoV M(pro) (coronavirus main proteinase), as reportedly recently (Chou, K. C.; Wei, D. Q.; Zhong, W. Z. Biochem. Biophys. Res. Commun. 2003, 308, 148-151). It has been found that, of the 3.6 millions of compounds screened, 0.07% are with the score satisfying five of the six pharmacophore points. Moreover, each of the hit compounds has been evaluated for druggability according to 13 metrics based on physical, chemical, and structural properties. Of the 0.07% compounds thus retrieved, 17% have a perfect score of 1.0; while 23% with one druggable rule violation, 13% two violations, and 47% more than two violations. If the criterion for druggability is set at a maximum allowance of two rule violations, we obtain that only about 0.03% of the compounds screened are worthy of further tests by experiments. These findings will significantly narrow down the search scope for potential compounds, saving substantial time and money. Finally, the featured templates derived from the current study will also be very useful for guiding the design and synthesis of effective drugs for SARS therapy.
authors.affiliation: Départment de chimie, Université du Québec à Montréal (UQAM), C.P. 8888 Succursale Centre-Ville, Montréal, Québec, Canada H3C 3P8.
authors.forename: Suzanne
authors.initials: S
authors.lastname: Sirois
authors.forename: Dong-Qing
authors.initials: DQ
authors.lastname: Wei
authors.forename: Qishi
authors.initials: Q
authors.lastname: Du
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000086782:Coronavirus 3C Proteases; D018360:Crystallography, X-Ray; D003546:Cysteine Endopeptidases; D010450:Endopeptidases / Q000737:chemistry*; D006860:Hydrogen Bonding; D008958:Models, Molecular; D011487:Protein Conformation; D014764:Viral Proteins / Q000737:chemistry*
chemical_list: D014764:Viral Proteins; D010450:Endopeptidases; D003546:Cysteine Endopeptidases; D000086782:Coronavirus 3C Proteases