Three-dimensional quantitative structure-activity relationship analysis of human CYP51 inhibitors.
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Ekins S, Mankowski DC, Hoover DJ, Lawton MP, Treadway JL, Harwood HJ Jr
Three-dimensional quantitative structure-activity relationship analysis of human CYP51 inhibitors.
Drug Metab Dispos. 2007 Mar;35(3):493-500. Epub 2006 Dec 28.
- PubMed ID
- 17194716 [ View in PubMed]
- Abstract
CYP51 fulfills an essential requirement for all cells, by catalyzing three sequential mono-oxidations within the cholesterol biosynthesis cascade. Inhibition of fungal CYP51 is used as a therapy for treating fungal infections, whereas inhibition of human CYP51 has been considered as a pharmacological approach to treat dyslipidemia and some forms of cancer. To predict the interaction of inhibitors with the active site of human CYP51, a three-dimensional quantitative structure-activity relationship model was constructed. This pharmacophore model of the common structural features of CYP51 inhibitors was built using the program Catalyst from multiple inhibitors (n = 26) of recombinant human CYP51-mediated lanosterol 14alpha-demethylation. The pharmacophore, which consisted of one hydrophobe, one hydrogen bond acceptor, and two ring aromatic features, demonstrated a high correlation between observed and predicted IC(50) values (r = 0.92). Validation of this pharmacophore was performed by predicting the IC(50) of a test set of commercially available (n = 19) and CP-320626-related (n = 48) CYP51 inhibitors. Using predictions below 10 microM as a cutoff indicative of active inhibitors, 16 of 19 commercially available inhibitors (84%) and 38 of 48 CP-320626-related inhibitors (79.2%) were predicted correctly. To better understand how inhibitors fit into the enzyme, potent CYP51 inhibitors were used to build a Cerius(2) receptor surface model representing the volume of the active site. This study has demonstrated the potential for ligand-based computational pharmacophore modeling of human CYP51 and enables a high-throughput screening system for drug discovery and data base mining.