PT  - JOURNAL ARTICLE
AU  - Ekins, Sean
AU  - Mankowski, Dayna C.
AU  - Hoover, Dennis J.
AU  - Lawton, Michael P.
AU  - Treadway, Judith L.
AU  - Harwood, H. James
TI  - Three-Dimensional Quantitative Structure-Activity Relationship Analysis of Human CYP51 Inhibitors
AID  - 10.1124/dmd.106.013888
DP  - 2007 Mar 01
TA  - Drug Metabolism and Disposition
PG  - 493--500
VI  - 35
IP  - 3
4099  - http://dmd.aspetjournals.org/content/35/3/493.short
4100  - http://dmd.aspetjournals.org/content/35/3/493.full
SO  - Drug Metab Dispos2007 Mar 01; 35
AB  - 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 14α-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 IC50 values (r = 0.92). Validation of this pharmacophore was performed by predicting the IC50 of a test set of commercially available (n = 19) and CP-320626-related (n = 48) CYP51 inhibitors. Using predictions below 10 μM 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 Cerius2 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. The American Society for Pharmacology and Experimental Therapeutics