Three-dimensional quantitative structure-activity relationship analysis of human CYP51 inhibitors

被引:18
|
作者
Ekins, Sean [1 ]
Mankowski, Dayna C. [1 ]
Hoover, Dennis J. [1 ]
Lawton, Michael P. [1 ]
Treadway, Judith L. [1 ]
Harwood, H. James, Jr. [1 ]
机构
[1] Groton Labs, Pfizer Global Res & Dev, Groton, CT USA
关键词
D O I
10.1124/dmd.106.013888
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
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 14 alpha-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 M 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.
引用
收藏
页码:493 / 500
页数:8
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