Virtual Lead Identification of Farnesyltransferase Inhibitors Based on Ligand and Structure-Based Pharmacophore Techniques

Abstract

Farnesyltransferase enzyme (FTase) is considered an essential enzyme in the Ras signaling pathway associated with cancer. Thus, designing inhibitors for this enzyme might lead to the discovery of compounds with effective anticancer activity. In an attempt to obtain effective FTase inhibitors, pharmacophore hypotheses were generated using structure-based and ligand-based approaches built in Discovery Studio v3.1. Knowing the presence of the zinc feature is essential for inhibitor’s binding to the active site of FTase enzyme; further customization was applied to include this feature in the generated pharmacophore hypotheses. These pharmacophore hypotheses were thoroughly validated using various procedures such as ROC analysis and ligand pharmacophore mapping. The validated pharmacophore hypotheses were used to screen 3D databases to identify possible hits. Those which were both high ranked and showed sufficient ability to bind the zinc feature in active site, were further refined by applying drug-like criteria such as Lipiniski’s “rule of five” and ADMET filters. Finally, the two candidate compounds (ZINC39323901 and ZINC01034774) were allowed to dock using CDOCKER and GOLD in the active site of FTase enzyme to optimize hit selection.

Keywords

• common feature pharmacophore
• structure-based pharmacophore
• zinc binding group
• database screening
• CDOCKER
• GOLD