Investigation of Binding Characteristics of Phosphoinositide-dependent Kinase-1 (PDK1) Co-crystallized Ligands Through Virtual Pharmacophore Modeling Leading to Novel Anti-PDK1 Hits.

BACKGROUND: 3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits. OBJECTIVE: This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.5 (DS 4.5). METHODS: Accordingly, 35 crystals for PDK1 were collected and studied. Every single receptorligand interaction was validated and the significant ones were converted into their corresponding pharmacophoric features. The generated pharmacophores were scored by the Receiver Operating Characteristic (ROC) curve analysis. RESULTS: Consequently, 169 pharmacophores were generated and sorted, 11 pharmacophores acquired good ROC-AUC results of 0.8 and a selectivity value above 8. Pharmacophore 1UU3_2_01 was used in particular as a searching filter to screen NCI database because of its acceptable validity criteria and its distinctive positive ionizable feature. Several low micromolar PDK1 inhibitors were revealed. The most potent hit illustrated anti-PDK1 IC50 values of 200 nM with 70% inhibition against SW480 cell lines. CONCLUSION: Eventually, the active hits were docked inside the PDK1 binding pocket and the recognition points between the active hits and the receptor were analyzed that led to the discovery of new scaffolds as potential PDK1 inhibitors.

Combination of pharmacophore modeling and 3D-QSAR analysis of potential glyoxalase-I inhibitors as anticancer agents.

Glyoxalase system is an ubiquitous system in human cells which has been examined thoroughly for its role in different diseases. It comprises two enzymes; Glyoxalase I (Glo-I) and Glyoxalase II (Glo-II) which perform detoxifying endogenous harmful metabolites, mainly methylglyoxal (MG) into non-toxic bystanders. In silico computer Aided Drug Design approaches were used and ninety two diverse pharmacophore models were generated from eighteen Glyoxalase I crystallographic complexes. Subsequent QSAR modeling followed by ROC evaluation identified a single pharmacophore model which was able to predict the expected Glyoxalase I inhibition. Screening of the National Cancer Institute (NCI) database using the optimal pharmacophore Hypo(3VW9) identified several promising hits. Thirty eight hits were successfully predicted then ordered and evaluated in vitro. Seven hits out of the thirty eight tested compounds showed more than 50% inhibition with low micromolar IC50.