Showing papers by "Mutasem O. Taha published in 2008"

Pharmacophore modeling, quantitative structure-activity relationship analysis, and in silico screening reveal potent glycogen synthase kinase-3beta inhibitory activities for cimetidine, hydroxychloroquine, and gemifloxacin

Abstract: The pharmacophoric space of glycogen synthase kinase-3beta (GSK-3beta) was explored using two diverse sets of inhibitors. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combination of pharmacophores and physicochemical descriptors that access self-consistent and predictive quantitative structure-activity relationship (QSAR) against 132 training compounds ( r (2) 123 = 0.663, F = 24.6, r (2) LOO = 0.592, r (2) PRESS against 29 external test inhibitors = 0.695). Two orthogonal pharmacophores emerged in the QSAR, suggesting the existence of at least two distinct binding modes accessible to ligands within GSK-3beta binding pocket. The validity of the QSAR equation and the associated pharmacophores was established by the identification of three nanomolar GSK-3beta inhibitors retrieved from our in-house-built structural database of established drugs, namely, hydroxychloroquine, cimetidine, and gemifloxacin. Docking studies supported the binding modes suggested by the pharmacophore/QSAR analysis. In addition to being excellent leads for subsequent optimization, the anti-GSK-3beta activities of these drugs should have significant clinical implications.

Combining ligand-based pharmacophore modeling, quantitative structure-activity relationship analysis and in silico screening for the discovery of new potent hormone sensitive lipase inhibitors.

Abstract: Hormone sensitive lipase (HSL) has been recently implicated in diabetes and obesity, prompting attempts to discover new HSL inhibitors. Toward this end, we explored the pharmacophoric space of HSL inhibitors using four diverse sets of compounds. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of yielding a self-consistent and predictive quantitative structure−activity relationship (QSAR) (r = 0.822, n = 99, F = 11.1, rLOO2 = 0.521, rPRESS2 against 23 external test inhibitors = 0.522). Interestingly, two pharmacophoric models emerged in the QSAR equation suggesting at least two binding modes. These pharmacophores were employed to screen the National Cancer Institute (NCI) list of compounds and our in-house built database of established drugs and agrochemicals. Active hits included the safe herbicidal agent bifenox (IC50 = 0.43 μM) and the nonsteroidal anti-inflammatory nap...

Discovery of DPP IV inhibitors by pharmacophore modeling and QSAR analysis followed by in silico screening.

Abstract: Dipeptidyl peptidase IV (DPP IV) deactivates the natural hypoglycemic incretin hormones. Inhibition of this enzyme should restore glucose homeostasis in diabetic patients making it an attractive target for the development of new antidiabetic drugs. With this in mind, the pharmacophoric space of DPP IV was explored using a set of 358 known inhibitors. Thereafter, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that yield selfconsistent and predictive quantitative structure-activity relationships (QSAR) (r(2) (287)=0.74, F-statistic=44.5, r(2) (BS)=0.74, r(2) (LOO)=0.69, r(2) (PRESS) against 71 external testing inhibitors=0.51). Two orthogonal pharmacophores (of cross-correlation r(2)=0.23) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within the DPP IV binding pocket. Docking experiments supported the binding modes suggested by QSAR/pharmacophore analyses. The validity of the QSAR equation and the associated pharmacophore models were established by the identification of new low-micromolar anti-DPP IV leads retrieved by in silico screening. One of our interesting potent anti-DPP IV hits is the fluoroquinolone gemifloxacin (IC(50)=1.12 muM). The fact that gemifloxacin was recently reported to potently inhibit the prodiabetic target glycogen synthase kinase 3beta (GSK-3beta) suggests that gemifloxacin is an excellent lead for the development of novel dual antidiabetic inhibitors against DPP IV and GSK-3beta.

Development of predictive in silico model for cyclosporine- and aureobasidin-based P-glycoprotein inhibitors employing receptor surface analysis

Abstract: P-glycoprotein (Pgp) is implicated in multiple drug resistance (MDR) exhibited by several types of cancer against a multitude of anticancer chemotherapeutic agents. This problem prompted several research groups to search for effective P-gp inhibitors. Cyclosporine A (CsA), aureobasidin A (AbA) and related analogues were reported to possess potent inhibitory actions against Pgp. In this work we employed receptor surface analysis (RSA) to construct two satisfactory receptor surface models (RSMs) for cyclosporine- and aureobasidin-based Pgp inhibitors. These pseudoreceptors were combined to achieve satisfactory three-dimensional quantitative structure activity relationship (3D-QSAR) for 68 different cyclosporine and aureobasidin derivatives. Upon validation against an external set of 16 randomly selected Pgp inhibitors, the optimal 3D-QSAR was found to be self-consistent and predictive (r(LOO)(2)=0.673, r(PRESS)(2)=0.600). The resulting 3D-QSAR was employed to probe the structural factors that control the inhibitory activities of cyclosporine and aureobasidin analogues against Pgp.