M
Mutasem O. Taha
Researcher at University of Jordan
Publications - 167
Citations - 3542
Mutasem O. Taha is an academic researcher from University of Jordan. The author has contributed to research in topics: Pharmacophore & Quantitative structure–activity relationship. The author has an hindex of 30, co-authored 152 publications receiving 2806 citations. Previous affiliations of Mutasem O. Taha include Loughborough University & Applied Science Private University.
Papers
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Elaborate ligand-based modeling reveals new human neutrophil elastase inhibitors
TL;DR: A drug discovery workflow was applied to unveil novel inhibitory HNE leads via combining pharmacophore modeling, quantitative structure–activity relationship (QSAR) analysis, and in silico screening to screen the National Cancer Institute list of compounds.
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Ligand-based pharmacophore exploration and QSAR analysis of transition state analogues followed by in silico screening guide the discovery of new sub-micromolar β-secreatase inhibitors
Afaf H. Al-Nadaf,Mutasem O. Taha +1 more
TL;DR: Two pharmacophoric models were validated via receiver-operating characteristic curve analysis and were found to exhibit excellent abilities in discerning active compounds from decoys and two novel inhibitors of nanomolar and low micromolar IC50 values were yielded.
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Discovery of new PKN2 inhibitory chemotypes via QSAR-guided selection of docking-based pharmacophores
TL;DR: Pharmacological assays showed promising cytotoxic properties for active hits in MTT and wound healing assays against MCF-7 and PANC-1 cancer cells and the optimal pharmacophore was sterically-refined and used as virtual search query to screen the National Cancer Institute database for new promising anti-PKN2 leads of novel chemotypes.
QSAR studies in the discovery of novel type-II
Areej Abuhammad,Mutasem O. Taha +1 more
TL;DR: In this paper, a review of quantitative structure-activity relationship (QSAR) strategies used to model antidiabetic agents is presented, focusing on drug targets that raised recent scientific interest and/or led to successful antiabetic agents in the market.
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Discovery of new selective cytotoxic agents against Bcl-2 expressing cancer cells using ligand-based modeling.
TL;DR: An elaborated ligand-based computational workflow that combines exhaustive pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis to explore the structural features required for potent Bcl-2 inhibitors employing 98 known Bcl -2 inhibitors.