Mutasem O. Taha

15 papers Journal 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
Computer-aided discovery of CDK16 inhibitors: a docking-augmented machine learning regression modelling approach.
J. Comput. Aided Mol. Des.
Taqwa Alfararjeh, Safa Dauod, Mámon M. Hatmal, Ahmed Adel, Mutasem O. Taha
2026 J jnl
Deep learning model for activity cliffs prediction: a comprehensive approach to protein kinase inhibitors.
J. Comput. Aided Mol. Des.
Said Elaiwat, Safa Daoud, Nour Jamal Jaradat, Mutasem O. Taha
2022 J jnl
Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study.
J. Comput. Aided Mol. Des.
Lubabah A. Mousa, Mámon M. Hatmal, Mutasem O. Taha
2018 J jnl
Combining Stochastic Deformation/Relaxation and Intermolecular Contacts Analysis for Extracting Pharmacophores from Ligand-Receptor Complexes.
J. Chem. Inf. Model.
Mámon M. Hatmal, Mutasem O. Taha
2018 J jnl
Discovery of new Gyrase β inhibitors via structure based modeling.
Comput. Biol. Chem.
Afaf H. Al-Nadaf, Sajeda A. Salah, Mutasem O. Taha
2017 J jnl
Ligand-based computational modelling of platelet-derived growth factor beta receptor leading to new angiogenesis inhibitory leads.
Comput. Biol. Chem.
Rua'a A. Al-Aqtash, Malek A. Zihlif, Hana Hammad, Zeyad D. Nassar, Jehad Al Meliti, Mutasem O. Taha
2016 J jnl
Combining molecular dynamics simulation and ligand-receptor contacts analysis as a new approach for pharmacophore modeling: beta-secretase 1 and check point kinase 1 as case studies.
J. Comput. Aided Mol. Des.
Mámon M. Hatmal, Shadi Jaber, Mutasem O. Taha
2014 J jnl
The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators.
J. Comput. Aided Mol. Des.
Mutasem O. Taha, Maha Habash, Mohammad A. Khanfar
2013 J jnl
Elaborate Ligand-Based Modeling Coupled with Multiple Linear Regression and k Nearest Neighbor QSAR Analyses Unveiled New Nanomolar mTOR Inhibitors.
J. Chem. Inf. Model.
Mohammad A. Khanfar, Mutasem O. Taha
2013 J jnl
Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors.
J. Comput. Aided Mol. Des.
Sawsan Abuhamdah, Maha Habash, Mutasem O. Taha
2012 J jnl
Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors.
J. Comput. Aided Mol. Des.
Rand Shahin, Saja AlQtaishat, Mutasem O. Taha
2011 J jnl
Discovery of new beta-D-galactosidase inhibitors via pharmacophore modeling and QSAR analysis followed by
J. Comput. Chem.
Ahmed Mutanabbi Abdula, Reema Abu Khalaf, Mohammad S. Mubarak, Mutasem O. Taha
2011 J jnl
Docking-Based Comparative Intermolecular Contacts Analysis as New 3-D QSAR Concept for Validating Docking Studies and in Silico Screening: NMT and GP Inhibitors as Case Studies.
J. Chem. Inf. Model.
Mutasem O. Taha, Maha Habash, Zeina Al-Hadidi, Amal Al-Bakri, Khaled Younis, Suhaib Sisan
2010 J jnl
Elaborate Ligand-Based Modeling Reveals New Nanomolar Heat Shock Protein 90α Inhibitors.
J. Chem. Inf. Model.
Mahmoud A. Al-Sha'er, Mutasem O. Taha
2009 J jnl
Pharmacophore Modeling, Quantitative Structure-Activity Relationship Analysis, and Shape-Complemented
J. Chem. Inf. Model.
Areej M. Abu Hammad, Mutasem O. Taha