Pharmacophore Modeling, Quantitative Structure-Activity Relationship Analysis, and Shape-Complemented in Silico Screening Allow Access to Novel Influenza Neuraminidase Inhibitors. - Areej M. Abu Hammad; Mutasem O. Taha (J. Chem. Inf. Model., 2009)

Elaborate Ligand-Based Modeling Reveals New Nanomolar Heat Shock Protein 90α Inhibitors. - Mahmoud A. Al-Sha'er; Mutasem O. Taha (J. Chem. Inf. Model., 2010)

Discovery of new beta-D-galactosidase inhibitors via pharmacophore modeling and QSAR analysis followed by in silico screening. - Ahmed Mutanabbi Abdula; Reema Abu Khalaf; Mohammad S. Mubarak; Mutasem O. Taha (J. Comput. Chem., 2011)

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. - Mutasem O. Taha; Maha Habash; Zeina Al-Hadidi; Amal Al-Bakri; Khaled Younis; Suhaib Sisan (J. Chem. Inf. Model., 2011)

Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors. - Rand Shahin; Saja AlQtaishat; Mutasem O. Taha (J. Comput. Aided Mol. Des., 2012)

Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors. - Sawsan Abuhamdah; Maha Habash; Mutasem O. Taha (J. Comput. Aided Mol. Des., 2013)

Elaborate Ligand-Based Modeling Coupled with Multiple Linear Regression and k Nearest Neighbor QSAR Analyses Unveiled New Nanomolar mTOR Inhibitors. - Mohammad A. Khanfar; Mutasem O. Taha (J. Chem. Inf. Model., 2013)

The use of docking-based comparative intermolecular contacts analysis to identify optimal docking conditions within glucokinase and to discover of new GK activators. - Mutasem O. Taha; Maha Habash; Mohammad A. Khanfar (J. Comput. Aided Mol. Des., 2014)

Combining docking-based comparative intermolecular contacts analysis and k-nearest neighbor correlation for the discovery of new check point kinase 1 inhibitors. - Nour Jamal Jaradat; Mohammad A. Khanfar; Maha Habash; Mutasem Omar Taha (J. Comput. Aided Mol. Des., 2015)

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. - Mámon M. Hatmal; Shadi Jaber; Mutasem O. Taha (J. Comput. Aided Mol. Des., 2016)

Ligand-based computational modelling of platelet-derived growth factor beta receptor leading to new angiogenesis inhibitory leads. - Rua'a A. Al-Aqtash; Malek A. Zihlif; Hana Hammad; Zeyad D. Nassar; Jehad Al Meliti; Mutasem O. Taha (Comput. Biol. Chem., 2017)

Discovery of new Gyrase β inhibitors via structure based modeling. - Afaf H. Al-Nadaf; Sajeda A. Salah; Mutasem O. Taha (Comput. Biol. Chem., 2018)

Combining Stochastic Deformation/Relaxation and Intermolecular Contacts Analysis for Extracting Pharmacophores from Ligand-Receptor Complexes. - Mámon M. Hatmal; Mutasem O. Taha (J. Chem. Inf. Model., 2018)

Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study. - Lubabah A. Mousa; Mámon M. Hatmal; Mutasem O. Taha (J. Comput. Aided Mol. Des., 2022)

Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study. - Nour Jamal Jaradat; Mámon M. Hatmal; Dana Alqudah; Mutasem Omar Taha (J. Comput. Aided Mol. Des., 2023)

Correction to: Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study. - Nour Jamal Jaradat; Mámon M. Hatmal; Dana Alqudah; Mutasem Omar Taha (J. Comput. Aided Mol. Des., 2023)