The FLEX Approach: An Alternative for Receptor-Ligand Docking and Computing Crystal Conformations

2007 ◽  
pp. 397-420
Author(s):  
Thomas Lengauer
Keyword(s):  
Ligand Docking ◽  
Receptor Ligand

scholarly journals Kinase Inhibitors Can Inhibit SARS-CoV-2 Mpro: A Theoretical Study

2020 ◽  
Author(s):  
BN Acharya
Keyword(s):  
Kinase Inhibitors ◽  
Theoretical Study ◽  
3D Qsar ◽  
Qsar Model ◽  
Randomization Test ◽  
Pharmacophore Modeling ◽  
Ligand Docking ◽  
Receptor Ligand ◽  
Test Set ◽  
Approved Drugs

This study describes screening of DrugBank library for approved drugs by pharmacophore modeling and receptor-ligand docking. A 3D-QSAR model was generated on the<br>inhibition constants (Ki AutoDock ) determined by AutoDock. This 3D-QSAR model was statistically validated by Fischer’s randomization test and further evaluated by a test set<br>comprising 75 molecules. Ki AutoDock values of 49 molecules were predicted correctly by the 3D-QSAR model. The validated 3D-QSAR model was used for screening of DrugBank library for approved molecules to identify potential molecules against novel SARS corona virus-2 (SARS-CoV-2). Ten out of 40 the shortlisted molecules were kinase inhibitors.

Modeling loop backbone flexibility in receptor-ligand docking simulations

2012 ◽  
Vol 33 (31) ◽  
pp. 2504-2515 ◽  
Author(s):  
Johannes Flick ◽  
Frank Tristram ◽  
Wolfgang Wenzel
Keyword(s):  
Ligand Docking ◽  
Backbone Flexibility ◽  
Receptor Ligand ◽  
Docking Simulations

scholarly journals Kinase Inhibitors Can Inhibit SARS-CoV-2 Mpro: A Theoretical Study

2020 ◽  
Author(s):  
BN Acharya
Keyword(s):  
Kinase Inhibitors ◽  
Theoretical Study ◽  
3D Qsar ◽  
Qsar Model ◽  
Randomization Test ◽  
Pharmacophore Modeling ◽  
Ligand Docking ◽  
Receptor Ligand ◽  
Test Set ◽  
Approved Drugs

This study describes screening of DrugBank library for approved drugs by pharmacophore modeling and receptor-ligand docking. A 3D-QSAR model was generated on the<br>inhibition constants (Ki AutoDock ) determined by AutoDock. This 3D-QSAR model was statistically validated by Fischer’s randomization test and further evaluated by a test set<br>comprising 75 molecules. Ki AutoDock values of 49 molecules were predicted correctly by the 3D-QSAR model. The validated 3D-QSAR model was used for screening of DrugBank library for approved molecules to identify potential molecules against novel SARS corona virus-2 (SARS-CoV-2). Ten out of 40 the shortlisted molecules were kinase inhibitors.

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