tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking

A critical step in structure-based drug discovery is predicting whether and how a candidate molecule binds to a model of a therapeutic target. However, substantial protein side chain movements prevent current screening methods, such as docking, from accurately predicting the ligand conformations and...

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Veröffentlicht in:	Journal of chemical information and modeling 2023-06, Vol.63 (11), p.3438-3447
Hauptverfasser:	Hsu, Darren J., Davidson, Russell B., Sedova, Ada, Glaser, Jens
Format:	Artikel
Sprache:	eng
Schlagworte:	Computational Biochemistry computer simulations COVID-19 Docking genetics Humans INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY Learning Ligands Molecular Docking Simulation Molecular Dynamics Simulation Protease inhibitors Protease Inhibitors - chemistry protein structure Proteins receptors SARS-CoV-2 Workflow
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