Scoring Functions for Fragment-Based Drug Discovery

作者: Jui-Chih Wang , Jung-Hsin Lin

DOI: 10.1007/978-1-4939-2486-8_9

关键词:

摘要: Fragment-based drug design represents a challenge for computational because almost inevitably fragments will be weak binders to the biomolecular targets of specific disease, and performances scoring functions are usually poorer than those stronger binders. This protocol describes how predict binding modes affinities towards their partner with our refined AutoDock function incorporating quantum chemical charge model, namely, restrained electrostatic potential (RESP) model. was calibrated by robust regression analysis has been demonstrated perform well general classes protein-ligand interactions (with root-mean square error about 2.1 kcal/mol).

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