Protein−Ligand CH−π Interactions: Structural Informatics, Energy Function Development, and Docking Implementation

Description:

Here,we develop an empirical energy function based on quantum mechanical data for the interaction between methane and benzene that captures the contribution from CH−π interactions. Such interactions are frequently observed in protein−ligand crystal structures, particularly for carbohydrate ligands, but have been hard to quantify due to the absence of a model for CH−π interactions in typical molecularmechanical force fields or docking scoring functions.The CH−π term was added to the AutoDockVina (AD VINA) scoring function enabling its performance to be evaluated against a cohort of more than 1600 occurrences in 496 experimental structures of protein−ligand complexes.By employing a conformational grid search algorithm, inclusionof the CH−π term was shown to improve the prediction of the preferred orientation of flexible ligands in protein-binding sites and to enhance the detection of carbohydrate-binding sites that display CH−π interactions. Last but not least,this term was also shown to improve docking performance for the CASF-2016 benchmark set and a carbohydrate set.

Publications:

• Yao Xiao, Robert J. Woods; Protein−LigandCH−πInteractions:StructuralInformatics,EnergyFunctionDevelopment,and DockingImplementation; Journal of Chemical Theory and Computation, 2023

Tags:

Aromatic compounds Atomistic simulation Chemical structure Interaction energies Ligands Mathematical methods

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