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

[Image: see text] 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 car...

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Detalles Bibliográficos
Autores principales: Xiao, Yao, Woods, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448718/
https://www.ncbi.nlm.nih.gov/pubmed/37493980
http://dx.doi.org/10.1021/acs.jctc.3c00300
Descripción
Sumario:[Image: see text] 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 molecular mechanical force fields or docking scoring functions. The CH−π term was added to the AutoDock Vina (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, inclusion of 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.