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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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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 |
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. |
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