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On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction

[Image: see text] Recent work showed that active site rather than full-protein-sequence information improves predictive performance in kinase-ligand binding affinity prediction. To refine the notion of an “active site”, we here propose and compare multiple definitions. We report significant evidence...

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Detalles Bibliográficos
Autores principales: Born, Jannis, Shoshan, Yoel, Huynh, Tien, Cornell, Wendy D., Martin, Eric J., Manica, Matteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516689/
https://www.ncbi.nlm.nih.gov/pubmed/36098536
http://dx.doi.org/10.1021/acs.jcim.2c00840
Descripción
Sumario:[Image: see text] Recent work showed that active site rather than full-protein-sequence information improves predictive performance in kinase-ligand binding affinity prediction. To refine the notion of an “active site”, we here propose and compare multiple definitions. We report significant evidence that our novel definition is superior to previous definitions and better models of ATP-noncompetitive inhibitors. Moreover, we leverage the discontiguity of the active site sequence to motivate novel protein-sequence augmentation strategies and find that combining them further improves performance.