Predicting the duration of action of β2-adrenergic receptor agonists: ligand and structure-based approaches.
Fiche publication
Date publication
octobre 2023
Journal
Molecular informatics
Auteurs
Membres identifiés du Cancéropôle Est :
Dr SICK Emilie
Tous les auteurs :
Kellenberger E, Chiesa L, Sick E
Lien Pubmed
Résumé
Agonists of the β2 adrenergic receptor (ADRB2) are an important class of medications used for the treatment of respiratory diseases. They can be classified as short acting (SABA) or long acting (LABA), with each class playing a different role in patient management. In this work we explored both ligand-based and structure-based high-throughput approaches to classify β2-agonists based on their duration of action. A completely in-silico prediction pipeline using an AlphaFold generated structure was used for structure-based modelling. Our analysis identified the ligands' 3D structure and lipophilicity as the most relevant features for the prediction of the duration of action. Interaction-based methods were also able to select ligands with the desired duration of action, incorporating the bias directly in the structure-based drug discovery pipeline without the need for further processing.
Mots clés
Machine learning, Molecular dynamics, Molecular modelling
Référence
Mol Inform. 2023 10 23;: