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Receptors, Adrenergic, beta-2

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Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7).

Journal of chemical information and modeling
Molecular docking, despite its undeniable usefulness in computer-aided drug design protocols and the increasing sophistication of tools used in the prediction of ligand-protein interaction energies, is still connected with a problem of effective resu...

Combined docking and machine learning identify key molecular determinants of ligand pharmacological activity on β2 adrenoceptor.

Pharmacology research & perspectives
G protein-coupled receptors (GPCRs) are valuable therapeutic targets for many diseases. A central question of GPCR drug discovery is to understand what determines the agonism or antagonism of ligands that bind them. Ligands exert their action via the...

A Study on the Robustness and Stability of Explainable Deep Learning in an Imbalanced Setting: The Exploration of the Conformational Space of G Protein-Coupled Receptors.

International journal of molecular sciences
G-protein coupled receptors (GPCRs) are transmembrane proteins that transmit signals from the extracellular environment to the inside of the cells. Their ability to adopt various conformational states, which influence their function, makes them cruci...

Integrative residue-intuitive machine learning and MD Approach to Unveil Allosteric Site and Mechanism for β2AR.

Nature communications
Allosteric drugs offer a new avenue for modern drug design. However, the identification of cryptic allosteric sites presents a formidable challenge. Following the allostery nature of residue-driven conformation transition, we propose a state-of-the-a...