Machine Learned Classification of Ligand Intrinsic Activities at Human <i>μ</i>-Opioid Receptor.

ABSTRACT: Opioids are small-molecule agonists of μ-opioid receptor (μOR), while reversal agents such as naloxone are antagonists of μOR. Here we developed machine learning (ML) models to classify the intrinsic activities of ligands at the human μOR based on the SMILE strings and two-dimensional molecular descriptors. We first manually curated a database of 983 small molecules with measured E _max values at the human μOR. Analysis of the chemical space allowed identification of dominant scaffolds and structurally similar agonists and antagonists. Decision tree models and directed message passing neural networks (MPNNs) were then trained to classify agonistic and antagonistic ligands. The hold-out test AUCs (areas under the receiver operator curves)

SUBMITTER: Oh M 

PROVIDER: S-EPMC11030315 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature