Activity Models of Key GPCR Families in the Central Nervous System: A Tool for Many Purposes

Shayma El-Atawneh, Amiram Goldblum

Research output: Contribution to journalArticlepeer-review

Abstract

G protein-coupled receptors (GPCRs) are targets of many drugs, of which ∼25% are indicated for central nervous system (CNS) disorders. Drug promiscuity affects their efficacy and safety profiles. Predicting the polypharmacology profile of compounds against GPCRs can thus provide a basis for producing more precise therapeutics by considering the targets and the anti-targets in that family of closely related proteins. We provide a tool for predicting the polypharmacology of compounds within prominent GPCR families in the CNS: serotonin, dopamine, histamine, muscarinic, opioid, and cannabinoid receptors. Our in-house algorithm, "iterative stochastic elimination"(ISE), produces high-quality ligand-based models for agonism and antagonism at 31 GPCRs. The ISE models correctly predict 68% of CNS drug-GPCR interactions, while the "similarity ensemble approach"predicts only 33%. The activity models correctly predict 56% of reported activities of DrugBank molecules for these CNS receptors. We conclude that the combination of interactions and activity profiles generated by screening through our models form the basis for subsequent designing and discovering novel therapeutics, either single, multitargeting, or repurposed.

Original languageEnglish
Pages (from-to)3248-3262
Number of pages15
JournalJournal of Chemical Information and Modeling
Volume63
Issue number11
DOIs
StatePublished - 12 Jun 2023

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Chemical Engineering
  • Library and Information Sciences
  • Computer Science Applications

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