Researchers used AlphaFold and homology modeling to identify potent TAAR1 agonists, showing AlphaFold's superior performance in drug discovery for neuropsychiatric conditions.
By Dr. Sushama R. Chaphalkar, PhD.Reviewed by Susha Cheriyedath, M.Sc.Aug 13 2024 In a recent study published in the journal Science Advances, researchers in Sweden conducted virtual screens of over 16 million compounds using multiple receptor models developed by AlphaFold and homology modeling techniques. These models were based on different protein structures to identify trace amine-associated receptor 1 agonists for the potential treatment of various neuropsychiatric conditions.
TAAR1, a GPCR with no available experimental structure at the time of the study, was a key focus of this research because of its potential as a drug target. The researchers aimed to explore the effectiveness of AlphaFold models in structure-based virtual screening, particularly for TAAR1 agonists, and to compare these results with traditional homology modeling techniques.
Furthermore, in vivo studies were performed, which involved measuring core-body temperature in TAAR1-wild-type and TAAR1-knockout mice, pre-pulse inhibition tests, and locomotion experiments to evaluate the antipsychotic-like effects of the compounds. In addition to evaluating these physiological effects, structural comparisons were made between the AlphaFold models and newly released cryo-electron microscopy structures of TAAR1.
Drugs Agonist Compound Drug Discovery GPCR G-Protein In Vivo Ligand Machine Learning Protein Receptor Research
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