AlphaFold accelerates discovery of potential antipsychotic drugs by outperforming traditional methods

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AlphaFold accelerates discovery of potential antipsychotic drugs by outperforming traditional methods

AlphaFold, a machine learning method, has revolutionized protein structure prediction and drug design by outperforming traditional methods in identifying potential antipsychotic drugs. Researchers in Sweden utilized AlphaFold models to screen over 16 million compounds and discovered potent TAAR1 agonists for treating neuropsychiatric conditions.

The study compared AlphaFold to homology modeling techniques in virtual screening and found that AlphaFold had a higher hit rate and accuracy in predicting protein-ligand interactions. Compound 65, identified through AlphaFold modeling, showed promising antipsychotic effects and favorable pharmacokinetic properties.

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