From ANNs to NAMs! Data from an experimental metabotropic glutamate receptor 5 (mGlu5) high-throughput screen (HTS) were employed to train artificial neural networks (ANNs) based on 345 confirmed negative allosteric modulators (NAMs) and 155 774 inactive compounds. This effort identified two potent mGlu5 NAMs with a unique chemotype. Optimization afforded a tool compound (shown), active in mouse models of anxiety and addiction.
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Mueller et al. (2012) studied this question.
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