Metabotropic glutamate receptors (mGLuRs) are attractive targets for the development of therapeutics for a diversity of neurological and neuropsychiatric conditions, such as chronic pain, epilepsy, neurodegenerative disorders, addiction disorders, and anxiety. Previous bioinformatic analyses have shown that they have a considerable similarity with taste receptors such as umami and sweet taste receptors, suggesting that relationships between taste and potential pharmacological activity may be established. Here, we have developed and validated classifiers and meta-classifiers capable of identifying mGluR subtype 1 (mGluR1) positive allosteric modulators. The resulting models have been validated via retrospective virtual screening campaigns, with excellent average and early enrichment metrics (area under the Receiver Operating Characteristic curve ≈ 0.99 and BEDROC, α = 100, > 0.90), and later applied in prospective virtual screening experiments.