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Iterative experimental and virtual high-throughput screening identifies metabotropic glutamate receptor subtype 4 positive allosteric modulators

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Abstract

Activation of metabotropic glutamate receptor subtype 4 has been shown to be efficacious in rodent models of Parkinson’s disease. Artificial neural networks were trained based on a recently reported high throughput screen which identified 434 positive allosteric modulators of metabotropic glutamate receptor subtype 4 out of a set of approximately 155,000 compounds. A jury system containing three artificial neural networks achieved a theoretical enrichment of 15.4 when selecting the top 2 % compounds of an independent test dataset. The model was used to screen an external commercial database of approximately 450,000 drug-like compounds. 1,100 predicted active small molecules were tested experimentally using two distinct assays of mGlu4 activity. This experiment yielded 67 positive allosteric modulators of metabotropic glutamate receptor subtype 4 that confirmed in both experimental systems. Compared to the 0.3 % active compounds in the primary screen, this constituted an enrichment of 22 fold.

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Mueller, R., Dawson, E.S., Niswender, C.M. et al. Iterative experimental and virtual high-throughput screening identifies metabotropic glutamate receptor subtype 4 positive allosteric modulators. J Mol Model 18, 4437–4446 (2012). https://doi.org/10.1007/s00894-012-1441-0

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  • DOI: https://doi.org/10.1007/s00894-012-1441-0

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