Abstract

Two QSAR approaches were applied to assist the design and to prioritise the synthesis of new active mGlu2 receptor positive allosteric modulators (PAMs). With the aim to explore a particular point of substitution the models successfully prioritised molecules originating from chemistry ideas and a large virtual library. The two methods, 3D topomer CoMFA and support vector machines with 2D ECFP6 fingerprints, delivered good correlation and success in this prospective application. Fourteen molecules with different substituent decoration were identified by the in silico models and synthesised. They were found to be highly active and their mGlu2 receptor PAM activity (pEC50) was predicted within 0.3 and 0.4log units of error with the two methods. The value of the molecules and the models for the future of the project is discussed.

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