Discovery of a Novel Class of d-Amino Acid Oxidase Inhibitors Using the Schrödinger Computational Platform.

d-Serine is a coagonist of the N-methyl d-aspartate (NMDA) receptor, a key excitatory neurotransmitter receptor. In the brain, d-serine is synthesized from its l-isomer by serine racemase and is metabolized by the D-amino acid oxidase (DAO, DAAO). Many studies have linked decreased d-serine concentration and/or increased DAO expression and enzyme activity to NMDA dysfunction and schizophrenia. Thus, it is feasible to employ DAO inhibitors for the treatment of schizophrenia and other indications. Powered by the Schrödinger computational modeling platform, we initiated a research program to identify novel DAO inhibitors with the best-in-class properties. The program execution leveraged an hDAO FEP+ model to prospectively predict compound potency. A new class of DAO inhibitors with desirable properties has been discovered from this endeavor. Our modeling technology on this program has not only enhanced the efficiency of structure-activity relationship development but also helped to identify a previously unexplored subpocket for further optimization.

Identification and optimisation of a series of tetrahydrobenzotriazoles as metabotropic glutamate receptor 5-selective positive allosteric modulators that improve performance in a preclinical model of cognition.

Herein we describe a series of tetrahydrobenzotriazoles as novel, potent metabotropic glutamate receptor subtype 5 (mGlu5) positive allosteric modulators (PAMs). Exploration of the SAR surrounding the tetrahydrobenzotriazole core ultimately led to the identification of 29 as a potent mGlu5 PAM with a low maximal glutamate potency fold shift, acceptable in vitro DMPK parameters and in vivo PK profile and efficacy in the rat novel object recognition (NOR) assay. As a result 29 was identified as a suitable compound for progression to in vivo safety evaluation.