1. Discovery of a Novel Class of d-Amino Acid Oxidase Inhibitors Using the Schrödinger Computational Platform.
- Author
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Tang H, Jensen K, Houang E, McRobb FM, Bhat S, Svensson M, Bochevarov A, Day T, Dahlgren MK, Bell JA, Frye L, Skene RJ, Lewis JH, Osborne JD, Tierney JP, Gordon JA, Palomero MA, Gallati C, Chapman RSL, Jones DR, Hirst KL, Sephton M, Chauhan A, Sharpe A, Tardia P, Dechaux EA, Taylor A, Waddell RD, Valentine A, Janssens HB, Aziz O, Bloomfield DE, Ladha S, Fraser IJ, and Ellard JM
- Subjects
- D-Amino-Acid Oxidase metabolism, Humans, Receptors, N-Methyl-D-Aspartate metabolism, Serine metabolism, Structure-Activity Relationship, N-Methylaspartate, Schizophrenia
- Abstract
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.
- Published
- 2022
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