AUTHOR=Liu Yunsheng , Shao Da , Lou Shulei , Kou Zengwei 

TITLE=Structural prediction of GluN3 NMDA receptors

JOURNAL=Frontiers in Physiology

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2024.1446459

DOI=10.3389/fphys.2024.1446459

ISSN=1664-042X

ABSTRACT=NMDA receptors are heterotetrametric ion channels composed of two obligatory GluN1 subunits and two alternative GluN2 or GluN3 subunits, forming GluN1-N2, GluN1-N3, and GluN1-N2-N3 type of NMDA receptors. Extensive research has focused on the functional and structural properties of conventional GluN1-GluN2 NMDA receptors due to their early discovery and high expression levels. However, the knowledge of unconventional GluN1-N3 NMDA receptors remains limited. In this study, we modeled the GluN1-N3A, GluN1-N3B, and GluN1-N3A-N3A NMDA receptors using deep-learned protein-language predication algorithm AlphaFold and RoseTTAFold All-Atom. We then compared these structures with GluN1-N2 and GluN1-N3A receptor cryo-EM structures and found GluN1-N3 receptors have distinct properties in subunit arrangement, domain swap, and domain interaction. Furthermore, we predicted the agonist-or antagonist-bound structures, highlighting the key molecular-residue interactions. Our findings shed new light on the structural and functional diversity of NMDA receptors and provides new direction for drug development.