Computationally Discovered Potentiating Role of Glycans on NMDA Receptors

Abstract

N-methyl-D-aspartate receptors (NMDARs) are glycoproteins in the brain central to learning and memory. The effects of glycosylation on the structure and dynamics of NMDARs are largely unknown. In this work, we use extensive molecular dynamics simulations of GluN1 and GluN2B ligand binding domains (LBDs) of NMDARs to investigate these effects. Our simulations predict that intra-domain interactions involving the glycan attached to residue GluN1-N440 stabilize closed-clamshell conformations of the GluN1 LBD. The glycan on GluN2B-N688 shows a similar, though weaker, effect. Based on these results, and assuming the transferability of the results of LBD simulations to the full receptor, we predict that glycans at GluN1-N440 might play a potentiator role in NMDARs. To validate this prediction, we perform electrophysiological analysis of full-length NMDARs with a glycosylation-preventing GluN1-N440Q mutation, and demonstrate an increase in the glycine EC50 value. Overall, our results suggest an intramolecular potentiating role of glycans on NMDA receptors.

N‐glycan content modulates kainate receptor functional properties

“…The N ‐glycosylation site at N440 is located in the upper lobe of the GluN1 LBD and was predicted to stabilize a closed LBD conformation (Sinitskiy et al . ) and mutation of this consensus site for glycosylation reduced NMDAR glycine affinity in functional studies. GluN1‐N440 is analogous to the GluK2‐N430 glycosylation site, which is one of three sites mutated in GluK2ΔNG.…”

“…The opposite changes in desensitization kinetics that we observed with HNK‐1 conjugation to wild‐type and GluK2ΔNG KARs suggest that HNK‐1–receptor interactions in distinct functional domains differentially influence receptor gating, and modelling studies such as those performed with NMDAR subunits would be a useful approach for understanding these interactions (Sinitskiy et al . ).…”

“…Sinitskiy et al . () predicted that polar interactions between the mannose constituents of immature glycans and a hydrophilic region of the lower LBD lobe occur only when the LBD is in a closed conformation, and these interactions reciprocally increase the likelihood of a closed LBD state. Almost all hydroxyl groups on the glycan mannose constituents interacted with the target residues on GluN1 in this model, with oligosaccharide flexibility highlighted by the lack of a single preferred structure and binding mode.…”

“…Moreover, the core oligosaccharide modelled in the study by Sinitskiy et al . (), Man 5 GlcNAc 2 , was both uncharged and predicted to be significantly smaller in mass relative to HNK‐1‐containing complex oligosaccharides, and thus HNK‐1 could possibly interact with a variety of different interaction partners on the LBD.…”

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

“…However, an empirical rule has been known in the community of specialists applying MSMs to study biomolecules, namely, that the slowest implicit timescale captured by an MSM can go up to the values on the same order of magnitude as the aggregate sampling achieved in the used MD dataset. In previous studies of specific biomolecular systems with MSMs based on MD simulations, reported longest implicit timescales turned out to be smaller than the aggregate sampling by at least one order of magnitude [5][6][7][8][9][10][11][12][13][14][15][16][17] or comparable to the aggregate sampling. [18][19][20][21][22] In this paper, we analyze several MSMs with different topologies to uncover the reasons for the above empirical rule.…”