Steered Molecular Dynamics Simulations Predict Conformational Stability of Glutamate Receptors.

Abstract

The stability of protein-protein interfaces can be essential for protein function. For ionotropic glutamate receptors, a family of ligand-gated ion channels vital for normal function of the central nervous system, such an interface exists between the extracellular ligand binding domains (LBDs). In the full-length protein, the LBDs are arranged as a dimer of dimers. Agonist binding to the LBDs opens the ion channel, and briefly after activation the receptor desensitizes. Several residues at the LBD dimer interface are known to modulate desensitization, and conformational changes around these residues are believed to be involved in the state transition. The general hypothesis is that the interface is disrupted upon desensitization, and structural evidence suggests that the disruption might be substantial. However, when cross-linking the central part of this interface, functional data suggest that the receptor can still undergo desensitization, contradicting the hypothesis of major interface disruption. Here, we illustrate how opening the dimer interface using steered molecular dynamics (SMD) simulations, and analyzing the work values required, provides a quantitative measure for interface stability. For one subtype of glutamate receptors, which is regulated by ion binding to the dimer interface, we show that opening the interface without ions bound requires less work than with ions present, suggesting that ion binding indeed stabilizes the interface. Likewise, for interface mutants with longer-lived active states, the interface is more stable, while the work required to open the interface is reduced for less active mutants. Moreover, a cross-linked mutant can still undergo initial interface opening motions similar to the native receptor and at similar energetic cost. Thus, our results support that interface opening is involved in desensitization. Furthermore, they provide reconciliation of apparently opposing data and demonstrate that SMD simulations can give relevant biological insight into longer time scale processes without the need for expensive calculations.