Adaptive sampling-based structural prediction reveals opening of a GABAA receptor through the αβ interface

GABAA receptors are ligand-gated ion channels in the central nervous system with largely inhibitory function. Despite being a target for drugs including general anesthetics and benzodiazepines, experimental structures have yet to capture an open state of canonical 1{beta}2{gamma}2 GABAA receptors. Here, we use a goal-oriented adaptive sampling strategy in molecular dynamics simulations followed by Markov state modeling to capture an energetically stable putative open state of the receptor. The model conducts chloride ions with comparable conductance as in electrophysiology measurements. The channel desensitizes by narrowing at both the cytoplasmic (-2') and central (9') gates, a motion primarily mediated by transmembrane {beta} subunit interface. Consistent with previous experiments, targeted substitutions disrupting interactions at this interface slowed the open-to-desensitized transition rate. This work demonstrates the capacity of advanced simulation techniques to investigate a computationally and experimentally plausible functionally critical of a complex membrane protein, yet to be resolved by experimental methods.