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

γ-Aminobutyric acid type A (GABA) 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 classical synaptic α1β2γ2 GABA 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.

Symmetry-adapted Markov state models of closing, opening, and desensitizing in α 7 nicotinic acetylcholine receptors.

α7 nicotinic acetylcholine receptors (nAChRs) are homopentameric ligand-gated ion channels with critical roles in the nervous system. Recent studies have resolved and functionally annotated closed, open, and desensitized states of these receptors, providing insight into ion permeation and lipid binding. However, the process by which α7 nAChRs transition between states remains unclear.

Divergent mechanisms of steroid inhibition in the human ρ1 GABA receptor.

ρ-type γ-aminobutyric acid-A (GABA) receptors are widely distributed in the retina and brain, and are potential drug targets for the treatment of visual, sleep and cognitive disorders. Endogenous neuroactive steroids including β-estradiol and pregnenolone sulfate negatively modulate the function of ρ1 GABA receptors, but their inhibitory mechanisms are not clear. By combining five cryo-EM structures with electrophysiology and molecular dynamics simulations, we characterize binding sites and negative modulation mechanisms of β-estradiol and pregnenolone sulfate at the human ρ1 GABA receptor.

MDverse, shedding light on the dark matter of molecular dynamics simulations.

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data.

Exploring the Impact of Protein Chain Selection in Binding Energy Calculations with DFT.

Calculation of binding free energies between a protein and a ligand are highly desired for computer-aided drug design. Here we approximate the binding energies of ABL1, an enzyme which is the target for drugs used in the treatment of chronic myeloid leukaemia, with minimal models and density functional theory (DFT). Starting from the crystal structures of protein-drug complexes, we estimated the binding free energies having used all available individual molecules (protein chains) within each structure, not only a single one as commonly used, in order to see if the choice of the protein chain is important in such calculations.