Research: Conformational Ensembles of Membrane Proteins

Proteins carry out their functions by sampling an ensemble of three-dimensional structures. The relative free energies of these states, rather than any single structure, determine how a protein responds to its ligands, its lipid environment, and mutations. A central question in the laboratory is how nature encoded these conformational energy landscapes in protein sequence and how substrates, nucleotides, ions, and lipids reshape them.

We address this question in membrane transporters, whose function requires isomerization between inward-facing (IF) and outward-facing (OF) conformations, a process known as alternating access. Transporters of the ATP-binding cassette (ABC) superfamily and of ion-coupled families extrude drugs from cells and take up neurotransmitters, and they contribute to resistance to antibiotics and chemotherapy.

Schematic free-energy landscape along a collective variable with inward-facing, occluded and outward-facing wells. A ligand that favors the outward-facing state lowers that well, shifting the populations toward it. — A ligand shifts state populations by changing relative free energies. Schematic, not to scale.

Our approach integrates three lines of evidence. Double electron-electron resonance (DEER) spectroscopy of spin-labeled proteins reports distance distributions between pairs of sites in lipid bilayers or nanodiscs, and therefore the populations of coexisting conformations. Cryo-electron microscopy (cryo-EM) and molecular dynamics (MD) simulations define the structures of these states and the interactions that stabilize them. AI structure prediction with AlphaFold2 and AlphaFold3 (AF2, AF3) generates ensembles of candidate conformations that guide the design of experiments, while the experiments in turn arbitrate between the predicted models.

Diagram of three lines of evidence converging on one ensemble model: DEER distance distributions constrain the populations of coexisting states, cryo-EM structures constrain the structure of each state, and simulation and AlphaFold ensembles propose candidate states. — Each method constrains part of the ensemble and none constrains all of it. Solid outline: measured. Dashed outline: predicted. Schematic, not to scale.

The research programs of the laboratory are organized as follows.

ABC exporters. How ATP energy and lipids drive drug transport by P-glycoprotein, BmrCD, and protease-containing transporters.
Ion-coupled multidrug transporters. How Na⁺ and H⁺ gradients are coupled to substrate efflux by MATE and MFS transporters.
LeuT-fold transporters. Conformational dynamics of neurotransmitter:sodium symporters, including the serotonin transporter.
AI prediction of conformational landscapes. Driving AF2 and AF3 to sample alternative conformations and testing what the predictions mean.
Integration of experiment and AI. DEERFold and Rosetta methods that fold experimental distance distributions into structure prediction.
DEER spectroscopy. Methods for measuring conformational ensembles in lipid bilayers.

The AI components of this work are carried out within the Center for Applied AI in Protein Dynamics at Vanderbilt University, directed by Dr. Mchaourab.