Interpretation of spectroscopic data using molecular simulations for the secondary active transporter BetP

Abstract

Mechanistic understanding of dynamic membrane proteins such as transporters, receptors, and channels requires accurate depictions of conformational ensembles, and the manner in which they interchange as a function of environmental factors including substrates, lipids, and inhibitors. Spectroscopic techniques such as electron spin resonance (ESR) pulsed electron–electron double resonance (PELDOR), also known as double electron–electron resonance (DEER), provide a complement to atomistic structures obtained from x-ray crystallography or cryo-EM, since spectroscopic data reflect an ensemble and can be measured in more native solvents, unperturbed by a crystal lattice. However, attempts to interpret DEER data are frequently stymied by discrepancies with the structural data, which may arise due to differences in conditions, the dynamics of the protein, or the flexibility of the attached paramagnetic spin labels. Recently, molecular simulation techniques such as EBMetaD have been developed that create a conformational ensemble matching an experimental distance distribution while applying the minimal possible bias. Moreover, it has been proposed that the work required during an EBMetaD simulation to match an experimentally determined distribution could be used as a metric with which to assign conformational states to a given measurement. Here, we demonstrate the application of this concept for a sodium-coupled transport protein, BetP. Because the probe, protein, and lipid bilayer are all represented in atomic detail, the different contributions to the work, such as the extent of protein backbone movements, can be separated. This work therefore illustrates how ranking simulations based on EBMetaD can help to bridge the gap between structural and biophysical data and thereby enhance our understanding of membrane protein conformational mechanisms.

Principles of Alternating Access in LeuT-fold Transporters: Commonalities and Divergences

“…As with NSSs discussed above, key differences exist between these SSS transporters: whereas sodium was not observed to engender large structural changes in vSGLT [113], sodium binding to PutP led to closing of EL4 and increased accessibility of residues lining the intracellular vestibule [141,145,146]. Importantly, similar sodium-invariant conformational dynamics were independently reported in the unrelated bacterial transporter Mhp1 using both EPR and cysteine accessibility measurements [107,147,148], and sodium-driven stabilization of an IF state was also suggested by EPR data in BetP [149].…”

Autoregulation of a trimeric transporter involves the cytoplasmic domains of both adjacent subunits

“…The C-terminal helix does not remain inclined in the absence of crystal contacts -The inclined orientation of the C-terminal helix is observed in all reported crystal structures, which include many different conformations of the membrane-spanning transport domain. Of these conformations, the inward-open state is the preferred conformation in resting conditions in the presence of saturating amounts of sodium but in the absence of betaine substrate (16). Therefore, here we simulated the trimer with all three transport domains in inward-open conformations (PDB code 4C7R), and with all three C-terminal helices in an inclined orientation.…”

Interrogating the conformational dynamics of BetP transport

“…Leone et al (2019) demonstrate how to use a variation of the Metadynamics strategy, called ensemble-biased Metadynamics (EBMetaD; Marinelli and Faraldo-Gómez, 2015), to interrogate which BetP structure most likely corresponds to the experimental dynamics data. Ensemble biasing means that the target of the simulation is a nonuniform distribution, such as a distance distribution measured by PELDOR (Fig.…”

“…In these cases, dynamics data cannot be clearly assigned to any particular structure and thus it can be difficult to interpret the data. Leone et al, show that this is a problem for the BetP transporter (Leone et al, 2019). They carry out site-directed spin labeling at two residue positions, G450C and S516C, which span the region of the protein where the largest conformational changes are observed between the inward-open (PDB ID 4C7R) and outward-open (PDB ID 4LLH) states.…”

“…Convergence of the sampling is directly monitored, and since the magnitudes of the biasing potentials are known, the results can be unbiased to reveal the underlying energy landscape of the system. Leone et al (2019) demonstrate how to use a variation of the Metadynamics strategy, called ensemble-biased Metadynamics (EBMetaD; Marinelli and Faraldo-Gómez, 2015), to interrogate which BetP structure most likely corresponds to the experimental dynamics data. Ensemble biasing means that the target of the simulation is a nonuniform distribution, such as a distance distribution measured by PELDOR (Fig.…”