Toward a Multipathway Perspective: pH-Dependent Kinetic Selection of Competing Pathways and the Role of the Internal Glutamate in Cl-/H+ Antiporters

Kinetic network modeling with molecular simulation inputs: A proton-coupled phosphate symporter

Phosphate, an essential metabolite involved in numerous cellular functions, is taken up by proton-coupled phosphate transporters of plants and fungi within the major facilitator family. Similar phosphate transporters have been identified across a diverse range of biological entities, including various protozoan parasites linked to human diseases, breast cancer cells with increased phosphate requirements, and osteoclast-like cells engaged in bone resorption. Prior studies have proposed an overview of the functional cycle of a proton-driven phosphate transporter (PiPT), yet a comprehensive understanding of the proposed reaction pathways necessitates a closer examination of each elementary reaction step within an overall kinetic framework. In this work, we leverage kinetic network modeling in conjunction with a "bottom-up" molecular dynamics approach to show how such an approach can characterize the proton-phosphate co-transport behavior of PiPT under different pH and phosphate concentration conditions. In turn, this allows us to reveal the prevailing reaction pathway within a high-affinity phosphate transporter under different experimental conditions and to uncover the molecular origin of the optimal pH condition of this transporter.

From Average Transient Transporter Currents to Microscopic Mechanism─A Bayesian Analysis

Electrophysiology studies of secondary active transporters have revealed quantitative mechanistic insights over many decades of research. However, the emergence of new experimental and analytical approaches calls for investigation of the capabilities and limitations of the newer methods. We examine the ability of solid-supported membrane electrophysiology (SSME) to characterize discrete-state kinetic models with >10 rate constants. We use a Bayesian framework applied to synthetic data for three tasks: to quantify and check (i) the precision of parameter estimates under different assumptions, (ii) the ability of computation to guide the selection of experimental conditions, and (iii) the ability of our approach to distinguish among mechanisms based on SSME data. When the general mechanism, i.e., event order, is known in advance, we show that a subset of kinetic parameters can be "practically identified" within ∼1 order of magnitude, based on SSME current traces that visually appear to exhibit simple exponential behavior. This remains true even when accounting for systematic measurement bias and realistic uncertainties in experimental inputs (concentrations) are incorporated into the analysis. When experimental conditions are optimized or different experiments are combined, the number of practically identifiable parameters can be increased substantially. Some parameters remain intrinsically difficult to estimate through SSME data alone, suggesting that additional experiments are required to fully characterize parameters. We also demonstrate the ability to perform model selection and determine the order of events when that is not known in advance, comparing Bayesian and maximum-likelihood approaches. Finally, our studies elucidate good practices for the increasingly popular but subtly challenging Bayesian calculations for structural and systems biology.

The role of conformational change and key glutamic acid residues in the ClC-ec1 antiporter

The triple glutamine (Q) mutant (QQQ) structure of a Cl-/H+ antiporter from Escherichia coli (ClC-ec1) displaying a novel backbone arrangement has been used to challenge the long-held notion that Cl-/H+ antiporters do not operate through large conformational motions. The QQQ mutant substitutes the glutamine residue for an external glutamate E148, an internal glutamate E203, and a third glutamate E113 that hydrogen-bonds with E203. However, it is unknown if QQQ represents a physiologically relevant state, as well as how the protonation of the wild-type glutamates relates to the global dynamics. We herein apply continuous constant-pH molecular dynamics to investigate the H+-coupled dynamics of ClC-ec1. Although any large-scale conformational rearrangement upon acidification would be due to the accumulation of excess charge within the protein, protonation of the glutamates significantly impacts mainly the local structure and dynamics. Despite the fact that the extracellular pore enlarges at acidic pHs, an occluded ClC-ec1 within the active pH range of 3.5-7.5 requires a protonated E148 to facilitate extracellular Cl- release. E203 is also involved in the intracellular H+ transfer as an H+ acceptor. The water wire connection of E148 with the intracellular solution is regulated by the charge states of the E113/E203 dyad with coupled proton titration. However, the dynamics extracted from our simulations are not QQQ-like, indicating that the QQQ mutant does not represent the behavior of the wild-type ClC-ec1. These findings reinforce the necessity of having a protonatable residue at the E203 position in ClC-ec1 and suggest that a higher level of complexity exists for the intracellular H+ transfer in Cl-/H+ antiporters.

Proton Coupling and the Multiscale Kinetic Mechanism of a Peptide Transporter

Proton coupled peptide transporters (POTs) are crucial for the uptake of di- and tri-peptides as well as drug and pro-drug molecules in prokaryotes and eukaryotic cells. We illustrate from multiscale modeling how transmembrane proton flux couples within a POT protein to drive essential steps of the full functional cycle: 1) protonation of a glutamate on transmembrane helix (TM) 7 opens the extracellular gate, allowing ligand entry; 2) inward proton flow induces the cytosolic release of ligand by varying the protonation state of a second conserved glutamate on TM10; 3) proton movement between TM7 and TM10 is thermodynamically driven and kinetically permissible via water proton shuttling without the participation of ligand. Our results, for the first time, give direct computational confirmation for the alternating access model of POTs, and point to a quantitative multiscale kinetic picture of the functioning protein mechanism.

Multiscale kinetic analysis of proteins

The stochasticity of molecular motion results in the existence of multiple kinetically relevant pathways in many biomolecular mechanisms. Because it is highly demanding to characterize them for complex systems, mechanisms are often described with a single-pathway perspective. However, kinetic network analysis and sub-ensemble experimental insight are increasingly demonstrating not only the existence of competing pathways but also the importance of kinetic selection in biology. This review focuses on advances in multiscale kinetic analysis of proteins, which connects molecular level information from simulations to macroscopic data to characterize mechanistic reaction networks and the reactive flux through them. We describe a range of methods used and highlight several examples where kinetic modeling has revealed functional importance of pathway heterogeneity.