Molecular Basis of CLC Antiporter Inhibition by Fluoride

Transport mechanism of DgoT, a bacterial homolog of SLC17 organic anion transporters

The solute carrier 17 (SLC17) family contains anion transporters that accumulate neurotransmitters in secretory vesicles, remove carboxylated monosaccharides from lysosomes, or extrude organic anions from the kidneys and liver. We combined classical molecular dynamics simulations, Markov state modeling and hybrid first principles quantum mechanical/classical mechanical (QM/MM) simulations with experimental approaches to describe the transport mechanisms of a model bacterial protein, the D-galactonate transporter DgoT, at atomic resolution. We found that protonation of D46 and E133 precedes galactonate binding and that substrate binding induces closure of the extracellular gate, with the conserved R47 coupling substrate binding to transmembrane helix movement. After isomerization to an inward-facing conformation, deprotonation of E133 and subsequent proton transfer from D46 to E133 opens the intracellular gate and permits galactonate dissociation either in its unprotonated form or after proton transfer from E133. After release of the second proton, apo DgoT returns to the outward-facing conformation. Our results provide a framework to understand how various SLC17 transport functions with distinct transport stoichiometries can be attained through subtle variations in proton and substrate binding/unbinding.

MiMiC: A high-performance framework for multiscale molecular dynamics simulations

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.g., CPU/GPU), and keep their setup and execution as close as possible to the original. At the moment, MiMiC offers an efficient implementation of electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) that has demonstrated unprecedented parallel scaling in simulations of large biomolecules using CPMD and GROMACS as QM and MM engines, respectively. However, as it is designed for high flexibility with general multiscale models in mind, it can be straightforwardly extended beyond QM/MM. In this article, we illustrate the software design and the features of the framework, which make it a compelling choice for multiscale simulations in the upcoming era of exascale high-performance computing.

Multiscale biomolecular simulations in the exascale era

The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations are crucial for capturing processes beyond the reach of classical MD simulations. The advent of exascale computing offers unprecedented opportunities for scientific exploration, not least within life sciences, where simulations are essential to unravel intricate molecular mechanisms underlying biological processes. However, leveraging the immense computational power of exascale computing requires innovative algorithms and software designs. In this context, we discuss the current status and future prospects of multiscale biomolecular simulations on exascale supercomputers with a focus on QM/MM MD. We highlight our own efforts in developing a versatile and high-performance multiscale simulation framework with the aim of efficient utilization of state-of-the-art supercomputers. We showcase its application in uncovering complex biological mechanisms and its potential for leveraging exascale computing.

Kinetic View of Enzyme Catalysis from Enhanced Sampling QM/MM Simulations

The rate constants of enzyme-catalyzed reactions (kcat) are often approximated from the barrier height of the reactive step. We introduce an enhanced sampling QM/MM approach that directly calculates the kinetics of enzymatic reactions, without introducing the transition-state theory assumptions, and takes into account the dynamical equilibrium between the reactive and non-reactive conformations of the enzyme/substrate complex. Our computed kcat values are in order-of-magnitude agreement with the experimental data for two representative enzymatic reactions.

Fluoride Ion Binding and Translocation in the CLCF Fluoride/Proton Antiporter: Molecular Insights from Combined Quantum-Mechanical/Molecular-Mechanical Modeling

CLCF fluoride/proton antiporters move fluoride ions out of bacterial cells, leading to fluoride resistance in these bacteria. However, many details about their operating mechanisms remain unclear. Here, we report a combined quantum-mechanical/molecular-mechanical (QM/MM) study of a CLCF homologue from Enterococci casseliflavus (Eca), in accord with the previously proposed windmill mechanism. Our multiscale modeling sheds light on two critical steps in the transport cycle: (i) the external gating residue E118 pushing a fluoride in the external binding site into the extracellular vestibule and (ii) an incoming fluoride reconquering the external binding site by forcing out E118. Both steps feature competitions for the external binding site between the negatively charged carboxylate of E118 and the fluoride. Remarkably, the displaced E118 by fluoride accepts a proton from the nearby R117, initiating the next transport cycle. We also demonstrate the importance of accurate quantum descriptions of fluoride solvation. Our results provide clues to the mysterious E318 residue near the central binding site, suggesting that the transport activities are unlikely to be disrupted by the glutamate interacting with a well-solvated fluoride at the central binding site. This differs significantly from the structurally similar CLC chloride/proton antiporters, where a fluoride trapped deep in the hydrophobic pore causes the transporter to be locked down. A free-energy barrier of 10-15 kcal/mol was estimated via umbrella sampling for a fluoride ion traveling through the pore to repopulate the external binding site.

Fluoride Transport and Inhibition Across CLC Transporters

The Chloride Channel (CLC) family includes proton-coupled chloride and fluoride transporters. Despite their similar protein architecture, the former exchange two chloride ions for each proton and are inhibited by fluoride, whereas the latter efficiently transport one fluoride in exchange for one proton. The combination of structural, mutagenesis, and functional experiments with molecular simulations has pinpointed several amino acid changes in the permeation pathway that capitalize on the different chemical properties of chloride and fluoride to fine-tune protein function. Here we summarize recent findings on fluoride inhibition and transport in the two prototypical members of the CLC family, the chloride/proton transporter from Escherichia coli (CLC-ec1) and the fluoride/proton transporter from Enterococcus casseliflavus (CLCF-eca).

The role of plant growth promoting rhizobacteria in strengthening plant resistance to fluoride toxicity: a review

A wide variety of bacteria are present in soil but in rhizospheric area, the majority of microbes helps plant in defending diseases and facilitate nutrient uptake. These microorganisms are supported by plants and they are known as plant growth-promoting rhizobacteria (PGPR). The PGPRs have the potential to replace chemical fertilizers in a way that is more advantageous for the environment. Fluoride (F) is one of the highly escalating, naturally present contaminants that can be hazardous for PGPRs because of its antibacterial capacity. The interactions of F with different bacterial species in groundwater systems are still not well understood. However, the interaction of PGPR with plants in the rhizosphere region reduces the detrimental effects of pollutants and increases plants' ability to endure abiotic stress. Many studies reveal that PGPRs have developed F defense mechanisms, which include efflux pumps, Intracellular sequestration, enzyme modifications, enhanced DNA repair mechanism, detoxification enzymes, ion transporter/antiporters, F riboswitches, and genetic mutations. These resistance characteristics are frequently discovered by isolating PGPRs from high F-contaminated areas or by exposing cells to fluoride in laboratory conditions. Numerous studies have identified F-resistant microorganisms that possess additional F transporters and duplicates of the well-known targets of F. Plants are prone to F accumulation despite the soil's low F content, which may negatively affect their growth and development. PGPRs can be used as efficient F bioremediators for the soil environment. Environmental biotechnology focuses on creating genetically modified rhizobacteria that can degrade F contaminants over time. The present review focuses on a thorough systemic analysis of contemporary biotechnological techniques, such as gene editing and manipulation methods, for improving plant-microbe interactions for F remediation and suggests the importance of PGPRs in improving soil health and reducing the detrimental effects of F toxicity. The most recent developments in the realm of microbial assistance in the treatment of F-contaminated environments are also highlighted.

Anion Pathways in the NarK Nitrate/Nitrite Exchanger

NarK nitrate/nitrite antiporter imports nitrate (a mineral form of the essential element nitrogen) into the cell and exports nitrite (a metabolite that can be toxic in high concentrations) out of the cell. However, many details about its operational mechanism remain poorly understood. In this work, we performed steered molecular dynamics simulations of anion translocations and quantum-chemistry model calculations of the binding sites to study the wild-type NarK protein and its R89K mutant. Our results shed light on the importance of the two strictly conserved binding-site arginine residues (R89 and R305) and two glycine-rich signature motifs (G164-M176 and G408-F419) in anion movement through the pore. We also observe conformational changes of the protein during anion migration. For the R89K mutant, our quantum calculations reveal a competition for a proton between the anion (especially nitrite) and lysine, which can potentially slow down or even trap the anion in the pore. Our findings provide a possible explanation for the striking experimental finding that the arginine-to-lysine mutation, despite preserving the charge, impedes or abolishes anion transport in such mutants of NarK and other similar nitrate/nitrite exchangers.

Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations

The initial phases of drug discovery - in silico drug design - could benefit from first principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, yet many applications are currently limited by the short time scales that this approach can cover. Developing scalable first principle QM/MM MD interfaces fully exploiting current exascale machines - so far an unmet and crucial goal - will help overcome this problem, opening the way to the study of the thermodynamics and kinetics of ligand binding to protein with first principle accuracy. Here, taking two relevant case studies involving the interactions of ligands with rather large enzymes, we showcase the use of our recently developed massively scalable Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework (currently using DFT to describe the QM region) to investigate reactions and ligand binding in enzymes of pharmacological relevance. We also demonstrate for the first time strong scaling of MiMiC-QM/MM MD simulations with parallel efficiency of ∼70% up to >80,000 cores. Thus, among many others, the MiMiC interface represents a promising candidate toward exascale applications by combining machine learning with statistical mechanics based algorithms tailored for exascale supercomputers.

Uncovering the Mechanism of the Proton-Coupled Fluoride Transport in the CLCF Antiporter

Fluoride is a natural antibiotic abundantly present in the environment and, in micromolar concentrations, is able to inhibit enzymes necessary for bacteria to survive. However, as is the case with many antibiotics, bacteria have evolved resistance methods, including through the use of recently discovered membrane proteins. One such protein is the CLC^F F^-/H⁺ antiporter protein, a member of the CLC superfamily of anion-transport proteins. Though previous studies have examined this F^- transporter, many questions are still left unanswered. To reveal details of the transport mechanism used by CLC^F, we have employed molecular dynamics simulations and umbrella sampling calculations. Our results have led to several discoveries, including the mechanism of proton import and how it is able to aid in the fluoride export. Additionally, we have determined the role of the previously identified residues Glu118, Glu318, Met79, and Tyr396. This work is among the first studies of the CLC^F F^-/H⁺ antiporter and is the first computational investigation to model the full transport process, proposing a mechanism which couples the F^- export with the H⁺ import.

Enhanced-Sampling Simulations for the Estimation of Ligand Binding Kinetics: Current Status and Perspective

The dissociation rate (k off) associated with ligand unbinding events from proteins is a parameter of fundamental importance in drug design. Here we review recent major advancements in molecular simulation methodologies for the prediction of k off. Next, we discuss the impact of the potential energy function models on the accuracy of calculated k off values. Finally, we provide a perspective from high-performance computing and machine learning which might help improve such predictions.

Discover, Sample, and Refine: Exploring Chemistry with Enhanced Sampling Techniques

Over the last few decades, enhanced sampling methods have been continuously improved. Here, we exploit this progress and propose a modular workflow for blind reaction discovery and determination of reaction paths. In a three-step strategy, at first we use a collective variable derived from spectral graph theory in conjunction with the explore variant of the on-the-fly probability enhanced sampling method to drive reaction discovery runs. Once different chemical products are determined, we construct an ad-hoc neural network-based collective variable to improve sampling, and finally we refine the results using the free energy perturbation theory and a more accurate Hamiltonian. We apply this strategy to both intramolecular and intermolecular reactions. Our workflow requires minimal user input and extends the power of ab initio molecular dynamics to explore and characterize the reaction space.

Structural Origin and Vibrational Fingerprints of the Ultrafast Excited State Proton Transfer of the Pyranine-Acetate Complex in Aqueous Solution

The excited state proton transfer (ESPT) reaction from the photoacid 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS or pyranine) to an acetate molecule has been investigated in explicit aqueous solution via excited state ab initio molecular dynamics simulations based on hybrid quantum/molecular mechanics (QM/MM) potentials. In all the trajectories, the direct proton transfer has been observed in the excited state within 1 ps. We find that the initial structural configuration extracted from the ground state distribution strongly affects the ESPT kinetics. Indeed, the relative orientation of the proton donor-acceptor pair and the presence of a water molecule hydrogen bonded to the phenolic acid group of the pyranine are the key factors to facilitate the ESPT. Furthermore, we analyze the vibrational fingerprints of the ESPT reaction, reproducing the blue shift of the acetate CO stretching (CO_ac), from 1666 to 1763 cm^-1 testifying the transformation of acetate to acetic acid. Finally, our findings suggest that the acetate CC stretching (CC_ac) is also sensitive to the progress of the ESPT reaction. The CC_ac stretching is indeed ruled by the two vibrational modes (928 and 1426 cm^-1), that in the excited state are alternately activated when the proton is shared or bound to the donor/acceptor, respectively.

From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules

The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.

Mechanisms Underlying Proton Release in CLC-type F-/H+ Antiporters

The CLC family of anion channels and transporters includes Cl^-/H⁺ exchangers (blocked by F^-) and F^-/H⁺ exchangers (or CLC^Fs). CLC^Fs contain a glutamate (E318) in the central anion-binding site that is absent in CLC Cl^-/H⁺ exchangers. The X-ray structure of the protein from Enterococcus casseliflavus (CLC^F-eca) shows that E318 tightly binds to F^- when the gating glutamate (E118; highly conserved in the CLC family) faces the extracellular medium. Here, we use classical and DFT-based QM/MM metadynamics simulations to investigate proton transfer and release by CLC^F-eca. After up to down movement of protonated E118, both glutamates combine with F^- to form a triad, from which protons and F^- anions are released as HF. Our results illustrate how glutamate insertion into the central anion-binding site of CLC^F-eca permits the release of H⁺ to the cytosol as HF, thus enabling a net 1:1 F^-/H⁺ stoichiometry.

Water-Mediated Excited State Proton Transfer of Pyranine-Acetate in Aqueous Solution: Vibrational Fingerprints from Ab Initio Molecular Dynamics

In this work, we simulate the excited state proton transfer (ESPT) reaction involving the pyranine photoacid and an acetate molecule as proton acceptor, connected by a bridge water molecule. We employ ab initio molecular dynamics combined with an hybrid quantum/molecular mechanics (QM/MM) framework. Furthermore, a time-resolved vibrational analysis based on the wavelet-transform allows one to identify two low frequency vibrational modes that are fingerprints of the ESPT event: a ring wagging and ring breathing. Their composition suggests their key role in optimizing the structure of the proton donor–acceptor couple and promoting the ESPT event. We find that the choice of the QM/MM partition dramatically affects the photoinduced reactivity of the system. The QM subspace was gradually extended including the water molecules directly interacting with the pyranine–water–acetate system. Indeed, the ESPT reaction takes place when the hydrogen bond network around the reactive system is taken into account at full QM level.

Membrane Exporters of Fluoride Ion

Microorganisms contend with numerous and unusual chemical threats and have evolved a catalog of resistance mechanisms in response. One particularly ancient, pernicious threat is posed by fluoride ion (F^-), a common xenobiotic in natural environments that causes broad-spectrum harm to metabolic pathways. This review focuses on advances in the last ten years toward understanding the microbial response to cytoplasmic accumulation of F^-, with a special emphasis on the structure and mechanisms of the proteins that microbes use to export fluoride: the CLC^F family of F^-/H⁺ antiporters and the Fluc/FEX family of F^- channels.