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ATP synthases play a crucial role in energy production by utilizing the proton motive force (pmf) across the membrane to rotate their membrane-embedded rotor c-ring, and thus driving ATP synthesis in the hydrophilic catalytic hexamer. However, the mechanism of how pmf converts into c-ring rotation remains unclear. This study presents a 2.8 Å cryo-EM structure of the V o domain of V/A-ATPase from Thermus thermophilus, revealing precise orientations of glutamate (Glu) residues in the c 12 -ring. Three Glu residues face a water channel, with one forming a salt bridge with the Arginine in the stator (a/Arg). Molecular dynamics (MD) simulations show that protonation of specific Glu residues triggers unidirectional Brownian motion of the c 12 -ring towards ATP synthesis. When the key Glu remains unprotonated, the salt bridge persists, blocking rotation. These findings suggest that asymmetry in the protonation of c/Glu residues biases c 12 -ring movement, facilitating rotation and ATP synthesis., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Transporter proteins carry their substrate across the cell membrane by changing their conformation. Thus, conformational dynamics are crucial for transport function. However, clarifying the complete transport cycle is challenging even with the current structural biology approach. Molecular dynamics (MD) simulation is a computational approach that can provide the time-resolved conformational dynamics of transporter proteins in atomic details but suffers from a high computational cost. Here, we integrate state-of-the-art protein structure prediction AI, AlphaFold2 (AF2), with MD simulation to reduce the computational cost. Focusing on the transporter protein NarK, we first show that AF2 sampled broad conformations of NarK, including the inward-open, occluded, and outward-open states. We also applied the coevolution-informed mutation in AF2, identifying state-shifting mutations. Then, we show that MD simulations from AF2-generated outward-open conformation, which is experimentally unresolved, captured the essence of the conformational state. We also found that MD simulations from AF2-generated intermediates showed transient dynamics like a transition state connecting two conformational states. This study paves the way for efficient conformational sampling of transporter proteins.

The present work shows that the free energy landscape associated with alanine dipeptide isomerization can be effectively represented by specific interatomic distances without explicit reference to dihedral angles. Conventionally, two stable states of alanine dipeptide in vacuum, i.e., C7eq (β-sheet structure) and C7ax (left handed α-helix structure), have been primarily characterized using the main chain dihedral angles, φ (C-N-Cα-C) and ψ (N-Cα-C-N). However, our recent deep learning combined with the "Explainable AI" (XAI) framework has shown that the transition state can be adequately captured by a free energy landscape using φ and θ (O-C-N-Cα) [Kikutsuji et al., J. Chem. Phys. 156, 154108 (2022)]. In the perspective of extending these insights to other collective variables, a more detailed characterization of the transition state is required. In this work, we employ interatomic distances and bond angles as input variables for deep learning rather than the conventional and more elaborate dihedral angles. Our approach utilizes deep learning to investigate whether changes in the main chain dihedral angle can be expressed in terms of interatomic distances and bond angles. Furthermore, by incorporating XAI into our predictive analysis, we quantified the importance of each input variable and succeeded in clarifying the specific interatomic distance that affects the transition state. The results indicate that constructing a free energy landscape based on the identified interatomic distance can clearly distinguish between the two stable states and provide a comprehensive explanation for the energy barrier crossing., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

To monitor the Ca 2+ dynamics in cells, various genetically encoded Ca 2+ indicators (GECIs) based on Förster resonance energy transfer (FRET) between fluorescent proteins are widely used for live imaging. Conventionally, cyan and yellow fluorescent proteins have been often used as FRET pairs. Meanwhile, bathochromically shifted indicators with green and red fluorescent protein pairs have various advantages, such as low toxicity and autofluorescence in cells. However, it remains difficult to develop them with a similar level of dynamic range as cyan and yellow fluorescent protein pairs. To improve this, we used Gamillus, which has a unique trans-configuration chromophore, as a green fluorescent protein. Based on one of the best high-dynamic-range GECIs, Twitch-NR, we developed a GECI with 1.5-times higher dynamic range (253%), Twitch-GmRR, using RRvT as a red fluorescent protein. Twitch-GmRR had high brightness and photostability and was successfully applied for imaging the Ca 2+ dynamics in live cells. Our results suggest that Gamillus with trans-type chromophores contributes to improving the dynamic range of GECIs. Therefore, selection of the cis-trans isomer of the chromophore may be a fundamental approach to improve the dynamic range of green-red FRET indicators, unlimited by GECIs.

Transporter proteins change their conformations to carry their substrate across the cell membrane. The conformational dynamics is vital to understanding the transport function. We have studied the oxalate transporter (OxlT), an oxalate:formate antiporter from Oxalobacter formigenes , significant in avoiding kidney stone formation. The atomic structure of OxlT has been recently solved in the outward-open and occluded states. However, the inward-open conformation is still missing, hindering a complete understanding of the transporter. Here, we performed a Gaussian accelerated molecular dynamics simulation to sample the extensive conformational space of OxlT and successfully predicted the inward-open conformation where cytoplasmic substrate formate binding was preferred over oxalate binding. We also identified critical interactions for the inward-open conformation. The results were complemented by an AlphaFold2 structure prediction. Although AlphaFold2 solely predicted OxlT in the outward-open conformation, mutation of the identified critical residues made it partly predict the inward-open conformation, identifying possible state-shifting mutations.

Multidomain proteins can exhibit sophisticated functions based on cooperative interactions and allosteric regulation through spatial rearrangements of the multiple domains. This study explored the potential of using multidomain proteins as a basis for Förster resonance energy transfer (FRET) biosensors, focusing on protein disulfide isomerase (PDI) as a representative example. PDI, a well-studied multidomain protein, undergoes redox-dependent conformational changes, enabling the exposure of a hydrophobic surface extending across the b ' and a ' domains that serves as the primary binding site for substrates. Taking advantage of the dynamic domain rearrangements of PDI, we developed FRET-based biosensors by fusing the b ' and a ' domains of thermophilic fungal PDI with fluorescent proteins as the FRET acceptor and donor, respectively. Both experimental and computational approaches were used to characterize FRET efficiency in different redox states. In vitro and in vivo evaluations demonstrated higher FRET efficiency of this biosensor in the oxidized form, reflecting the domain rearrangement and its responsiveness to intracellular redox environments. This novel approach of exploiting redox-dependent domain dynamics in multidomain proteins offers promising opportunities for designing innovative FRET-based biosensors with potential applications in studying cellular redox regulation and beyond.

Silicon has been considered to be one of the most promising anode active materials for next-generation lithium-ion batteries due to its large theoretical capacity (4200 mA h g -1 , Li 22 Si 5 ). However, silicon anodes suffer from degradation due to large volume expansion and contraction. To control the ideal particle morphology, an experimental method is required to analyze anisotropic diffusion and surface reaction phenomena. This study investigates the anisotropy of the silicon-lithium alloying reaction using electrochemical measurements and Si K-edge X-ray absorption spectroscopy on silicon single crystals. During the electrochemical reduction process in lithium-ion battery systems, the continuous formation of solid electrolyte interphase (SEI) films prevents the achievement of steady-state conditions. Instead, the physical contact between silicon single crystals and lithium metals can prevent the effect of SEI formation. The apparent diffusion coefficient and the surface reaction coefficient are determined from the progress of the alloying reaction analyzed by X-ray absorption spectroscopy. While the apparent diffusion coefficients show no clear anisotropy, the apparent surface reaction coefficient of Si (100) is more significant than that of Si (111). This finding indicates that the surface reaction of silicon governs the anisotropy of practical lithium alloying reaction for silicon anodes., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

An oxalate-degrading bacterium in the gut microbiota absorbs food-derived oxalate to use this as a carbon and energy source, thereby reducing the risk of kidney stone formation in host animals. The bacterial oxalate transporter OxlT selectively uptakes oxalate from the gut to bacterial cells with a strict discrimination from other nutrient carboxylates. Here, we present crystal structures of oxalate-bound and ligand-free OxlT in two distinct conformations, occluded and outward-facing states. The ligand-binding pocket contains basic residues that form salt bridges with oxalate while preventing the conformational switch to the occluded state without an acidic substrate. The occluded pocket can accommodate oxalate but not larger dicarboxylates, such as metabolic intermediates. The permeation pathways from the pocket are completely blocked by extensive interdomain interactions, which can be opened solely by a flip of a single side chain neighbouring the substrate. This study shows the structural basis underlying metabolic interactions enabling favourable symbiosis., (© 2023. The Author(s).)

IF 1 is a natural inhibitor protein for mitochondrial F o F 1 ATP synthase that blocks catalysis and rotation of the F 1 by deeply inserting its N-terminal helices into F 1 . A unique feature of IF 1 is condition-dependent inhibition; although IF 1 inhibits ATP hydrolysis by F 1 , IF 1 inhibition is relieved under ATP synthesis conditions. To elucidate this condition-dependent inhibition mechanism, we have performed single-molecule manipulation experiments on IF 1 -inhibited bovine mitochondrial F 1 (bMF 1 ). The results show that IF 1 -inhibited F 1 is efficiently activated only when F 1 is rotated in the clockwise (ATP synthesis) direction, but not in the counterclockwise direction. The observed rotational-direction-dependent activation explains the condition-dependent mechanism of IF 1 inhibition. Investigation of mutant IF 1 with N-terminal truncations shows that the interaction with the γ subunit at the N-terminal regions is crucial for rotational-direction-dependent ejection, and the middle long helix is responsible for the inhibition of F 1 ., (© 2023. The Author(s).)

A method for obtaining appropriate reaction coordinates is required to identify transition states distinguishing the product and reactant in complex molecular systems. Recently, abundant research has been devoted to obtaining reaction coordinates using artificial neural networks from deep learning literature, where many collective variables are typically utilized in the input layer. However, it is difficult to explain the details of which collective variables contribute to the predicted reaction coordinates owing to the complexity of the nonlinear functions in deep neural networks. To overcome this limitation, we used Explainable Artificial Intelligence (XAI) methods of the Local Interpretable Model-agnostic Explanation (LIME) and the game theory-based framework known as Shapley Additive exPlanations (SHAP). We demonstrated that XAI enables us to obtain the degree of contribution of each collective variable to reaction coordinates that is determined by nonlinear regressions with deep learning for the committor of the alanine dipeptide isomerization in vacuum. In particular, both LIME and SHAP provide important features to the predicted reaction coordinates, which are characterized by appropriate dihedral angles consistent with those previously reported from the committor test analysis. The present study offers an AI-aided framework to explain the appropriate reaction coordinates, which acquires considerable significance when the number of degrees of freedom increases.

Coarse-grained (CG) molecular dynamics (MD) simulations allow us to access much larger length and time scales than atomistic MD simulations, providing an attractive alternative to the conventional simulations. Based on the well-known MARTINI CG force field, the recently developed Gō-MARTINI model for proteins describes large-amplitude structural dynamics, which has not been possible with the commonly used elastic network model. Using the Gō-MARTINI model, we conduct MD simulations of the F-BAR Pacsin1 protein on lipid membrane. We observe that structural changes of the non-globular protein are largely dependent on the definition of the native contacts in the Gō model. To address this issue, we introduced a simple cutoff scheme and tuned the cutoff distance of the native contacts and the interaction strength of the Lennard-Jones potentials in the Gō-MARTINI model. With the optimized Gō-MARTINI model, we show that it reproduces structural fluctuations of the Pacsin1 dimer from atomistic simulations. We also show that two Pacsin1 dimers properly assemble through lateral interaction on the lipid membrane. Our work presents a first step towards describing membrane remodeling processes in the Gō-MARTINI CG framework by simulating a crucial step of protein assembly on the membrane., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Mahmood, Poma and Okazaki.)

We propose a cross-entropy minimization method for finding the reaction coordinate from a large number of collective variables in complex molecular systems. This method is an extension of the likelihood maximization approach describing the committor function with a sigmoid. By design, the reaction coordinate as a function of various collective variables is optimized such that the distribution of the committor p B * values generated from molecular dynamics simulations can be described in a sigmoidal manner. We also introduce the L 2 -norm regularization used in the machine learning field to prevent overfitting when the number of considered collective variables is large. The current method is applied to study the isomerization of alanine dipeptide in vacuum, where 45 dihedral angles are used as candidate variables. The regularization parameter is determined by cross-validation using training and test datasets. It is demonstrated that the optimal reaction coordinate involves important dihedral angles, which are consistent with the previously reported results. Furthermore, the points with p B * ∼0.5 clearly indicate a separatrix distinguishing reactant and product states on the potential of mean force using the extracted dihedral angles.

The mechanism of biomolecular motors has been elucidated using single-molecule experiments for visualizing motor motion. However, it remains elusive that how changes in the chemical state during the catalytic cycle of motors lead to unidirectional motions. In this study, we use single-molecule trajectories to estimate an underlying diffusion model with chemical-state-dependent free energy profile. To consider nonequilibrium trajectories driven by the chemical energy consumed by biomolecular motors, we develop a novel framework based on a hidden Markov model, wherein switching among multiple energy profiles occurs reflecting the chemical state changes in motors. The method is tested using simulation trajectories and applied to single-molecule trajectories of processive chitinase, a linear motor that is driven by the hydrolysis energy of a single chitin chain. The chemical-state-dependent free energy profile underlying the burnt-bridge Brownian ratchet mechanism of processive chitinase is determined. The novel framework allows us to connect the chemical state changes to the unidirectional motion of biomolecular motors.

Motor proteins are essential units of life and are well-designed nanomachines working under thermal fluctuations. These proteins control moving direction by consuming chemical energy or by dissipating electrochemical potentials. Chitinase A from bacterium Serratia marcescens (SmChiA) processively moves along crystalline chitin by hydrolysis of a single polymer chain to soluble chitobiose. Recently, we directly observed the stepping motions of SmChiA labeled with a gold nanoparticle by dark-field scattering imaging to investigate the moving mechanism. Time constants analysis revealed that SmChiA moves back and forth along the chain freely, because forward and backward states have a similar free energy level. The similar probabilities of forward-step events (83.5%=69.3%+14.2%) from distributions of step sizes and chain-hydrolysis (86.3%=(1/2.9)/(1/2.9+1/18.3)×100) calculated from the ratios of time constants of hydrolysis and the backward step indicated that SmChiA moves forward as a result of shortening of the chain by a chitobiose unit, which stabilizes the backward state. Furthermore, X-ray crystal structures of sliding intermediate and molecular dynamics simulations showed that SmChiA slides forward and backward under thermal fluctuation without large conformational changes of the protein. Our results demonstrate that SmChiA is a burnt-bridge Brownian ratchet motor., (2020 THE BIOPHYSICAL SOCIETY OF JAPAN.)

Cells employ membrane-embedded antiporter proteins to control their pH, salt concentration, and volume. The large family of cation/proton antiporters is dominated by Na + /H + antiporters that exchange sodium ions against protons, but homologous K + /H + exchangers have recently been characterized. We show experimentally that the electroneutral antiporter NhaP1 of Methanocaldococcus jannaschii (MjNhaP1) is highly selective for Na + ions. We then characterize the ion selectivity in both the inward-open and outward-open states of MjNhaP1 using classical molecular dynamics simulations, free energy calculations, and hybrid quantum/classical (QM/MM) simulations. We show that MjNhaP1 is highly selective for binding of Na + over K + in the inward-open state, yet it is only weakly selective in the outward-open state. These findings are consistent with the function of MjNhaP1 as a sodium-driven deacidifier of the cytosol that maintains a high cytosolic K + concentration in environments of high salinity. By combining experiment and computation, we gain mechanistic insight into the Na + /H + transport mechanism and help elucidate the molecular basis for ion selectivity in cation/proton exchangers.

Fluoride-shuttle batteries (FSBs), which are based on fluoride-ion transfer, have attracted attention because of their high theoretical energy densities. The fluorination and defluorination reactions at the electrodes are the possible rate-determining steps in FSBs, and understanding the mechanism is important to achieve smooth charge/discharge. In this study, we discuss the thermodynamically favored pathways for the fluorination and defluorination reactions and compare the reactions through the solid-solution and two-phase-coexistent states by density functional theory (DFT) calculations. The free energies of the solid-solution and two-phase states approximate the energies calculated by DFT, and their accuracy was validated by comparison with experimental formation enthalpies and free energies. The relative formation enthalpies of typical, transition, and relativistic metal (Tl, Pb, and Bi) fluorides are well reproduced by DFT calculations within 0.1, 0.2, and 0.4 eV, respectively. We also show that the reaction pathway can be determined by comparing the formation enthalpies of the metal fluoride H , a fluorine vacancy H V , and an interstitial fluorine defect H I from the simple selection rule. The enthalpy relation of H I > H > - H V observed in all the calculations strongly suggests that fluorination and defluorination in FSB electrodes occur by a two-phase reaction. This fluorination and defluorination mechanism will be useful to clarify the rate-determining step in FSBs.

F-Bin/Amphiphysin/Rvs (F-BAR) domain proteins play essential roles in biological processes that involve membrane remodelling, such as endocytosis and exocytosis. It has been shown that such proteins transform the lipid membrane into tubes. Notably, Pacsin1 from the Pacsin/Syndapin subfamily has the ability to transform the membrane into various morphologies: striated tubes, featureless wide and thin tubes, and pearling vesicles. The molecular mechanism of this interesting ability remains elusive. In this study, we performed all-atom (AA) and coarse-grained (CG) molecular dynamics simulations to investigate the curvature induction and sensing mechanisms of Pacsin1 on a membrane. From AA simulations, we show that Pacsin1 has internal structural flexibility. In CG simulations with parameters tuned from the AA simulations, spontaneous assembly of two Pacsin1 dimers through lateral interaction is observed. Based on the complex structure, we show that the regularly assembled Pacsin1 dimers bend a tensionless membrane. We also show that a single Pacsin1 dimer senses the membrane curvature, binding to a buckled membrane with a preferred curvature. These results provide molecular insights into polymorphic membrane remodelling.

Na + /H + antiporters exchange sodium ions and protons on opposite sides of lipid membranes. The electroneutral Na + /H + antiporter NhaP from archaea Pyrococcus abyssi (PaNhaP) is a functional homolog of the human Na + /H + exchanger NHE1, which is an important drug target. Here we resolve the Na + and H + transport cycle of PaNhaP by transition-path sampling. The resulting molecular dynamics trajectories of repeated ion transport events proceed without bias force, and overcome the enormous time-scale gap between seconds-scale ion exchange and microseconds simulations. The simulations reveal a hydrophobic gate to the extracellular side that opens and closes in response to the transporter domain motion. Weakening the gate by mutagenesis makes the transporter faster, suggesting that the gate balances competing demands of fidelity and efficiency. Transition-path sampling and a committor-based reaction coordinate optimization identify the essential motions and interactions that realize conformational alternation between the two access states in transporter function.

Fluoride shuttle batteries (FSBs), which utilize defluorination of metal fluorides and fluorination of the resultant metals, are expected to have high energy densities. In situ Raman microscopy was conducted during FSB reactions of a nearly-2D cluster of orthorhombic BiF 3 microparticles partly embedded in a gold-plated film (o-BiF 3 /gold). At a high overpotential, defluorination of the surface of an o-BiF 3 particle (or cluster) was almost completed within approximately 120 s. At a low over potential, defluorination proceeded from the contours of the cluster that was in contact with the gold to the center of the cluster, suggesting that the rate-limiting process was electronic diffusion. Conversely, fluorination proceeded uniformly at the surface of the cluster to form BiF 3 with a cubic structure (c-BiF 3 ). The results will lead to the establishment of a strategy for efficient use of active materials with low electronic and ionic conductivities., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Processive chitinase is a linear molecular motor which moves on the surface of crystalline chitin driven by processive hydrolysis of single chitin chain. Here, we analyse the mechanism underlying unidirectional movement of Serratia marcescens chitinase A (SmChiA) using high-precision single-molecule imaging, X-ray crystallography, and all-atom molecular dynamics simulation. SmChiA shows fast unidirectional movement of ~50 nm s -1 with 1 nm forward and backward steps, consistent with the length of reaction product chitobiose. Analysis of the kinetic isotope effect reveals fast substrate-assisted catalysis with time constant of ~3 ms. Decrystallization of the single chitin chain from crystal surface is the rate-limiting step of movement with time constant of ~17 ms, achieved by binding free energy at the product-binding site of SmChiA. Our results demonstrate that SmChiA operates as a burnt-bridge Brownian ratchet wherein the Brownian motion along the single chitin chain is rectified forward by substrate-assisted catalysis.

Transition path sampling is a powerful tool in the study of rare events. Shooting trial trajectories from configurations along existing transition paths proved particularly efficient in the sampling of reactive trajectories. However, most shooting attempts tend not to result in transition paths, in particular in cases where the transition dynamics has diffusive character. To overcome the resulting efficiency problem, we developed an algorithm for "shooting from the top." We first define a shooting range through which all paths have to pass and then shoot off trial trajectories only from within this range. For a well chosen shooting range, nearly every shot is successful, resulting in an accepted transition path. To deal with multiple mechanisms, weighted shooting ranges can be used. To cope with the problem of unsuitably placed shooting ranges, we developed an algorithm that iteratively improves the location of the shooting range. The transition path sampling procedure is illustrated for models of diffusive and Langevin dynamics. The method should be particularly useful in cases where the transition paths are long so that only relatively few shots are possible, yet reasonable order parameters are known.

Clarification of the details of the interface structure between liquids and solids is crucial for understanding the fundamental processes of physical functions. Herein, we investigate the structure of the interface between tetraglyme and graphite and propose a model for the interface structure based on the observation of frequency-modulation atomic force microscopy in liquids. The ordering and distorted adsorption of tetraglyme on graphite were observed. It is found that tetraglyme stably adsorbs on graphite. Density functional theory calculations supported the adsorption structure. In the liquid phase, there is a layered structure of the molecular distribution with an average distance of 0.60 nm between layers.