Regulation of caveolae through cholesterol-depletion-dependent tubulation mediated by PACSIN2.

The membrane-shaping ability of PACSIN2 (also known as syndapin II), which is mediated by its F-BAR domain, has been shown to be essential for caveolar morphogenesis, presumably through the shaping of the caveolar neck. Caveolar membranes contain abundant cholesterol. However, the role of cholesterol in PACSIN2-mediated membrane deformation remains unclear. Here, we show that the binding of PACSIN2 to the membrane can be negatively regulated by cholesterol. We prepared reconstituted membranes based on the lipid composition of caveolae. The reconstituted membrane with cholesterol had a weaker affinity for the F-BAR domain of PACSIN2 than a membrane without cholesterol. Consistent with this, upon depletion of cholesterol from the plasma membrane, PACSIN2 localized at tubules that had caveolin-1 at their tips, suggesting that cholesterol inhibits membrane tubulation mediated by PACSIN2. The tubules induced by PACSIN2 could be representative of an intermediate of caveolae endocytosis. Consistent with this, the removal of caveolae from the plasma membrane upon cholesterol depletion was diminished in the PACSIN2-deficient cells. These data suggest that PACSIN2-mediated caveolae internalization is dependent on the amount of cholesterol, providing a mechanism for cholesterol-dependent regulation of caveolae.This article has an associated First Person interview with the first author of the paper.

Impact of key residues within chloroplast thioredoxin-f on recognition for reduction and oxidation of target proteins.

Thioredoxin (Trx) is a redox-responsive protein that modulates the activities of its target proteins mostly by reducing their disulfide bonds. In chloroplasts, five Trx isoforms (Trx-f, Trx-m, Trx-x, Trx-y, and Trx-z) regulate various photosynthesis-related enzymes with distinct target selectivity. To elucidate the determinants of the target selectivity of each Trx isoform, here we investigated the residues responsible for target recognition by Trx-f, the most well-studied chloroplast-resident Trx. As reported previously, we found that positively-charged residues on the Trx-f surface are involved in the interactions with its targets. Moreover, several residues that are specifically conserved in Trx-f (e.g. Cys-126 and Thr-158) were also involved in interactions with target proteins. The validity of these residues was examined by the molecular dynamics simulation. In addition, we validated the impact of these key residues on target protein reduction by studying (i) Trx-m variants into which we introduced the key residues for Trx-f and (ii) Trx-like proteins, named atypical Cys His-rich Trx 1 (ACHT1) and ACHT2a, that also contain these key residues. These artificial or natural protein variants could reduce Trx-f-specific targets, indicating that the key residues for Trx-f are critical for Trx-f-specific target recognition. Furthermore, we demonstrate that ACHT1 and ACHT2a efficiently oxidize some Trx-f-specific targets, suggesting that its target selectivity also contributes to the oxidative regulation process. Our results reveal the key residues for Trx-f-specific target recognition and uncover ACHT1 and ACHT2a as oxidation factors of their target proteins, providing critical insight into redox regulation of photosynthesis.

evERdock BAI: Machine-learning-guided selection of protein-protein complex structure.

Computational techniques for accurate and efficient prediction of protein-protein complex structures are widely used for elucidating protein-protein interactions, which play important roles in biological systems. Recently, it has been reported that selecting a structure similar to the native structure among generated structure candidates (decoys) is possible by calculating binding free energies of the decoys based on all-atom molecular dynamics (MD) simulations with explicit solvent and the solution theory in the energy representation, which is called evERdock. A recent version of evERdock achieves a higher-accuracy decoy selection by introducing MD relaxation and multiple MD simulations/energy calculations; however, huge computational cost is required. In this paper, we propose an efficient decoy selection method using evERdock and the best arm identification (BAI) framework, which is one of the techniques of reinforcement learning. The BAI framework realizes an efficient selection by suppressing calculations for nonpromising decoys and preferentially calculating for the promising ones. We evaluate the performance of the proposed method for decoy selection problems of three protein-protein complex systems. Their results show that computational costs are successfully reduced by a factor of 4.05 (in the best case) compared to a standard decoy selection approach without sacrificing accuracy.

Binding free energy analysis of protein-protein docking model structures by evERdock.

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

Refining evERdock: Improved selection of good protein-protein complex models achieved by MD optimization and use of multiple conformations.

A method for evaluating binding free energy differences of protein-protein complex structures generated by protein docking was recently developed by some of us. The method, termed evERdock, combined short (2 ns) molecular dynamics (MD) simulations in explicit water and solution theory in the energy representation (ER) and succeeded in selecting the near-native complex structures from a set of decoys. In the current work, we performed longer (up to 100 ns) MD simulations before employing ER analysis in order to further refine the structures of the decoy set with improved binding free energies. Moreover, we estimated the binding free energies for each complex structure based on an average value from five individual MD snapshots. After MD simulations, all decoys exhibit a decrease in binding free energy, suggesting that proper equilibration in explicit solvent resulted in more favourably bound complexes. During the MD simulations, non-native structures tend to become unstable and in some cases dissociate, while near-native structures maintain a stable interface. The energies after the MD simulations show an improved correlation between similarity criteria (such as interface root-mean-square distance) to the native (crystal) structure and the binding free energy. In addition, calculated binding free energies show sensitivity to the number of contacts, which was demonstrated to reflect the relative stability of structures at earlier stages of the MD simulation. We therefore conclude that the additional equilibration step along with the use of multiple conformations can make the evERdock scheme more versatile under low computational cost.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation.

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

Dependence of Vibrational Energy Transfer on Distance in a Four-Helix Bundle Protein: Equidistant Increments with the Periodicity of α Helices.

Vibrational energy exchanges between various degrees of freedom are critical to barrier-crossing processes in proteins. Heme proteins are highly suitable for studies of the vibrational energy exchanges in proteins. The migration of excess energy released by heme in a protein moiety can be observed using time-resolved anti-Stokes ultraviolet resonance Raman spectroscopy. The anti-Stokes resonance Raman intensity of a tryptophan residue is an excellent probe for the excess energy and the spatial resolution of a single amino acid residue can be achieved. Here, we studied dependence of vibrational energy transfer on the distance in cytochrome b562, which is a heme-containing, four-helix bundle protein. The vibrational energy transfer from the heme group to a single tryptophan residue introduced by site-directed mutagenesis was examined for different heme-tryptophan distances by a quasi-constant length with the periodicity of α helices. Taken together with structural data obtained by molecular dynamics simulations, the energy transfer could be well described by the model of classical thermal diffusion, which suggests that continuum media provide a good approximation of the protein interior, of which the atomic packing density is very high.

Regulatory Switching by Concerted Motions on the Microsecond Time Scale of the Oxygen Sensor Protein FixL.

Signal transduction proteins perceive external stimuli in their sensor module and regulate the biological activities of the effector module, allowing cellular adaptation in response to environmental changes. FixL is a dimeric heme protein kinase that senses the oxygen level in plant root nodules to regulate the transcription of nitrogen fixation genes via the phosphorylation of its cognate transcriptional activator. Dissociation of oxygen from the heme induces conformational changes in the protein, converting it from the inactive form for phosphorylation to the active form. However, how FixL undergoes conformational change to regulate kinase activity upon oxygen dissociation remains poorly understood. Here we report time-resolved ultraviolet resonance Raman spectra showing conformational changes for FixL from Sinorhizobium meliloti. We observed spectral changes with a time constant of about 3 µs, which were oxygen-specific. Furthermore, we found that the conformational changes in the sensor and kinase domains are coupled, enabling allosteric control of kinase activity. Our results demonstrate that concerted structural changes on the microsecond time scale serve as the regulatory switch in FixL.

An Efficient Timer and Sizer of Biomacromolecular Motions.

Life ticks as fast as how proteins move. Computationally expensive molecular dynamics simulation has been the only theoretical tool to gauge the time and sizes of these motions, though barely to their slowest ends. Here, we convert a computationally cheap elastic network model (ENM) into a molecular timer and sizer to gauge the slowest functional motions of structured biomolecules. Quasi-harmonic analysis, fluctuation profile matching, and the Wiener-Khintchine theorem are used to define the "time periods," t, for anharmonic principal components (PCs), which are validated by nuclear magnetic resonance (NMR) order parameters. The PCs with their respective "time periods" are mapped to the eigenvalues (λENM) of the corresponding ENM modes. Thus, the power laws t(ns) = 56.1λENM-1.6 and σ2(Å2) = 32.7λENM-3.0 can be established allowing the characterization of the timescales of NMR-resolved conformers, crystallographic anisotropic displacement parameters, and important ribosomal motions, as well as motional sizes of the latter.

More efficient screening of protein-protein complex model structures for reducing the number of candidates.

Rigid-body protein-protein docking is very efficient in generating tens of thousands of docked complex models (decoys) in a very short time without considering structure change upon binding, but typical docking scoring functions are not necessarily sufficiently accurate to narrow these decoys down to a small number of plausible candidates. Flexible refinements and sophisticated evaluation of the decoys are thus required to achieve more accurate prediction. Since this process is time-consuming, an efficient screening method to reduce the number of decoys is necessary immediately following rigid-body dockings. We attempted to develop an efficient screening method by clustering decoys generated by the rigid-body docking ZDOCK. We introduced the three metrics ligand-root-mean-square deviation (L-RMSD), interface-ligand-RMSD (iL-RMSD), and the fraction of common contacts (FCC), and examined various ranges of cut-offs for clusters to determine the best set of clustering parameters. Although the employed clustering algorithm is simple, it successfully reduced the number of decoys. Using iL-RMSD with a cut-off radius of 8 Å, the number of decoys that contain at least one near-native model with 90% probability decreased from 4,808 to 320, a 93% reduction in the original number of decoys. Using FCC for the clustering step, the top 1,000 success rates, defined as the probability that the top 1,000 models contain at least one near-native structure, reached 97%. We conclude that the proposed method is very efficient in selecting a small number of decoys that include near-native decoys.

Enhancing Biomolecular Sampling with Reinforcement Learning: A Tree Search Molecular Dynamics Simulation Method.

This paper proposes a novel molecular simulation method, called tree search molecular dynamics (TS-MD), to accelerate the sampling of conformational transition pathways, which require considerable computation. In TS-MD, a tree search algorithm, called upper confidence bounds for trees, which is a type of reinforcement learning algorithm, is applied to sample the transition pathway. By learning from the results of the previous simulations, TS-MD efficiently searches conformational space and avoids being trapped in local stable structures. TS-MD exhibits better performance than parallel cascade selection molecular dynamics, which is one of the state-of-the-art methods, for the folding of miniproteins, Chignolin and Trp-cage, in explicit water.

Phagocytosis is mediated by two-dimensional assemblies of the F-BAR protein GAS7.

Phagocytosis is a cellular process for internalization of micron-sized large particles including pathogens. The Bin-Amphiphysin-Rvs167 (BAR) domain proteins, including the FCH-BAR (F-BAR) domain proteins, impose specific morphologies on lipid membranes. Most BAR domain proteins are thought to form membrane invaginations or protrusions by assembling into helical submicron-diameter filaments, such as on clathrin-coated pits, caveolae, and filopodia. However, the mechanism by which BAR domain proteins assemble into micron-scale phagocytic cups was unclear. Here, we show that the two-dimensional sheet-like assembly of Growth Arrest-Specific 7 (GAS7) plays a critical role in phagocytic cup formation in macrophages. GAS7 has the F-BAR domain that possesses unique hydrophilic loops for two-dimensional sheet formation on flat membranes. Super-resolution microscopy reveals the similar assemblies of GAS7 on phagocytic cups and liposomes. The mutations of the loops abolishes both the membrane localization of GAS7 and phagocytosis. Thus, the sheet-like assembly of GAS7 plays a significant role in phagocytosis.

ColDock: Concentrated Ligand Docking with All-Atom Molecular Dynamics Simulation.

We propose a simple but efficient and accurate method to generate protein-ligand complex structures, called Concentrated ligand Docking (ColDock). This method consists of multiple independent molecular dynamics simulations in which ligands are initially distributed randomly around a protein at relatively high concentration (∼100 mM). This condition significantly increases the probability of the ligand exploring the protein surface, which induces spontaneous ligand binding to the correct binding sites within a 100 ns MD. After clustering of the protein-bound ligand poses, representatives of the populationally dominant clusters are considered as predicted ligand poses. We applied ColDock to four cases starting from holo protein structures and showed that ColDock can generate "correct" ligand poses very similar to the crystal complex structures. Correct ligand poses are also well reproduced in three out of four cases started from apo structures, with the exception being a case with an initially closed binding pocket. The results indicate that ColDock can be used as a protein-ligand docking as long as the ligand binding pocket is initially open. Plausible protein-ligand complex structures can be easily generated by conducting the ColDock procedure using standard MD simulation software.

Protein-Ligand Dissociation Simulated by Parallel Cascade Selection Molecular Dynamics.

We investigated the dissociation process of tri-N-acetyl-d-glucosamine from hen egg white lysozyme using parallel cascade selection molecular dynamics (PaCS-MD), which comprises cycles of multiple unbiased MD simulations using a selection of MD snapshots as the initial structures for the next cycle. Dissociation was significantly accelerated by PaCS-MD, in which the probability of rare event occurrence toward dissociation was enhanced by the selection and rerandomization of the initial velocities. Although this complex was stable during 1 µs of conventional MD, PaCS-MD easily induced dissociation within 100-101 ns. We found that velocity rerandomization enhances the dissociation of triNAG from the bound state, whereas diffusion plays a more important role in the unbound state. We calculated the dissociation free energy by analyzing all PaCS-MD trajectories using the Markov state model (MSM), compared the results to those obtained by combinations of PaCS-MD and umbrella sampling (US), steered MD (SMD) and US, and SMD and the Jarzynski equality, and experimentally determined binding free energy. PaCS-MD/MSM yielded results most comparable to the experimentally determined binding free energy, independent of simulation parameter variations, and also gave the lowest standard errors.

Prediction of Perceived Steering Wheel Operation Force by Muscle Activity.

Humans feel forces or weights while grasping and manipulating an object. There is a difference between the physical and perceived forces because the physical characteristics of an object and/or human psychophysical characteristics affect perceived force. Sense of effort plays an important role in deciding the movement made by humans. In this study, we propose a computational method to predict the perceived force by evaluating the muscle activity as a function of effort in the operation of a steering wheel based on a 3D-musculoskeletal model simulation. We found that the perceived-force characteristics depend on the driving posture, though the applied force is the same. We evaluated the results, and showed that the mean of the absolute error is 1.78 N for the experiments conducted on four different vehicles in commercially available.

Effects of water model and simulation box size on protein diffusional motions.

We performed molecular dynamics simulations of ubiquitin with the distinct water models, TIP3P, SPC, SPC/E, and SPC/Fw, in different system sizes with different box shapes. The translational diffusion constants of pure water linearly depend on the effective box length, which is known as finite size effect, whereas the first and second rotational times of pure water are nearly constant. We then observed that both the overall translation and rotational motions of the protein are linearly correlated to the viscosity of pure water. As expected from the finite size effect in pure water, the translational diffusion of the protein is significantly affected by the system size, and rotational diffusion is nearly size-independent. After correction for the finite size effect, the SPC/E and SPC/Fw models reproduce both the translational and rotational motion of the protein relatively well. Thus, water models that reproduce the experimentally derived diffusional properties of pure water accurately are expected to also be suitable for simulating protein diffusion quantitatively.

High anisotropy and frustration: the keys to regulating protein function efficiently in crowded environments.

Highly anisotropic protein dynamics in equilibrium can be observed experimentally or through structural bioinformatics and molecular simulations. This anisotropic nature causes a response, to an external perturbation, along a small number of intrinsic large-amplitude directions as expected from the fluctuation-dissipation theorem. It is also key for controlling specific reactions as stochastic processes in macromolecular crowded environments. Protein anisotropy can be exploited for the calculation of physical properties, such as entropy, which can be employed for binding affinity studies. Energy frustration along soft modes including both global large-amplitude and localized small-amplitude movements is another key feature, as conformational transitions along soft modes, triggered by external perturbations such as the binding of other molecules, can act as a switch to control function.

Salt Bridge Formation between the I-BAR Domain and Lipids Increases Lipid Density and Membrane Curvature.

The BAR domain superfamily proteins sense or induce curvature in membranes. The inverse-BAR domain (I-BAR) is a BAR domain that forms a straight "zeppelin-shaped" dimer. The mechanisms by which IRSp53 I-BAR binds to and deforms a lipid membrane are investigated here by all-atom molecular dynamics simulation (MD), binding energy analysis, and the effects of mutation experiments on filopodia on HeLa cells. I-BAR adopts a curved structure when crystallized, but adopts a flatter shape in MD. The binding of I-BAR to membrane was stabilized by ~30 salt bridges, consistent with experiments showing that point mutations of the interface residues have little effect on the binding affinity whereas multiple mutations have considerable effect. Salt bridge formation increases the local density of lipids and deforms the membrane into a concave shape. In addition, the point mutations that break key intra-molecular salt bridges within I-BAR reduce the binding affinity; this was confirmed by expressing these mutants in HeLa cells and observing their effects. The results indicate that the stiffness of I-BAR is important for membrane deformation, although I-BAR does not act as a completely rigid template.

Drug Targeting Based on a New Concept-Targeting Against TLR4 as an Example.

TLRs are very important players to regulate innate immune responses. TLR4 controls the host defense by sensing an exotic pathogen, such as lipopolysaccharides. At the same time, some endogenous proteins, including HMGB1 and S100A8, could also function to be a ligand to elicit inflammatory reactions. These facts make TLR4 signaling system very complicated. For instance, the application of TLR4 ligands in cancer therapies is desirable for enhancement of anti-tumor immunity in terms of its reparative nature, but undesirable for enhancement of metastatic growth of cancer cells. In this manuscript, in order to make a novel molecular design to disrupt an interaction between TLR4/MD-2 and endogenous ligands, we provide a potential binding style of the TLR4/MD-2 complex with HMGB1 by using their 3D structural data and docking simulations, and also discuss S100A8 binding to TLR4/MD-2.

Mechanism of deep-sea fish α-actin pressure tolerance investigated by molecular dynamics simulations.

The pressure tolerance of monomeric α-actin proteins from the deep-sea fish Coryphaenoides armatus and C. yaquinae was compared to that of non-deep-sea fish C. acrolepis, carp, and rabbit/human/chicken actins using molecular dynamics simulations at 0.1 and 60 MPa. The amino acid sequences of actins are highly conserved across a variety of species. The actins from C. armatus and C. yaquinae have the specific substitutions Q137K/V54A and Q137K/L67P, respectively, relative to C. acrolepis, and are pressure tolerant to depths of at least 6000 m. At high pressure, we observed significant changes in the salt bridge patterns in deep-sea fish actins, and these changes are expected to stabilize ATP binding and subdomain arrangement. Salt bridges between ATP and K137, formed in deep-sea fish actins, are expected to stabilize ATP binding even at high pressure. At high pressure, deep-sea fish actins also formed a greater total number of salt bridges than non-deep-sea fish actins owing to the formation of inter-helix/strand and inter-subdomain salt bridges. Free energy analysis suggests that deep-sea fish actins are stabilized to a greater degree by the conformational energy decrease associated with pressure effect.