MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology

Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation

Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. These methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore the conformational space more broadly. Based on the insights of this analysis, we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here.

Mutations in Dynamic Structural Elements Alter the Kinetics and Fidelity of the Multifunctional Class II Lanthipeptide Synthetase, HalM2

Class II lanthipeptide synthetases (LanM enzymes) catalyze the multistep post-translational modification of genetically encoded precursor peptides into macrocyclic (often antimicrobial) lanthipeptides. The reaction sequence involves dehydration of serine/threonine residues, followed by intramolecular addition of cysteine thiols onto the nascent dehydration sites to construct thioether bridges. LanMs utilize two separate active sites in an iterative yet highly coordinated manner to maintain a remarkable level of regio- and stereochemical control over the multistep maturation. The mechanisms underlying this biosynthetic fidelity remain enigmatic. We recently demonstrated that proper function of the haloduracin β synthetase (HalM2) requires dynamic structural elements scattered across the surface of the enzyme. Here, we perform kinetic simulations, structural analysis of reaction intermediates, hydrogen-deuterium exchange mass spectrometry studies, and molecular dynamics simulations to investigate the contributions of these dynamic HalM2 structural elements to biosynthetic efficiency and fidelity. Our studies demonstrate that a large, conserved loop (HalM2 residues P349-P405) plays essential roles in defining the precursor peptide binding site, facilitating efficient peptide dehydration, and guiding the order of thioether ring formation. Moreover, mutations near the interface of the HalM2 dehydratase and cyclase domains perturb cyclization fidelity and result in aberrant thioether topologies that cannot be corrected by the wild type enzyme, suggesting an element of kinetic control in the normal cyclization sequence. Overall, this work provides the most comprehensive correlation of the structural and functional properties of a LanM enzyme reported to date and should inform mechanistic studies of the biosynthesis of other ribosomally synthesized and post-translationally modified peptide natural products.

Charge-driven condensation of RNA and proteins suggests broad role of phase separation in cytoplasmic environments

Phase separation processes are increasingly being recognized as important organizing mechanisms of biological macromolecules in cellular environments. Well-established drivers of phase separation are multi-valency and intrinsic disorder. Here, we show that globular macromolecules may condense simply based on electrostatic complementarity. More specifically, phase separation of mixtures between RNA and positively charged proteins is described from a combination of multiscale computer simulations with microscopy and spectroscopy experiments. Phase diagrams were mapped out as a function of molecular concentrations in experiment and as a function of molecular size and temperature via simulations. The resulting condensates were found to retain at least some degree of internal dynamics varying as a function of the molecular composition. The results suggest a more general principle for phase separation that is based primarily on electrostatic complementarity without invoking polymer properties as in most previous studies. Simulation results furthermore suggest that such phase separation may occur widely in heterogenous cellular environment between nucleic acid and protein components.

Pathogen-specific antimicrobials engineered de novo through membrane-protein biomimicry

Precision antimicrobials aim to kill pathogens without damaging commensal bacteria in the host, and thus to cure disease without antibiotic-associated dysbiosis. Here, we report the de novo design of a synthetic host defence peptide that targets a specific pathogen by mimicking key molecular features of the pathogen’s channel-forming membrane proteins. By exploiting physical and structural vulnerabilities within the pathogen’s cellular envelope, we designed a peptide sequence that undergoes instructed tryptophan-zippered assembly within the mycolic-acid rich outer membrane of Mycobacterium tuberculosis (Mtb) to specifically kill the pathogen without collateral toxicity towards lung commensal bacteria or host tissue. These ‘mycomembrane-templated’ assemblies elicit rapid mycobactericidal activity, and enhance the potency of antibiotics by improving their otherwise poor diffusion across the rigid Mtb envelope with respect to agents that exploit transmembrane protein channels for antimycobacterial activity. This biomimetic strategy may aid the design of other narrow-spectrum antimicrobial peptides.

Continuous Constant pH Molecular Dynamics Simulations of Transmembrane Proteins

Many membrane channels, transporters, and receptors utilize a pH gradient or proton coupling to drive functionally relevant conformational transitions. Conventional molecular dynamics simulations employ fixed protonation states, thus neglecting the coupling between protonation and conformational equilibria. Here we describe the membrane-enabled hybrid-solvent continuous constant pH molecular dynamics method for capturing atomic details of proton-coupled conformational dynamics of transmembrane proteins. Example protocols from our recent application studies of proton channels and ion/substrate transporters are discussed.

The effect on ion channel of different protonation states of E90 in channelrhodopsin-2: a molecular dynamics simulation

Channelrhodopsin-2 (ChR2) is a cationic channel protein that has been extensively studied in optogenetics. The ion channel is opened via a series of proton transfers and H-bond changes during the photocycle but the detailed mechanism is still unknown. Molecular dynamics (MD) simulations with enhanced sampling were performed on the dark-adapted state (i.e., D470) and two photocycle intermediates (P₁⁵⁰⁰ and P₂³⁹⁰) to study the proton transfer path of the Schiff base and the subsequent conformational changes. The results suggest there are two possible proton transfer pathways from the Schiff base to proton acceptors (i.e., E123 or D253), depending on the protonation of E90. If E90 is protonated in the P₁⁵⁰⁰ state, the proton on the Schiff base will transfer to E123. The polyene chain of 13-cis retinal tilts and opens the channel that detours the blocking central gate (CG) and forms a narrow channel through the transmembrane helices (TM) 2, 3, 6 and 7. In contrast, if E90 deprotonates after retinal isomerization, the primary proton acceptor is D253, and an almost-open channel through TM1, 2, 3 and 7 is generated. The channel diameter is very close to the experimental value. The potential mean force (PMF) suggests that the free energy is extremely low for ions passing through this channel.

With E90 protonated, the proton acceptor of RSBH⁺ is E123 with a narrow channel along TM3; while with E90 deprotonated, proton transfer from RSBH⁺ to D253 generates an approximately open channel along TM2.

Understanding the Structure and Apo Dynamics of the Functionally Active JIP1 Fragment

Recent experiments indicate that the C-Jun amino-terminal kinase-interacting protein 1 (JIP1) binds to and activates the c-Jun N-terminal kinase (JNK) protein. JNK is an integral part of cell apoptosis, and misregulation of this process is a causative factor in diseases such as Alzheimer's disease (AD), obesity, and cancer. It has also been shown that JIP1 may increase the phosphorylation of tau by facilitating the interaction between the tau protein and JNK, which could also be a causative factor in AD. Very little is known about the structure and dynamics of JIP1; however, the amino acid composition of the first 350 residues suggests that it contains an intrinsically disordered region. Molecular dynamics (MD) simulations using AMBER 14 were used to study the structure and dynamics of a functionally active JIP1 10mer fragment to better understand the solution behavior of the fragment. Two microseconds of unbiased MD was performed on the JIP1 10mer fragment in 10 different seeds for a total of 20 μs of simulation time, and from this, seven structurally stable conformations of the 10mer fragment were identified via classical clustering. The 10mer ensemble was also used to build a Markov state model (MSM) that identified four metastable states that encompassed six of the seven conformational families identified by classical dimensional reduction. Based on this MSM, conformational interconversions between the four states occur via two dominant pathways with probability fluxes of 55 and 44% for each individual pathway. Transitions between the initial and final states occur with mean first passage times of 31 (forward) and 16 (reverse) μs.

Intrinsically Disordered Protein Ensembles Shape Evolutionary Rates Revealing Conformational Patterns

Intrinsically disordered proteins (IDPs) lack stable tertiary structure under physiological conditions. The unique composition and complex dynamical behaviour of IDPs make them a challenge for structural biology and molecular evolution studies. Using NMR ensembles, we found that IDPs evolve under a strong site-specific evolutionary rate heterogeneity, mainly originated by different constraints derived from their inter-residue contacts. Evolutionary rate profiles correlate with the experimentally observed conformational diversity of the protein, allowing the description of different conformational patterns possibly related to their structure-function relationships. The correlation between evolutionary rates and contact information improves when structural information is taken not from any individual conformer or the whole ensemble, but from combining a limited number of conformers. Our results suggest that residue contacts in disordered regions constrain evolutionary rates to conserve the dynamic behaviour of the ensemble and that evolutionary rates can be used as a proxy for the conformational diversity of IDPs.

Sampling of the conformational landscape of small proteins with Monte Carlo methods

Computer simulation provides an increasingly realistic picture of large-scale conformational change of proteins, but investigations remain fundamentally constrained by the femtosecond timestep of molecular dynamics simulations. For this reason, many biologically interesting questions cannot be addressed using accessible state-of-the-art computational resources. Here, we report the development of an all-atom Monte Carlo approach that permits the modelling of the large-scale conformational change of proteins using standard off-the-shelf computational hardware and standard all-atom force fields. We demonstrate extensive thermodynamic characterization of the folding process of the α-helical Trp-cage, the Villin headpiece and the β-sheet WW-domain. We fully characterize the free energy landscape, transition states, energy barriers between different states, and the per-residue stability of individual amino acids over a wide temperature range. We demonstrate that a state-of-the-art intramolecular force field can be combined with an implicit solvent model to obtain a high quality of the folded structures and also discuss limitations that still remain.

Transglutaminase-Mediated Cross-Linking of Tropoelastin to Fibrillin Stabilises the Elastin Precursor Prior to Elastic Fibre Assembly

Elastic fibres are essential components of all mammalian elastic tissues such as blood vessels, lung and skin, and are critically important for the mechanical properties they endow. The main components of elastic fibres are elastin and fibrillin, where correct formation of elastic fibres requires a fibrillin microfibril scaffold for the deposition of elastin. It has been demonstrated previously that the interaction between fibrillin and tropoelastin, the elastin precursor, increases the rate of assembly of tropoelastin. Furthermore, tropoelastin and fibrillin can be cross-linked by transglutaminase-2, but the function of cross-linking on their elastic properties is yet to be elucidated. Here we show that transglutaminase cross-linking supports formation of a 1:1 stoichiometric fibrillin-tropoelastin complex. SAXS data show that the complex retains features of the individual proteins but is elongated supporting end-to-end assembly. Elastic network models were constructed to compare the dynamics of tropoelastin and fibrillin individually as well as in the cross-linked complex. Normal mode analysis was performed to determine the structures' most energetically favourable, biologically accessible motions which show that within the complex, tropoelastin is less mobile and this molecular stabilisation extends along the length of the tropoelastin molecule to regions remote from the cross-linking site. Together, these data suggest a long-range stabilising effect of cross-linking that occurs due to the covalent linkage of fibrillin to tropoelastin. This work provides insight into the interactions of tropoelastin and fibrillin and how cross-link formation stabilises the elastin precursor so it is primed for elastic fibre assembly.

Alternative proton-binding site and long-distance coupling in Escherichia coli sodium-proton antiporter NhaA

Escherichia coli NhaA is a prototypical sodium-proton antiporter responsible for maintaining cellular ion and volume homeostasis by exchanging two protons for one sodium ion; despite two decades of research, the transport mechanism of NhaA remains poorly understood. Recent crystal structure and computational studies suggested Lys300 as a second proton-binding site; however, functional measurements of several K300 mutants demonstrated electrogenic transport, thereby casting doubt on the role of Lys300. To address the controversy, we carried out state-of-the-art continuous constant pH molecular dynamics simulations of NhaA mutants K300A, K300R, K300Q/D163N, and K300Q/D163N/D133A. Simulations suggested that K300 mutants maintain the electrogenic transport by utilizing an alternative proton-binding residue Asp133. Surprisingly, while Asp133 is solely responsible for binding the second proton in K300R, Asp133 and Asp163 jointly bind the second proton in K300A, and Asp133 and Asp164 jointly bind two protons in K300Q/D163N. Intriguingly, the coupling between Asp133 and Asp163 or Asp164 is enabled through the proton-coupled hydrogen-bonding network at the flexible intersection of two disrupted helices. These data resolve the controversy and highlight the intricacy of the compensatory transport mechanism of NhaA mutants. Alternative proton-binding site and proton sharing between distant aspartates may represent important general mechanisms of proton-coupled transport in secondary active transporters.

Comparison and Evaluation of Force Fields for Intrinsically Disordered Proteins

Molecular dynamics (MD) simulations of six upgraded empirical force fields were compared and evaluated with short peptides, intrinsically disordered proteins, and folded proteins using trajectories of 1, 1.5, 5, or 10 μs (five replicates of 200 ns, 300 ns, 1 μs, or 2 μs) for each system. Previous studies have shown that different force fields, water models, simulation methods, and parameters can affect simulation outcomes. Here, the MD simulations were done in an explicit solvent with RS-peptide, HEWL19, HIV-rev, β amyloid (Aβ)-40, Aβ-42, phosphodiesterase-γ, CspTm, and ubiquitin using ff99IDPs, ff14IDPs, ff14IDPSFF, ff03w, CHARMM36m, and CHARMM22* force fields. The IDP ensembles generated by six all-atom empirical force fields were compared against NMR data. Despite using identical starting structures and simulation parameters, ensembles obtained with different force fields exhibit significant differences in NMR RMDs, secondary structure contents, and global properties such as the radius of gyration. The intrinsically disordered protein (IDP)-specific force fields could substantially reproduce the experimental observables in force field comparison: they have the lowest error in chemical shifts and J-couplings for short peptides/proteins, reasonably well for large IDPs and reasonably well with the radius of gyration. A high population of disorderness was observed in the IDP-specific force field for the IDP ensemble with a fraction of β sheets for β-amyloids. CHARMM22* performs better for many observables; however, it still has a preference toward the helicity for short peptides. The results of β-amyloid 42 starting from two different initial structures (Aβ42^1Z0Q and Aβ42^model) were also compared with DSSP and NMR data. The results obtained with IDP-specific force fields within 2 μs simulation time are similar, even though starting from different structures. The current force fields perform equally well for folded proteins. The results of currently developed or modified force fields for IDPs are capable of enlightening the overall performance of the force field for disordered as well as folded proteins, thereby contributing to force field development.

Structure of the PCBP2/stem-loop IV complex underlying translation initiation mediated by the poliovirus type I IRES

The poliovirus type I IRES is able to recruit ribosomal machinery only in the presence of host factor PCBP2 that binds to stem-loop IV of the IRES. When PCBP2 is cleaved in its linker region by viral proteinase 3CD, translation initiation ceases allowing the next stage of replication to commence. Here, we investigate the interaction of PCBP2 with the apical region of stem-loop IV (SLIVm) of poliovirus RNA in its full-length and truncated form. CryoEM structure reconstruction of the full-length PCBP2 in complex with SLIVm solved to 6.1 Å resolution reveals a compact globular complex of PCBP2 interacting with the cruciform RNA via KH domains and featuring a prominent GNRA tetraloop. SEC-SAXS, SHAPE and hydroxyl-radical cleavage establish that PCBP2 stabilizes the SLIVm structure, but upon cleavage in the linker domain the complex becomes more flexible and base accessible. Limited proteolysis and REMSA demonstrate the accessibility of the linker region in the PCBP2/SLIVm complex and consequent loss of affinity of PCBP2 for the SLIVm upon cleavage. Together this study sheds light on the structural features of the PCBP2/SLIV complex vital for ribosomal docking, and the way in which this key functional interaction is regulated following translation of the poliovirus genome.

Identification of Intrinsic Disorder in Complexes from the Protein Data Bank

Background: Intrinsically disordered proteins or regions (IDPs or IDRs) lack stable structures in solution, yet often fold upon binding with partners. IDPs or IDRs are highly abundant in all proteomes and represent a significant modification of sequence → structure → function paradigm. The Protein Data Bank (PDB) includes complexes containing disordered segments bound to globular proteins, but the molecular mechanisms of such binding interactions remain largely unknown. Results: In this study, we present the results of various disorder predictions on a nonredundant set of PDB complexes. In contrast to their structural appearances, many PDB proteins were predicted to be disordered when separated from their binding partners. These predicted-to-be-disordered proteins were observed to form structures depending upon various factors, including heterogroup binding, protein/DNA/RNA binding, disulfide bonds, and ion binding. Conclusions: This study collects many examples of disorder-to-order transition in IDP complex formation, thus revealing the unusual structure–function relationships of IDPs and providing an additional support for the newly proposed paradigm of the sequence → IDP/IDR ensemble → function.

Exploring pH Dependent Host/Guest Binding Affinities

When the electrostatic environment surrounding binding partners changes between unbound and bound states, the net uptake or release of a proton is possible by either binding partner. This process is pH-dependent in that the free energy required to uptake or release the proton varies with pH. This pH-dependence is typically not considered in conventional free energy methods where the use of fixed protonation states is the norm. In the present paper, we apply a simple two-step approach to calculate the pH-dependent binding free energy of a model cucubit[7]uril host/guest system. By use of λ-dynamics with an enhanced sampling protocol, adaptive landscape flattening, pK_a shifts and reference binding free energies upon complexation were determined. This information enables the construction of pH-dependent binding profiles that accurately capture the pK_a shifts and reproduce binding free energies at the different pH conditions that were observed experimentally. Our calculations illustrate a general framework for computing pH-dependent binding free energies but also point to some issues in modeling the molecular charge distributions within this series of molecules with CGenFF. However, by introducing some minor charge modifications to the CGenFF force field, we saw significant improvement in accuracy of the calculated pK_a shifts.

Identification of a Broad-Spectrum Viral Inhibitor Targeting a Novel Allosteric Site in the RNA-Dependent RNA Polymerases of Dengue Virus and Norovirus

All RNA viruses encode the RNA-dependent RNA polymerase (RdRp) which replicates and transcribes viral RNA. This essential viral enzyme does not exist in mammalian cells, thus presents a main target for the development of antiviral drugs with potential pan-antiviral activity. In this study, we take advantage of the structurally equivalent site in the dengue virus (DENV) RdRp, the N-pocket, and in the human norovirus (hNV) RdRp, the B-site, and performed a parallel structure-based virtual screening to discover compounds that can inhibit the RdRps of both hNV and DENV. We successfully identified a small molecule called Entrectinib (RAI-13) as a potent inhibitor of both hNV and DENV infection. Specifically, RAI-13 binds directly to hNV and DENV RdRps, effectively inhibits the polymerase activity in the in vitro biochemical assays, and exhibits does-responsive inhibition of murine norovirus (MNV) and DENV2 infection with IC50 values of 2.01 and 2.43 μM, respectively. Most promisingly, RAI-13 inhibits hepatitis C virus (HCV) infection by 95% at the 2 μM concentration. We have therefore discovered a small molecule compound that targets an allosteric site that is shared by different viral RdRps and strongly inhibits multiple pathogenic RNA viruses, thus holding the potential of being developed into a broad-spectrum antiviral drug.

Higher Accuracy Achieved for Protein-Ligand Binding Pose Prediction by Elastic Network Model-Based Ensemble Docking

Molecular docking plays an indispensable role in predicting the receptor-ligand interactions in which the protein receptor is usually kept rigid, whereas the ligand is treated as being flexible. Because of the inherent flexibility of proteins, the binding pocket of apo receptors might undergo significant conformational rearrangement upon ligand binding, which limits the prediction accuracy of docking. Here, we present an iterative anisotropic network model (iterANM)-based ensemble docking approach, which generates multiple holo-like receptor structures starting from the apo receptor and incorporates protein flexibility into docking. In a validation data set consisting of 233 chemically diverse cyclin-dependent kinase 2 (CDK2) inhibitors, the iterANM-based ensemble docking achieves higher capacity to reproduce native-like binding poses compared with those using single apo receptor conformation or conformational ensemble from molecular dynamics simulations. The prediction success rate within the top5-ranked binding poses produced by the iterANM can further be improved through reranking with the molecular mechanics-Poisson-Boltzmann surface area method. In a smaller data set with 58 CDK2 inhibitors, the iterANM-based ensemble shows a higher success rate compared with the flexible receptor-based docking procedure AutoDockFR and other receptor conformation generation approaches. Further, an additional docking test consisting of 10 diverse receptor-ligand combinations shows that the iterANM is robustly applicable for different receptor structures. These results suggest the iterANM-based ensemble docking as an accurate, efficient, and practical framework to predict the binding mode of a ligand for receptors with flexibility.

Accelerated CDOCKER with GPUs, Parallel Simulated Annealing, and Fast Fourier Transforms

Fast Fourier transform (FFT)-based protein ligand docking together with parallel simulated annealing for both rigid and flexible receptor docking are implemented on graphical processing unit (GPU) accelerated platforms to significantly enhance the throughput of the CDOCKER and flexible CDOCKER - the docking algorithms in the CHARMM program for biomolecule modeling. The FFT-based approach for docking, first applied in protein-protein docking to efficiently search for the binding position and orientation of proteins, is adapted here to search ligand translational and rotational spaces given a ligand conformation in protein-ligand docking. Running on GPUs, our implementation of FFT docking in CDOCKER achieves a 15 000 fold speedup in the ligand translational and rotational space search in protein-ligand docking problems. With this significant speedup it becomes practical to exhaustively search ligand translational and rotational space when docking a rigid ligand into a protein receptor. We demonstrate in this paper that this provides an efficient way to calculate an upper bound for docking accuracy in the assessment of scoring functions for protein-ligand docking, which can be useful for improving scoring functions. The parallel molecular dynamics (MD) simulated annealing, also running on GPUs, aims to accelerate the search algorithm in CDOCKER by running MD simulated annealing in parallel on GPUs. When utilized as part of the general CDOCKER docking protocol, acceleration in excess of 20 times is achieved. With this acceleration, we demonstrate that the performance of CDOCKER for redocking is significantly improved compared with three other popular protein-ligand docking programs on two widely used protein ligand complex data sets: the Astex diverse set and the SB2012 test set. The flexible CDOCKER is similarly improved by the parallel MD simulated annealing on GPUs. Based on the results presented here, we suggest that the accelerated CDOCKER platform provides a highly competitive docking engine for both rigid-receptor and flexible-receptor docking studies and will further facilitate continued improvement in the physics-based scoring function employed in CDOCKER docking studies.

Environment-Specific Force Field for Intrinsically Disordered and Ordered Proteins

The need for accurate and efficient force fields for modeling 3D structures of macrobiomolecules and in particular intrinsically disordered proteins (IDPs) has increased with recent findings to associate IDPs and human diseases. However, most conventional protein force fields and recent IDP-specific force fields are limited in reproducing accurate structural features of IDPs. Here, we present an environmental specific precise force field (ESFF1) based on CMAP corrections of 71 different sequence environments to improve the accuracy and efficiency of MD simulation for both IDPs and folded proteins. MD simulations of 84 different short peptides, IDPs, and structured proteins show that ESFF1 can accurately reproduce spectroscopic properties for different peptides and proteins whether they are disordered or ordered. The successful ab initio folding of five fast-folding proteins further supports the reliability of ESFF1. The extensive analysis documented here shows that ESFF1 is able to achieve a reasonable balance between ordered and disordered states in protein simulations.

Structures and dynamics of DNA complexes of the desmethyl analog of the cytotoxin MLN944: Insights into activity when a methyl isn't futile

Structure activity relationships for tricyclic-carboxamide topoisomerase II poisons indicate that cytotoxicity is enhanced by the presence of methyl, and other, groups in the position peri to the carboxamide. Linked dimers of phenazine-1-carboxamides are potent cytotoxins and one phenazine dimer, MLN944 (alternatively XR5944), has been in clinical trial. MLN944 is a template inhibitor of transcription, whereas corresponding monomers are not. Nevertheless, its cytotoxic potency is also diminished by removal of its peri methyl groups. Here, we describe NMR and molecular dynamic studies of the interaction of desmethyl MLN944 with d(ATGCAT)₂ , d(TATGCATA)₂ , and d(TACGCGTA)₂ to investigate the influence of the nine-methyl group on the structure of MLN944 complexes. As with MLN944, the carboxamide group hydrogen bonds to the phenazine ring nitrogen, the ligand sandwiches the central GC base pairs in the major groove, and the protonated linker amines hydrogen bond primarily to the O6 atom of the guanines. Molecular dynamics studies reveal that the linker exists in multiple conformations, none of which produce an ideal set of hydrogen bonds. In distinction, however, the carboxamide-to-phenazine ring nitrogen hydrogen bond is weaker, the overall helix winding is less and the NMR resonances are broader in the desmethyl complexes. Exchange between free and complexed DNA, quantified using two-dimensional NOESY spectra, is faster for the desmethyl MLN944 complexes than for MLN944 complexes. Overall, the data suggest that desmethyl MLN944 DNA complexes are "looser" and more unwound at the binding site, leading to faster dissociation rates, which could account for the diminished efficacy of the desmethyl analog.

Disorder-Order Transitions in Conformational Selection of a Peptide by Ebola Virus Nucleoprotein

This study presents parallel-tempering lattice Monte Carlo simulations based on the side-chain-only (SICHO) model for calculating the conformational landscape of a 28-residue intrinsically disordered peptide extracted from the Ebola virus protein VP35. The central issue is the applicability of the SICHO potential energy function and in general coarse-grained (CG) representations of intermediate resolution for modeling large-scale conformational heterogeneity that includes both folded and unstructured peptide states. Crystallographic data shows that the peptide folds in a 4₁₀-helix-turn-3₁₀-helix topology upon complex formation with the Ebola virus nucleoprotein, whereas in isolation, the peptide transitions to a disordered conformational ensemble as observed in circular dichroism experiments. The simulation reveals a potential of mean force that displays conformational diversity along the helix-forming reaction coordinate consistent with disorder-order transitions, yet unexpectedly the bound topology is poorly sampled, and a population shift to an unstructured state incurs a significant free-energy penalty. Applying an elastic network interpolation model suggests a hybrid binding mechanism through conformational selection of the 4₁₀-helix followed by an induced fit of the 3₁₀-helix. A comparison of the CG model with previously reported all-atom CHARMM-based simulations highlights a lattice-based approach that is computationally fast and with the correct parameterization yields good resolution to modeling conformational plasticity.

Methodology for Further Thermostabilization of an Intrinsically Thermostable Membrane Protein Using Amino Acid Mutations with Its Original Function Being Retained

We develop a new methodology best suited to the identification of thermostabilizing mutations for an intrinsically stable membrane protein. The recently discovered thermophilic rhodopsin, whose apparent midpoint temperature of thermal denaturation T_m is measured to be ∼91.8 °C, is chosen as a paradigmatic target. In the methodology, we first regard the residues whose side chains are missing in the crystal structure of the wild type (WT) as the "residues with disordered side chains," which make no significant contributions to the stability, unlike the other essential residues. We then undertake mutating each of the residues with disordered side chains to another residue except Ala and Pro, and the resultant mutant structure is constructed by modifying only the local structure around the mutated residue. This construction is based on the postulation that the structure formed by the other essential residues, which is nearly optimized in such a highly stable protein, should not be modified. The stability changes arising from the mutations are then evaluated using our physics-based free-energy function (FEF). We choose the mutations for which the FEF is much lower than for the WT and test them by experiments. We successfully find three mutants that are significantly more stable than the WT. A double mutant whose T_m reaches ∼100 °C is also discovered.

Molecular dynamics reveals insight into how N226P and H227Y mutations affect maltose binding in the active site of α-glucosidase II from European honeybee, Apis mellifera

European honeybee, Apis mellifera, produces α-glucosidase (HBGase) that catalyzes the cleavage of an α-glycosidic bond of the non-reducing end of polysaccharides and has potential applications for malt hydrolysis in brewing industry. Characterized by their substrate specificities, HBGases have three isoforms including HBGase II, which prefers maltose to sucrose as a substrate. Previous study found that the catalytic efficiency of maltose hydrolysis of N226P mutant of HBGase II was higher than that of the wild type (WT), and the catalytic efficiency of maltose hydrolysis of WT was higher than those of H227Y and N226P-H227Y mutants. We hypothesized that N226P mutation probably caused maltose to bind with better affinity and position/orientation for hydrolysis than WT, while H227Y and N226P-H227Y mutations caused maltose to bind with worse affinity and position/orientation for hydrolysis than WT. Using this hypothesis, we performed molecular dynamics on the catalytically competent binding conformations of maltose/WT, maltose/N226P, maltose/H227Y, and maltose/N226P-H227Y complexes to elucidate effects of N226P and H227Y mutations on maltose binding in HBGase II active site. Our results reasonably support this hypothesis because the N226P mutant had better binding affinity, higher number of important binding residues, strong and medium hydrogen bonds as well as shorter distance between atoms necessary for hydrolysis than WT, while the H227Y and N226P-H227Y mutants had worse binding affinities, lower number of important binding residues and strong hydrogen bonds as well as longer distances between atoms necessary for hydrolysis than WT. Moreover, results of binding free energy and hydrogen bond interaction of residue 227 support the role of H227 as a maltose preference residue, as proposed by previous studies. Our study provides important and novel insight into how N226P and H227Y mutations affect maltose binding in HBGase II active site. This knowledge could potentially be used to engineer HBGase II to improve its efficiency.

Molecular Details of a Salt Bridge and Its Role in Insulin Fibrillation by NMR and Raman Spectroscopic Analysis

Insulin, a simple polypeptide hormone with huge biological importance, has long been known to self-assemble in vitro and form amyloid-like fibrillar aggregates. Utilizing high-resolution NMR, Raman spectroscopy, and computational analysis, we demonstrate that the fluctuation of the carboxyl terminal (C-ter) residues of the insulin B-chain plays a key role in the growth phase of insulin aggregation. By comparing the insulin sourced from bovine, human, and the modified glargine (GI), we observed reduced aggregation propensity in the GI variant, resulting from two additional Arg residues at its C-ter. NMR analysis showed atomic contacts and residue-specific interactions, particularly the salt bridge and H-bond formed among the C-ter residues Arg31^B, Lys29^B, and Glu4^A. These inter-residue interactions were reflected in strong nuclear Overhauser effects among Arg31^BδH-Glu4^AδH and Lys29^BδHs-Glu4^AδH in GI, as well as the associated downfield chemical shift of several A-chain amino terminal (N-ter) residues. The two additional Arg residues of GI, Arg31^B and Arg32^B, enhanced the stability of the GI native structure by strengthening the Arg31^B, Lys29^B, and Glu4^A salt bridge, thus reducing extensive thermal distortion and fluctuation of the terminal residues. The high stability of the salt bridge retards tertiary collapse, a crucial biochemical event for oligomerization and subsequent fibril formation. Circular dichroism and Raman spectroscopic measurement also suggest slow structural distortion in the early phase of the aggregation of GI because of the restricted mobility of the C-ter residues as explained by NMR. In addition, the structural and dynamic parameters derived from molecular dynamics simulations of insulin variants highlight the role of residue-specific contacts in aggregation and amyloid-like fibril formation.

Inhibition Mechanism of Indoleamine 2, 3-Dioxygenase 1 (IDO1) by Amidoxime Derivatives and Its Revelation in Drug Design: Comparative Molecular Dynamics Simulations

For cancer treatment, in addition to the three standard therapies of surgery, chemotherapy, and radiotherapy, immunotherapy has become the fourth internationally-recognized alternative treatment. Indoleamine 2, 3-dioxygenase 1 (IDO1) catalyzes the conversion of tryptophan to kynurenine causing lysine depletion, which is an important target in the research and development of anticancer drugs. Epacadostat (INCB024360) is currently one of the most potent IDO1 inhibitors, nevertheless its inhibition mechanism still remains elusive. In this work, comparative molecular dynamics simulations were performed to reveal that the high inhibitory activity of INCB024360 mainly comes from two aspects: disturbing the ligand delivery tunnel and then preventing small molecules such as oxygen and water molecules from accessing the active site, as well as hindering the shuttle of substrate tryptophan with product kynurenine through the heme binding pocket. The scanning of key residues showed that L234 and R231 residues both were crucial to the catalytic activity of IDO1. With the association with INCB024360, L234 forms a stable hydrogen bond with G262, which significantly affects the spatial position of G262-A264 loop and then greatly disturbs the orderliness of ligand delivery tunnel. In addition, the cleavage of hydrogen bond between G380 and R231 increases the mobility of the GTGG conserved region, leading to the closure of the substrate tryptophan channel. This work provides new ideas for understanding action mechanism of amidoxime derivatives, improving its inhibitor activity and developing novel inhibitors of IDO1.

Exploring Conformational Change of Adenylate Kinase by Replica Exchange Molecular Dynamic Simulation

Replica exchange molecular dynamics (REMD) simulation is a popular enhanced sampling method that is widely used for exploring the atomic mechanism of protein conformational change. However, the requirement of huge computational resources for REMD, especially with the explicit solvent model, largely limits its application. In this study, the availability and efficiency of a variant of velocity-scaling REMD (vsREMD) was assessed with adenylate kinase as an example. Although vsREMD achieved results consistent with those from conventional REMD and experimental studies, the number of replicas required for vsREMD (30) was much less than that for conventional REMD (80) to achieve a similar acceptance rate (∼0.2), demonstrating high efficiency of vsREMD to characterize the protein conformational change and associated free-energy profile. Thus, vsREMD is a highly efficient approach for studying the large-scale conformational change of protein systems.

Flipped regiospecificity in L434F mutant of 8-lipoxygenase

Conformational change of Phe434 controls regio- and stereospecificity of L434F lipoxygenase catalysis.

The misfolding mechanism of the key fragment R3 of tau protein: a combined molecular dynamics simulation and Markov state model study

All-atom molecular dynamics (MD) simulation combined with Markov state model (MSM) were used to uncover the structural characteristics and misfolding mechanism of the key R3 fragment of tau protein at the atomic level.

Control of Protein Conformation and Orientation on Graphene

Graphene-based biosensors have attracted considerable attention due to their advantages of label-free detection and high sensitivity. Many such biosensors utilize noncovalent van der Waals force to attach proteins onto graphene surface while preserving graphene's high conductivity. Maintaining the protein structure without denaturation/substantial conformational change and controlling proper protein orientation on the graphene surface are critical for biosensing applications of these biosensors fabricated with proteins on graphene. Based on the knowledge we obtained from our previous experimental study and computer modeling of amino acid residual level interactions between graphene and peptides, here we systemically redesigned an important protein for better conformational stability and desirable orientation on graphene. In this paper, immunoglobulin G (IgG) antibody-binding domain of protein G (protein GB1) was studied to demonstrate how we can preserve the protein native structure and control the protein orientation on graphene surface by redesigning protein mutants. Various experimental tools including sum frequency generation vibrational spectroscopy, attenuated total refection-Fourier transform infrared spectroscopy, fluorescence spectroscopy, and circular dichroism spectroscopy were used to study the protein GB1 structure on graphene, supplemented by molecular dynamics simulations. By carefully designing the protein GB1 mutant, we can avoid strong unfavorable interactions between protein and graphene to preserve protein conformation and to enable the protein to adopt a preferred orientation. The methodology developed in this study is general and can be applied to study different proteins on graphene and beyond. With the knowledge obtained from this research, one could apply this method to optimize protein function on surfaces (e.g., to enhance biosensor sensitivity).

Disclosing the Mechanism of Spontaneous Aggregation and Template-Induced Misfolding of the Key Hexapeptide (PHF6) of Tau Protein Based on Molecular Dynamics Simulation

The microtubule-associated protein tau is critical for the development and maintenance of the nervous system. Tau dysfunction is associated with a variety of neurodegenerative diseases called tauopathies, which are characterized by neurofibrillary tangles formed by abnormally aggregated tau protein. Studying the aggregation mechanism of tau protein is of great significance for elucidating the etiology of tauopathies. The hexapeptide ³⁰⁶VQIVYK³¹¹ (PHF6) of R3 has been shown to play a vital role in promoting tau aggregation. In this study, long-term all-atom molecular dynamics simulations in explicit solvent were performed to investigate the mechanisms of spontaneous aggregation and template-induced misfolding of PHF6, and the dimerization at the early stage of nucleation was further specifically analyzed by the Markov state model (MSM). Our results show that PHF6 can spontaneously aggregate to form multimers enriched with β-sheet structure and the β-sheets in multimers prefer to exist in a parallel way. It is observed that PHF6 monomer can be induced to form a β-sheet structure on either side of the template but in a different way. In detail, the β-sheet structure is easier to form on the left side but does not extend well, but on the right side, the monomer can form the extended β-sheet structure. Furthermore, MSM analysis shows that the formation of dimer mainly occurs in three steps. First, the separated monomers collide with each other at random orientations, and then a dimer with short β-sheet structure at the N-terminal forms; finally, β-sheets elongate to form an extended parallel β-sheet dimer. During these processes, multiple intermediate states are identified and multiple paths can form a parallel β-sheet dimer from the disordered coil structure. Moreover, the residues I308, V309, and Y310 play an essential role in the dimerization. In a word, our results uncover the aggregation and misfolding mechanism of PHF6 from the atomic level, which can provide useful theoretical guidance for rational design of effective therapeutic drugs against tauopathies.

Extensive tests and evaluation of the CHARMM36IDPSFF force field for intrinsically disordered proteins and folded proteins

Intrinsically disordered proteins (IDPs) have received increasing attention in recent studies due to their structural heterogeneity and critical biological functions. To fully understand the structural properties and determine accurate ensembles of IDPs, molecular dynamics (MD) simulation was widely used to sample diverse conformations and reveal the structural dynamics. However, the classical state-of-the-art force fields perform well for folded proteins while being unsatisfactory for the simulations of disordered proteins reported in many previous studies. Thus, improved force fields were developed to precisely describe both folded proteins and disordered proteins. Preliminary tests show that our newly developed CHARMM36IDPSFF (C36IDPSFF) force field can well reproduce the experimental observables of several disordered proteins, but more tests on different types of proteins are needed to further evaluate the performance of C36IDPSFF. Here, we extensively simulate short peptides, disordered proteins, and fast-folding proteins as well as folded proteins, and compare the simulated results with the experimental observables. The simulation results show that C36IDPSFF could substantially reproduce the experimental observables for most of the tested proteins but some limitations are also found in the radius of gyration of large disordered proteins and the stability of fast-folding proteins. This force field will facilitate large scale studies of protein structural dynamics and functions using MD simulations.

Combination of coarse-grained molecular dynamics simulations and small-angle X-ray scattering experiments

The combination of molecular dynamics (MD) simulations and small-angle X-ray scattering (SAXS), called the MD-SAXS method, is efficient for investigating protein dynamics. To overcome the time-scale limitation of all-atom MD simulations, coarse-grained (CG) representations are often utilized for biomolecular simulations. In this study, we propose a method to combine CG MD simulations with SAXS, termed the CG-MD-SAXS method. In the CG-MD-SAXS method, the scattering factors of CG particles for proteins and nucleic acids are evaluated using high-resolution structural data in the Protein Data Bank, and the excluded volume and the hydration shell are modeled using two adjustable parameters to incorporate solvent effects. To avoid overfitting, only the two parameters are adjusted for an entire structure ensemble. To verify the developed method, theoretical SAXS profiles for various proteins, DNA/RNA, and a protein-RNA complex are compared with both experimental profiles and theoretical profiles obtained by the all-atom representation. In the present study, we applied the CG-MD-SAXS method to the Swi5-Sfr1 complex and three types of nucleosomes to obtain reliable ensemble models consistent with the experimental SAXS data.

Gō model revisited

This review discusses Gō models broadly used in biomolecular simulations. I start with a brief description of the original lattice model study by Nobuhiro Gō. Then, the theory of protein folding behind Gō model, free energy approaches, and off-lattice Gō models are reviewed. I also mention a stringent test for the assumption in Gō models given from all-atom molecular dynamics simulations. Subsequently, I move to application of Gō models to protein dynamical functions. Various extension of Gō models is also reviewed. Finally, some publicly available tools to use Gō models are listed.

Well-Balanced Force Field ff03CMAP for Folded and Disordered Proteins

Molecular dynamics simulation as an important complement of experiment is widely used to study protein structures and functions. However, previous studies indicate that the current force fields cannot, simultaneously, provide accurate descriptions of folded proteins and intrinsically disordered proteins (IDPs). Therefore, a correction maps (CMAP)-optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of folded proteins and IDPs. Extensive validations of short peptides, folded proteins, disordered proteins, and fast-folding proteins show that simulated chemical shifts, J-coupling constants, order parameters, and residual dipolar couplings (RDCs) with the ff03CMAP force field are in very good agreement with nuclear magnetic resonance measurements and are more accurate than other ff03-series force fields. The influence of solvent models was also investigated. It was found that the combination of ff03CMAP/TIP4P-Ew is suitable for folded proteins, and that of ff03CMAP/TIP4PD is better for disordered proteins. These findings confirm that the newly developed force field ff03CMAP can improve the balance of conformer sampling between folded proteins and IDPs.

Delineation of a new structural motif involving NHN γ-turn

Macromolecules are characterized by distinctive arrangement of hydrogen bonds. Different patterns of hydrogen bonds give rise to distinct and stable structural motifs. An analysis of 4114 non-redundant protein chains reveals the existence of a three-residue, (i - 1) to (i + 1), structural motif, having two hydrogen-bonded five-membered pseudo rings (the first, an NH···OC involving the first residue, and the second being NH∙∙∙N involving the last two residues), separated by a peptide bond. There could be an additional hydrogen bond between the side-chain at (i-1) and the main-chain NH of (i + 1). The average backbone torsion angles of -76(±21)° and - 12(±17)° at i creates a tight turn in the polypeptide chain, akin to a γ-turn. Indeed, a search of three-residue fragments with restriction on the terminal C^α ···C^α distance and the existence of the two pseudo rings on either side revealed the presence 14 846 cases of a variant, termed NHN γ-turn, distinct from the NHO γ-turn (2032 cases) that has traditionally been characterized by the presence of NHO hydrogen bond linking the terminal main-chain atoms. As in the latter, the newly identified γ-turns are also of two types-classical and inverse, occurring in the ratio of 1:6. The propensities of residues to occur in these turns and their secondary structural features have been enumerated. An understanding of these turns would be useful for structure prediction and loop modeling, and may serve as models to represent some of the unfolded state or disordered region in proteins.

Thermal Stability of Peptide Nucleic Acid Complexes

Peptide nucleic acid (PNA) is a neutral nucleic acid analogue that base pairs with itself and natural nucleic acids. PNA-nucleic acid complexes are more thermally stable than the corresponding complexes of natural nucleic acids. In addition, PNA is biostable and thus used in many antisense and antigene applications to block functional RNA or DNA via sequence-specific interactions. We have recently developed force field parameters for molecular dynamics (MD) simulations of PNA and PNA-involving duplexes with natural nucleic acids. In this work, we provide the first application of this force field to biologically relevant PNA sequences and their complexes with RNA. We investigated thermal stabilities of short PNA-PNA, PNA-RNA, and RNA-RNA duplexes using UV-monitored thermal denaturation experiments and MD simulations at ambient and elevated temperatures. The simulations show a two-state melting transition and reproduce the thermal stability from melting experiments, with PNA-PNA being the most and RNA-RNA the least stable. The PNA-PNA duplex also displays the highest activation energy for melting. The atomistic details of unfolding of PNA duplexes suggest that all PNA-PNA bases melt concomitantly, whereas the RNA-RNA and PNA-RNA are destabilized from the termini toward the central part of the duplexes.

Exploring the Ligand Binding/Unbinding Pathway by Selectively Enhanced Sampling of Ligand in a Protein-Ligand Complex

Understanding the protein-ligand binding is of fundamental biological interest and is essential for structure-based drug design. The difficulty in capturing the dynamic process, however, poses a great challenge for current experimental and theoretical simulation techniques. A selective integrated-tempering-sampling molecular dynamics (SITSMD) method offering an option for selectively enhanced sampling of the ligand in a protein-ligand complex was utilized to quantitatively illuminate the binding of benzamidine to the wild-type trypsin protease and its two mutants (S214E and S214K). The SITSMD simulations could produce consistent results as the extensive conventional MD simulation and gave additional insights into the binding pathway for the test protein-ligand complex system using significantly saved computational resource and time, indicating the potential of such a method in investigating protein-ligand binding. Additionally, the simulations identified the different roles of trypsin-benzamidine van der Waals (vdW) and electrostatic interactions in the binding: the former interaction works as the driving force for dragging the benzamidine close to the native binding pocket, and the latter interaction mainly contributes to stabilizing the benzamidine inside the pocket. The S214E mutation introduces more favorable electrostatic interactions, and as a result, both vdW and electrostatic interactions drive the benzamidine binding, lowering the binding and unbinding free energy barrier. In contrast, the S214K mutation prohibits the binding of the benzamidine to the native ligand binding pocket by introducing disliked charge-charge interactions. In summary, these findings suggest that the change in specific residues could modify the protein druggability, including the binding kinetics and thermodynamics.

Predicting changes in protein stability caused by mutation using sequence-and structure-based methods in a CAGI5 blind challenge

Predicting the impact of mutations on proteins remains an important problem. As part of the CAGI5 frataxin challenge, we evaluate the accuracy with which Provean, FoldX, and ELASPIC can predict changes in the Gibbs free energy of a protein using a limited data set of eight mutations. We find that different methods have distinct strengths and limitations, with no method being strictly superior to other methods on all metrics. ELASPIC achieves the highest accuracy while also providing a web interface which simplifies the evaluation and analysis of mutations. FoldX is slightly less accurate than ELASPIC but is easier to run locally, as it does not depend on external tools or datasets. Provean achieves reasonable results while being computational less expensive than the other methods and not requiring a structure of the protein. In addition to methods submitted to the CAGI5 community experiment, and with the aim to inform about other methods with high accuracy, we also evaluate predictions made by Rosetta's ddg_monomer protocol, Rosetta's cartesian_ddg protocol, and thermodynamic integration calculations using Amber package. ELASPIC still achieves the highest accuracy, while Rosetta's catesian_ddg protocol appears to perform best in capturing the overall trend in the data.

Computational design of Bacillus licheniformis RN-01 levansucrase for control of the chain length of levan-type fructooligosaccharides

Levansucrase (LS) from Gram-positive bacteria generally produces a large quantity of levan polymer, a polyfructose with glucose at the end (GF_n) but a small quantity of levan-type fructooligosaccharides (LFOs). The properties of levan and LFOs depend on their chain lengths, thereby determining their potential applications in food and pharmaceutical industries such as prebiotics and anti-tumor agents. Therefore, an ability to redesign and engineer the active site of levansucrase for synthesis of products with desired degree of polymerization (DP) is very beneficial. We employed computational protein design, docking and molecular dynamics to redesign and engineer the active site of Bacillus licheniformis RN-01 levansucrase for production of LFOs with DP up to five (GF₄), using two approaches: 1) blocking oligosaccharide binding track of GF₃-LS complex with large aromatic residues and 2) eliminating hydrogen bond interactions between terminal glucose of GF₄ and side chains of binding residues of GF₄-LS complex. The designed enzymes and their product patterns from these two approaches were experimentally characterized. The experimental results show that the first approach was successful in creating N251W and N251W/K372Y mutants that synthesized LFOs with DP up to five. This work illustrates how computer-aided approaches can offer novel opportunities to engineer enzymes for desired products.

Ternary Complex Formation and Photoactivation of a Photoenzyme Results in Altered Protein Dynamics

The interplay between protein dynamics and catalysis remains a fundamental question in enzymology. We here investigate the ns-timescale dynamics of a light-dependent NADPH:protochlorophyllide oxidoreductase (LPOR), a photoenzyme crucial for chlorophyll synthesis. LPORs catalyze the light-triggered trans addition of a hydride and a proton across the C17═C18 double bond of the chlorophyll precursor protochlorophyllide (Pchlide). Because of the lack of an LPOR structure, the global structural and dynamic consequences of LPOR/Pchlide/NADPH ternary complex formation remain elusive. Moreover, photoactivation of LPORs by low-light preillumination is controversially discussed as unequivocal proof for this phenomenon is lacking. By employing quasielastic neutron spectroscopy (QENS), we show that the formation of the ternary holoprotein complex as well as photoactivation lead to progressive rigidification of the protein. These findings are supported by thermostability measurements, which reveal different melting behavior and thermostabilities for the apo- and holoprotein ternary complexes. Molecular dynamics simulations in good agreement with the experimental QENS results suggest that the increased flexibility observed for the apoprotein stems from structural fluctuations of the NADPH and Pchlide substrate binding sites of the enzyme. On the basis of our results, in conjunction with activity and stability measurements, we provide independent proof for LPOR photoactivation, defined as a process that modifies the protein structure and dynamics, resulting in an increased substrate turnover. Our findings advance the structural and dynamic understanding of LPORs and provide a first link between protein dynamics and catalysis for this enzyme class.

Formation Mechanism of Ion Channel in Channelrhodopsin-2: Molecular Dynamics Simulation and Steering Molecular Dynamics Simulations

Channelrhodopsin-2 (ChR2) is a light-activated and non-selective cationic channel protein that can be easily expressed in specific neurons to control neuronal activity by light. Although ChR2 has been extensively used as an optogenetic tool in neuroscience research, the molecular mechanism of cation channel formation following retinal photoisomerization in ChR2 is not well understood. In this paper, studies of the closed and opened state ChR2 structures are presented. The formation of the cationic channel is elucidated in atomic detail using molecular dynamics simulations on the all-trans-retinal (ChR2-trans) configuration of ChR2 and its isomerization products, 13-cis-retinal (ChR2-cis) configuration, respectively. Photoisomerization of the retinal-chromophore causes the destruction of interactions among the crucial residues (e.g., E90, E82, N258, and R268) around the channel and the extended H-bond network mediated by numerous water molecules, which opens the pore. Steering molecular dynamics (SMD) simulations show that the electrostatic interactions at the binding sites in intracellular gate (ICG) and central gate (CG) can influence the transmembrane transport of Na⁺ in ChR2-cis obviously. Potential of mean force (PMF) constructed by SMD and umbrella sampling also found the existing energy wells at these two binding sites during the transportation of Na⁺. These wells partly hinder the penetration of Na⁺ into cytoplasm through the ion channel. This investigation provides a theoretical insight on the formation mechanism of ion channels and the mechanism of ion permeation.

Molecular mechanisms for dynamic regulation of N1 riboswitch by aminoglycosides

A synthetic riboswitch N1, inserted into the 5'-untranslated mRNA region of yeast, regulates gene expression upon binding ribostamycin and neomycin. Interestingly, a similar aminoglycoside, paromomycin, differing from neomycin by only one substituent (amino versus hydroxyl), also binds to the N1 riboswitch, but without affecting gene expression, despite NMR evidence that the N1 riboswitch binds all aminoglycosides in a similar way. Here, to explore the details of structural dynamics of the aminoglycoside-N1 riboswitch complexes, we applied all-atom molecular dynamics (MD) and temperature replica-exchange MD simulations in explicit solvent. Indeed, we found that ribostamycin and neomycin affect riboswitch dynamics similarly but paromomycin allows for more flexibility because its complex lacks the contact between the distinctive 6' hydroxyl group and the G9 phosphate. Instead, a transient hydrogen bond of 6'-OH with A17 is formed, which partially diminishes interactions between the bulge and apical loop of the riboswitch, likely contributing to riboswitch inactivity. In many ways, the paromomycin complex mimics the conformations, interactions, and Na+ distribution of the free riboswitch. The MD-derived interaction network helps understand why riboswitch activity depends on aminoglycoside type, whereas for another aminoglycoside-binding site, aminoacyl-tRNA site in 16S rRNA, activity is not discriminatory.