Long-time Molecular Dynamics Simulations Research Articles

Long-Time Scale Simulations Reveal Key Dynamics That Drive the Onset of the N State in the Proteorhodopsin Photocycle.

Proteorhodopsin (PR) is a microbial proton pump that plays a significant role in phototrophy of bacteria in marine environments. Fundamental understanding of the structure-function relationship that drives proton pumping in PR has largely been elusive due to a lack of high-resolution structures of the photointermediates in the PR photocycle. Extending upon previous work, we used long-time scale molecular dynamics (MD) simulations to characterize the M state of the blue variant of PR, which represents the first proton transfer that takes place in the photocycle. Several notable structural changes occur in the M state that are hallmarks of subsequent steps in the PR photocycle, indicating that although this protein is often compared to the canonical microbial rhodopsins, such as bacteriorhodopsin, PR possesses characteristics that make it distinct among the rapidly increasing and widely variable catalog of microbial rhodopsins.

Simulation-Guided Molecular Modeling of Nisin and Lipid II Assembly and Membrane Pore Formation.

The lantibiotic pore-forming peptide nisin is a promising candidate in the fight against multidrug-resistant bacteria due to its unique structure, which allows it to disrupt bacteria in two distinct ways─Lipid II trafficking and transmembrane pore formation. However, exactly how nisin and Lipid II assemble into oligomeric pore structures in the bacterial membrane is not known. Spontaneous peptide assembly into pores is difficult to observe in even the very long-time scale molecular dynamics (MD) simulations. In this study, we adopted an MD-guided modeling approach to investigate the nisin-nisin and nisin-Lipid II associations in the membrane environment. Through extensive microsecond-time scale all-atom MD simulations, we established that nisin monomers dimerize by forming β-sheets in a POPE:POPG lipid bilayer and oligomerize further to form stable transmembrane channels. We determined that these nisin dimers use Lipid II as a dimer interface to incur enhanced stability. Our results provide a clearer understanding of the self-assembly of nisin monomers within the membrane and insights into the role of Lipid II in the structural integrity of oligomeric structures.

In silico Identification of Potential Inhibitors against Staphylococcus aureus Tyrosyl-tRNA Synthetase.

Drug-resistant Staphylococcus aureus (S. aureus) has spread from nosocomial to community-acquired infections. Novel antimicrobial drugs that are effective against resistant strains should be developed. S. aureus tyrosyl-tRNA synthetase (saTyrRS) is considered essential for bacterial survival and is an attractive target for drug screening. The purpose of this study was to identify potential new inhibitors of saTyrRS by screening compounds in silico and evaluating them using molecular dynamics (MD) simulations. A 3D structural library of 154,118 compounds was screened using the DOCK and GOLD docking simulations and short-time MD simulations. The selected compounds were subjected to MD simulations of a 75-ns time frame using GROMACS. Thirty compounds were selected by hierarchical docking simulations. The binding of these compounds to saTyrRS was assessed by short-time MD simulations. Two compounds with an average value of less than 0.15 nm for the ligand RMSD were ultimately selected. The longtime (75 ns) MD simulation results demonstrated that two novel compounds bound stably to saTyrRS in silico. Two novel potential saTyrRS inhibitors with different skeletons were identified by in silico drug screening using MD simulations. The in vitro validation of the inhibitory effect of these compounds on enzyme activity and their antibacterial effect on drug-resistant S. aureus would be useful for developing novel antibiotics.

Exploring Protonation State, Ion Binding, and Photoactivated Channel Opening of an Anion Channelrhodopsin by Molecular Simulations.

Channelrhodopsins are light-gated ion channels with a retinal chromophore found in microbes and are widely used in optogenetics, a field of neuroscience that utilizes light to regulate neuronal activity. GtACR1, an anion conducting channelrhodopsin derived from Guillardia theta, has attracted attention for its application as a neuronal silencer in optogenetics because of its high conductivity and selectivity. However, atomistic mechanisms of channel photoactivation and ion conduction have not yet been elucidated. In the present study, we investigated the molecular characteristics of GtACR1 and its photoactivation processes by molecular simulations. The QM/MM RWFE-SCF method which combines highly accurate quantum chemistry calculations with long-time molecular dynamics (MD) simulations were used to model protein structures of the wild-type and mutants with different protonation states of key groups and to calculate absorption energies for verification of the models. The QM/MM modeling together with MD simulations of free-energy calculations favors protonation of a key counterion carboxyl group of Asp234 with a strong binding of a chloride ion in the extracellular pocket in the dark state. A channel open state was also successfully modeled by the QM/MM RWFE-SCF free-energy optimizations, providing atomistic insights into the channel activation mechanism.

Modification of glycosyltransferase SrUGT76G1 based on computer-aided screening of mutation sites for efficient synthesis of rebaudioside M

Steviol glycosides (SGs) from Stevia rebaudiana Bertoni is a widely used sweetener with the advantage of high sweet and low in calories. Stevioside (ST) and Rebaudioside A (Reb A) with a bitter aftertaste are the main sweetening components in SGs. Reb M is a highly potency sweetener with almost no bitter aftertaste but is found in low content in S. rebaudiana Bertoni. In this study, the pre- and post-catalytic differences of stevioside glycosyltransferase SrUGT76G1 were investigated through long-time molecular dynamics simulations. SrUGT76G1 was mutated to enhance its efficiency in catalyzing the synthesis of Reb D to Reb M by identifying the enzyme mutation site through an integrated three-in-one approach that combines hinge region analysis, coevolutionary conservation, and energy calculations. The kcat and kcat/Km values of the M88V mutant with Reb D as substrate were 2.18-fold and 4.85-fold higher than those of wild-type SrUGT76G1, respectively. In addition, the M88V mutant coupled with sucrose synthase StSUS1 increased the yield of Reb M synthesis from Reb D to 92.40%. The present study provides an effective method for rapid search for mutation sites in the enzyme and for increasing the yield of Reb M.

Impart of Heterogeneous Charge Polarization and Distribution on Friction at Water-Graphene Interfaces: a Density-Functional-Theory based Machine Learning Study.

Accurately characterizing friction behaviors at water-solid interfaces remains a challenge because of the dynamic nature of water molecules and temporal variations in solid surface charges. By using a density-functional-theory (DFT) based machine learning (ML) technique and long-time ML-parametrized molecular dynamics simulations, we have systematically investigated water-induced charge polarization and redistribution on graphene, as well as its impact on friction at water-graphene interfaces. Heterogeneous charge polarization and distribution are observed for water-covered graphene accompanied by the formation of electric double layers (EDLs). The introduction of defects into graphene significantly enhances the heterogeneity in charge polarization and distribution. Compared to pristine graphene, defected graphene exhibits reduced friction at water-graphene interfaces due to stronger charge heterogeneity, resulting in lower surface charge density and the inverse relationship between slip length and surface charge density for EDLs. Our results highlight the pivotal roles of defects and charge heterogeneity in reducing friction at water-graphene interfaces.

Molecular Insights into the Effects of F16L and F19L Substitutions on the Conformation and Aggregation Dynamics of Human Calcitonin.

Human calcitonin (hCT) regulates calcium-phosphorus metabolism, but its amyloid aggregation disrupts physiological activity, increases thyroid carcinoma risk, and hampers its clinical use for bone-related diseases like osteoporosis and Paget's disease. Improving hCT with targeted modifications to mitigate amyloid formation while maintaining its function holds promise as a strategy. Understanding how each residue in hCT's amyloidogenic core affects its structure and aggregation dynamics is crucial for designing effective analogues. Mutants F16L-hCT and F19L-hCT, where Phe residues in the core are replaced with Leu as in nonamyloidogenic salmon calcitonin, showed different aggregation kinetics. However, the molecular effects of these substitutions in hCT are still unclear. Here, we systematically investigated the folding and self-assembly conformational dynamics of hCT, F16L-hCT, and F19L-hCT through multiple long-time scale independent atomistic discrete molecular dynamics (DMD) simulations. Our results indicated that the hCT monomer primarily assumed unstructured conformations with dynamic helices around residues 4-12 and 14-21. During self-assembly, the amyloidogenic core of hCT14-21 converted from dynamic helices to β-sheets. However, substituting F16L did not induce significant conformational changes, as F16L-hCT exhibited characteristics similar to those of wild-type hCT in both monomeric and oligomeric states. In contrast, F19L-hCT exhibited substantially more helices and fewer β-sheets than did hCT, irrespective of their monomers or oligomers. The substitution of F19L significantly enhanced the stability of the helical conformation for hCT14-21, thereby suppressing the helix-to-β-sheet conformational conversion. Overall, our findings elucidate the molecular mechanisms underlying hCT aggregation and the effects of F16L and F19L substitutions on the conformational dynamics of hCT, highlighting the critical role of F19 as an important target in the design of amyloid-resistant hCT analogs for future clinical applications.

Softeners doped with asphaltene dispersants acting in synergy with resins: Molecular mechanisms underlying asphalt rejuvenation

In confronting the global climate change, reusing waste asphalt materials stands out as a key strategy for the transportation sector to preserve natural resources and reduce the carbon footprint. Recycling additives or rejuvenators are usually required in this practice, especially for boosting the recycling rate. Given the imperative need for a general compositional design principle of rejuvenators, we previously proposed an innovative formulation concept by combining softeners with asphaltene dispersants, and reported that the use of dispersants largely reduced the total quantity of rejuvenators needed and thus would minimize the environmental impacts. The present study is aimed for probing the molecular mechanisms underlying this observation, with additional interest focused on the synergistic effect of the dispersants with resins and also on the impacts due to their self-association. Selection of representative materials consisted of three types of dispersants including an ionic liquid, a phenolic amphiphile, and an ester plasticizer, in combination with an aromatic oil as the softener. Long-time molecular dynamics (MD) simulation was employed to inspect the aggregation of asphaltenes. Quantum chemical (QC) computation was performed to provide insights into the source of different dispersing behaviors. The results indicated that the three dispersants all acted in concert with resins in dispersing asphaltenes. The dispersion characteristics of asphaltenes could be viewed as a net result of the two competing mechanisms of the dispersing capability and self-association of the dispersant used. The ionic liquid exhibited much higher propensity to self-association at increasing concentrations than the phenolic dispersant, and yet the optimum performance was achieved for both when they were added at low dosages. The ester plasticizer showed minimal self-association and yielded improved dispersion with increasing concentrations. In all cases, the dispersing functionality mainly originated from the presence or formation of significant electron-withdrawing sites, collectively due to the highly electronegative cation and anion, hydrogen bonding, and polar groups. Comparison of the dispersing power was also conducted from different perspectives. The findings are expected to provide molecular insights for formulating versatile and more environmentally benign asphalt rejuvenators.

The Origin and Evolution of Sex Peptide and Sex Peptide Receptor Interactions.

Post-mating responses play a vital role in successful reproduction across diverse species. In fruit flies, sex peptide binds to the sex peptide receptor, triggering a series of post-mating responses. However, the origin of sex peptide receptor predates the emergence of sex peptide. The evolutionary origins of the interactions between sex peptide and sex peptide receptor and the mechanisms by which they interact remain enigmatic. In this study, we used ancestral sequence reconstruction, AlphaFold2 predictions, and molecular dynamics simulations to study sex peptide-sex peptide receptor interactions and their origination. Using AlphaFold2 and long-time molecular dynamics simulations, we predicted the structure and dynamics of sex peptide-sex peptide receptor interactions. We show that sex peptide potentially binds to the ancestral states of Diptera sex peptide receptor. Notably, we found that only a few amino acid changes in sex peptide receptor are sufficient for the formation of sex peptide-sex peptide receptor interactions. Ancestral sequence reconstruction and molecular dynamics simulations further reveal that sex peptide receptor interacts with sex peptide through residues that are mostly involved in the interaction interface of an ancestral ligand, myoinhibitory peptides. We propose a potential mechanism whereby sex peptide-sex peptide receptor interactions arise from the preexisting myoinhibitory peptides-sex peptide receptor interface as well as early chance events both inside and outside the preexisting interface that created novel sex peptide-specific sex peptide-sex peptide receptor interactions. Our findings provide new insights into the origin and evolution of sex peptide-sex peptide receptor interactions and their relationship with myoinhibitory peptides-sex peptide receptor interactions.

Genetic Algorithm for Automated Parameterization of Network Hamiltonian Models of Amyloid Fibril Formation.

The time scales of long-time atomistic molecular dynamics simulations are typically reported in microseconds, while the time scales for experiments studying the kinetics of amyloid fibril formation are typically reported in minutes or hours. This time scale deficit of roughly 9 orders of magnitude presents a major challenge in the design of computer simulation methods for studying protein aggregation events. Coarse-grained molecular simulations offer a computationally tractable path forward for exploring the molecular mechanism driving the formation of these structures, which are implicated in diseases such as Alzheimer's, Parkinson's, and type-II diabetes. Network Hamiltonian models of aggregation are centered around a Hamiltonian function that returns the total energy of a system of aggregating proteins, given the graph structure of the system as an input. In the graph, or network, representation of the system, each protein molecule is represented as a node, and noncovalent bonds between proteins are represented as edges. The parameter, i.e., a set of coefficients that determine the degree to which each topological degree of freedom is favored or disfavored, must be determined for each network Hamiltonian model, and is a well-known technical challenge. The methodology is first demonstrated by beginning with an initial set of randomly parametrized models of low fibril fraction (<5% fibrillar), and evolving to subsequent generations of models, ultimately leading to high fibril fraction models (>70% fibrillar). The methodology is also demonstrated by applying it to optimizing previously published network Hamiltonian models for the 5 key amyloid fibril topologies that have been reported in the Protein Data Bank (PDB). The models generated by the AI produced fibril fractions that surpass previously published fibril fractions in 3 of 5 cases, including the most naturally abundant amyloid fibril topology, the 1,2 2-ribbon, which features a steric zipper. The authors also aim to encourage more widespread use of the network Hamiltonian methodology for fitting a wide variety of self-assembling systems by releasing a free open-source implementation of the genetic algorithm introduced here.

Comparison of Accuracy and Efficiency of Milestoning Variants: Introducing Buffer Milestoning.

The Milestoning algorithm is a method for long-time molecular dynamics simulations. It enables the sampling of rare events. The precise calculations of observables depend on accurately determining the first hitting point distribution (FHPD) for each milestone. There is no analytical expression for FHPD, which is estimated numerically. Several variants of Milestoning offer approximations to the FHPD. Here, we examine in detail the FHPD of an exact calculation and Milestoning variants. We also introduce a new version of the Milestoning algorithm, buffer Milestoning, with a comparable cost to conventional Milestoning but higher accuracy. We use the mean first passage time and the free energy to assess the simulation quality, and we compare the accuracy and efficiency of buffer Milestoning to exact calculations, conventional Milestoning, local-passage-time-weighted Milestoning, Markovian Milestoning with Voronoi tessellation, and exact Milestoning. Conventional Milestoning requires milestone decorrelation. If this condition is not satisfied, it is the least accurate approach of all the techniques we examined. We conclude that for a small increase in cost compared to conventional Milestoning, buffer Milestoning provides accurate results for a range of problems, including more correlated milestones and is, therefore, versatile compared to other variants. Local-passage-time-weighted Milestoning provides accuracy similar to that of buffer Milestoning but at an increased simulation cost. Markovian Milestoning with Voronoi tessellation is the most accurate compared with other approximations, but it is less stable for high barriers and more expensive.

Construction of full-atomistic polymer amorphous structures using reverse-mapping from Kremer-Grest models.

We propose a method to build full-atomistic (FA) amorphous polymer structures using reverse-mapping from coarse-grained (CG) models. In this method, three models with different resolutions are utilized, namely the CG1, CG2, and FA models. It is assumed that the CG1 model is more abstract than the CG2 model. The CG1 is utilized to equilibrate the system, and then sequential reverse-mapping procedures from the CG1 to the CG2 models and from the CG2 to the FA models are conducted. A mapping relation between the CG1 and the FA models is necessary to generate a polymer structure with a given density and radius of chains. Actually, we have used the Kremer-Grest (KG) model as the CG1 and the monomer-level CG model as the CG2 model. Utilizing the mapping relation, we have developed a scheme that constructs an FA polymer model from the KG model. In the scheme, the KG model, the monomer level CG model, and the FA model are successively constructed. The scheme is applied to polyethylene (PE), cis 1,4-polybutadiene (PB), and poly(methyl methacrylate) (PMMA). As a validation, the structures of PE and PB constructed by the scheme were carefully checked through comparison with those obtained using long-time FA molecular dynamics (MD) simulations. We found that both short- and long-range chain structures constructed by the scheme reproduced those obtained by the FA MD simulations. Then, as an interesting application, the scheme is applied to generate an entangled PMMA structure. The results showed that the scheme provides an efficient and easy way to construct amorphous structures of FA polymers.

Tyr 118-Mediated Electron Transfer is Key to the Chlorite Decomposition in Heme-Dependent Chlorite Dismutase.

Chlorite dismutase (Cld) is a crucial enzyme that catalyzes the decomposition of chlorite ions into chloride ions (Cl-) and molecular oxygen (O2). Despite playing an important role in the detoxification of toxic chlorite ions, the mechanism of cleavage of the Cl-O bond by Cld remains highly debatable. The present study highlights the mechanism of such Cl-O bond cleavage in Cld using sophisticated computational tools such as hybrid quantum mechanical/molecular mechanical calculations and long-time scale molecular dynamics simulations. Here, we show that Cld forms a high spin ferric hexacoordinated substrate adduct in the presence of a chlorite ion, which subsequently reduces to a ferrous state. Our study shows a stepwise pathway with the homolytic cleavage of the Cl-O bond that produces a high spin Fe(III)-OH species and a diradicaloid species formed by the combination of a chlorine-based ClO• radical and a protein-based tyrosine118• radical. The findings provide significant insights into Cl-O bond cleavage and O2 formation which shows a crucial role of the tyrosine118 during the electron transfer process.

Evaluation of Molecular Simulations and Deep Learning Prediction of Antibodies' Recognition of TRBC1 and TRBC2.

T cell receptor β-chain constant (TRBC) is a promising class of cancer targets consisting of two highly homologous proteins, TRBC1 and TRBC2. Developing targeted antibody therapeutics against TRBC1 or TRBC2 is expected to eradicate the malignant T cells and preserve half of the normal T cells. Recently, several antibody engineering strategies have been used to modulate the TRBC1 and TRBC2 specificity of antibodies. Here, we used molecular simulation and artificial intelligence methods to quantify the affinity difference in antibodies with various mutations for TRBC1 and TRBC2. The affinity of the existing mutants was verified by FEP calculations aided by the AI. We also performed long-time molecular dynamics simulations to reveal the dynamical antigen recognition mechanisms of the TRBC antibodies.

Barium isotope fractionation during granitic magmatism and potential of δ138/134Ba for distinguishing magmatic-hydrothermal transition in granitic magma systems

The geochemistry of Ba is commonly used to study igneous processes and fluid-melt interaction in subduction zone and granitic environments. Recent advances in analytical techniques have also indicated that Ba isotope geochemistry has the potential to significantly augment these studies. Understanding the Ba isotope fractionation mechanisms is thus critical if this potential is to be fully realized. Hence, we have used the first-principles calculations based on the density functional theory (DFT) and long-time ab initio molecular dynamics (AIMD) simulation to calculate Ba isotope fractionation during felsic magma evolution. In fluids, the reduced partition function ratio (β factor) of aqueous Ba2+ is highly variable, depending on the coordination number (n) of H2O in the first hydration shell. At ambient surface conditions on the Earth, n = 8 best represents the aqueous Ba2+ species in natural fluid, and the temperature-dependent equilibrium Ba isotope fractionation between barite/witherite and fluids can be described by the relationships: 103lnαwitherite-fluid = −0.00009×(106/T2)2 + 0.0603×(106/T2) + 0.0003 and 103lnαbarite-fluid = −0.0001×(106/T2)2 + 0.0648×(106/T2) + 0.0004, which is consistent with previous theoretical and experimental studies. In hydrothermal fluids, the hydration number of Ba2+ varies from 4 to 6 at high P-T, and the cumulative average of 103lnβ is derived to be 0.0798 ± 0.005‰ in 923.15 K and 0.2 GPa. In silicate minerals, the enrichment of heavy Ba isotopes decreases in the sequence of muscovite > microcline ≈ celsian ≈ sanbornite > barylite > phlogopite. Variations in Ba concentrations and the degree of Al-Si disordering only induce limited Ba isotope fractionation, which would be hard to distinguish analytically. At high temperatures (> 600 °C), the melt phase is enriched in heavy Ba isotopes relative to any coexisting aqueous fluid and crystallizing minerals. During the early stages of felsic magma differentiation involving plagioclase crystallization as the main mineral, the δ138/134Ba and concentration in the residual melt remain close to their initial values, but any fluid exsolved from the melt will have light δ138/134Ba values. The high Ba distribution coefficient of K-feldspar means that the resultant K-feldspar granite inherits > 90% of the Ba contained in the initial magma reservoir. Hence, the δ138/134Ba of K-feldspar is close to that of the initial melt. During the final stage of felsic magma evolution, mixing of exsolved fluids from deeper reservoirs may significantly reduce the δ138/134Ba of the now Ba-depleted melt, and can account for the low δ138/134Ba values measured in highly differentiated leucogranites and pegmatites.

Liquid Structures and Diffusion Dynamics of Alkyl-Pyrene Liquids Studied by Molecular Dynamics Simulations.

Functional molecular liquids (FMLs) based on alkylated π-conjugated molecules have attracted attention as solvent-free and nonvolatile liquid materials with prominent optoelectronic features. Recently, novel FML compounds containing pyrene as the functional core were synthesized, and their rheological and photochemical properties were investigated. Although the molecules differ only in the number of alkyl chain substituents and their substitution positions, their viscosity coefficients are largely different beyond the Stokes-Einstein relation on the assumption of identical microscopic friction, indicating that local microscopic molecular interactions are crucial for the macroscopic rheological properties. Here, we report a theoretical study on the rheological properties of the alkyl-pyrene liquids by means of atomistic molecular dynamics (MD) simulations. We performed long-time MD simulations for tens of microseconds to obtain ample statistical samples of the alkyl-pyrene liquids and analyzed their liquid structures and diffusion dynamics based on spatiotemporal correlation functions. We found the formation of characteristic local liquid structures of π-π stacking of the pyrene moieties and locally anisotropic and anomalous diffusion dynamics, which remarkably vary depending on the alkyl substituent patterns. The present results provide an atomistic insight into the macroscopic rheological properties of alkyl-π FMLs and molecular design strategy for them.

Computational Insights into Prostaglandin E2 Ligand Binding and Activation of G-Protein-Coupled Receptors.

G-protein coupled receptors (GPCRs) are eukaryotic integral membrane proteins that regulate signal transduction cascade pathways implicated in a variety of human diseases and are consequently of interest as drug targets. For this reason, it is of interest to investigate the way in which specific ligands bind and trigger conformational changes in the receptor during activation and how this in turn modulates intracellular signaling. In the present study, we investigate the way in which the ligand Prostaglandin E2 interacts with three GPCRs in the E-prostanoid family: EP1, EP2, and EP3. We examine information transfer pathways based on long-time scale molecular dynamics simulations using transfer entropy and betweenness centrality to measure the physical transfer of information among residues in the system. We monitor specific residues involved in binding to the ligand and investigate how the information transfer behavior of these residues changes upon ligand binding. Our results provide key insights that enable a deeper understanding of EP activation and signal transduction functioning pathways at the molecular level, as well as enabling us to make some predictions about the activation pathway for the EP1 receptor, for which little structural information is currently available. Our results should advance ongoing efforts in the development of potential therapeutics targeting these receptors.

Classification of GTP-dependent K-Ras4B active and inactive conformational states.

Classifying reliably active and inactive molecular conformations of wildtype (WT) and mutated oncogenic proteins is a key, ongoing challenge in molecular cancer studies. Here, we probe the GTP-bound K-Ras4B conformational dynamics using long-time atomistic molecular dynamics (MD) simulations. We extract and analyze the detailed underlying free energy landscape of WT K-Ras4B. We use two key reaction coordinates, labeled d1 and d2 (i.e., distances coordinating the Pβ atom of the GTP ligand with two key residues, T35 and G60), shown to correlate closely with activities of WT and mutated K-Ras4B. However, our new K-Ras4B conformational kinetics study reveals a more complex network of equilibrium Markovian states. We show that a new reaction coordinate is required to account for the orientation of acidic K-Ras4B sidechains such as D38 with respect to the interface with binding effector RAF1 and rationalize the activation/inactivation propensities and the corresponding molecular binding mechanisms. We use this understanding to unveil how a relatively conservative mutation (i.e., D33E, in the switch I region) can lead to significantly different activation propensities compared with WT K-Ras4B. Our study sheds new light on the ability of residues near the K-Ras4B-RAF1 interface to modulate the network of salt bridges at the binding interface with the RAF1 downstream effector and, thus, to influence the underlying GTP-dependent activation/inactivation mechanism. Altogether, our hybrid MD-docking modeling approach enables the development of new in silico methods for quantitative assessment of activation propensity changes (e.g., due to mutations or local binding environment). It also unveils the underlying molecular mechanisms and facilitates the rational design of new cancer drugs.

Long-time scale simulations of virus-like particles from three human-norovirus strains.

The dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 μs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that sits in the VLP shell) and the P2 subdomain (that protrudes outside) of the major VP1 protein, this resulting in a correlated wagging motion of the P2 subdomains with respect to the VLP surface. The fluctuations of the P2 subdomain were found to be more pronounced and the P2 domain made a greater angle with the normal to the VLP surface for the GII.2 strain, which could explain the inability of this strain to bind the histo-blood group antigens (HBGAs).

Spliceosomal SL1 RNA binding to U1-70K: the role of the extended RRM.

The RNA recognition motif (RRM) occurs widely in RNA-binding proteins, but does not always by itself support full binding. For example, it is known that binding of SL1 RNA to the protein U1-70K in the U1 spliceosomal particle is reduced when a region flanking the RRM is truncated. How the RRM flanking regions that together with the RRM make up an ‘extended RRM’ (eRRM) contribute to complex stability and structural organization is unknown. We study the U1-70K eRRM bound to SL1 RNA by thermal dissociation and laser temperature jump kinetics; long-time molecular dynamics simulations interpret the experiments with atomistic resolution. Truncation of the helix flanking the RRM on its N-terminal side, ‘N-helix,’ strongly reduces overall binding, which is further weakened under higher salt and temperature conditions. Truncating the disordered region flanking the RRM on the C-terminal side, ‘C-IDR’, affects the local binding site. Surprisingly, all-atom simulations show that protein truncation enhances base stacking interactions in the binding site and leaves the overall number of hydrogen bonds intact. Instead, the flanking regions of the eRRM act in a distributed fashion via collective interactions with the RNA when external stresses such as temperature or high salt mimicking osmotic imbalance are applied.