Study on the anisotropic response of condensed-phase RDX under repeated stress wave loading via ReaxFF molecular dynamics simulation

Anisotropic mechanical response and chemical reaction process of cyclotrimethylene trinitramine (RDX) along crystal orientations were studied with molecular dynamics simulations using ReaxFF potential under repeated stress wave loading. In the simulations, shocks were propagated along the [010], [001], [210], [100], [111], and [102] orientations of crystal RDX at initial particle velocity U_p in the range of 1～4 km/s. For shocks at U_p?≤?2 km/s, local stacking fault and molecular conformational change can only cause marginal temperature and pressure increase without molecular decomposition. As shocks increase to U_p?≥?2.5 km/s, rupture of N-NO₂ bond accompanied by partial HONO elimination dominates the main chemical reactions at the initial stage. The ordering of the follow-up consumption of NO₂ and ring-breaking rate is directly consistent with that of increasing rate in temperature and pressure. The (210) and (100) planes are more sensitive to shocks in temperature and pressure profiles than the (111) plane, which agrees well with experimental observations and theoretical results in the literature. Therefore, the repeated dynamic loading model in conjunction with MD simulation using ReaxFF potential for crystal RDX indicates that these methods can be applied to study the mechanical response and chemical reaction process of polymer bonded explosives that are commonly subjected to compressive and tensile stress waves observed in practice.     

Deep analysis of N-cadherin/ADH-1 interaction: a computational survey

Due to the considerable role of N-cadherin in cancer metastasis, tumor growth, and progression, inhibition of this protein has been highly regarded in recent years. Although ADH-1 has been known as an appropriate inhibitor of N-cadherin in clinical trials, its chemical nature and binding mode with N-cadherin have not been precisely specified yet. Accordingly, in this study, quantum mechanics calculations were used to investigate the chemical nature of ADH-1. These calculations clarify the molecular properties of ADH-1 and determine its reactive sites. Based on the results, the oxygen atoms are suitable for electrophilic reactivity, while the hydrogen atoms that are connected to nitrogen atoms are the favorite sites for nucleophilic reactivity. The higher electronegativity of the oxygen atoms makes them the most reactive portions in this molecule. Molecular docking and molecular dynamics (MD) simulation have also been applied to specify the binding mode of ADH-1 with N-cadherin and determine the important residues of N-cadherin involving in the interaction with ADH-1. Moreover, the verified model by MD simulation has been studied to extract the free energy value and find driving forces. These calculations and molecular electrostatic potential map of ADH-1 indicated that hydrophobic and electrostatic interactions are almost equally involved in the implantation of ADH-1 in the N-cadherin binding site. The presented results not only enable a closer examination of N-cadherin in complex with ADH-1 molecule, but also are very beneficial in designing new inhibitors for N-cadherin and can help to save time and cost in this field.     

Computational modeling of membrane trafficking processes: From large molecular assemblies to chemical specificity

In the last decade, molecular dynamics (MD) simulations have become an essential tool to investigate the molecular properties of membrane trafficking processes, often in conjunction with experimental approaches. The combination of MD simulations with recent developments in structural biology, such as cryo-electron microscopy and artificial intelligence-based structure determination, opens new, exciting possibilities for future investigations. However, the full potential of MD simulations to provide a molecular view of the complex and dynamic processes involving membrane trafficking can only be realized if certain limitations are addressed, and especially those concerning the quality of coarse-grain models, which, despite recent successes in describing large-scale systems, still suffer from far-from-ideal chemical accuracy. In this review, we will highlight recent success stories of MD simulations in the investigation of membrane trafficking processes, their implications for future research, and the challenges that lie ahead in this specific research domain.     

Thermal decomposition behaviour of polyethylene in oxygen-free and low oxygen content circumstances by reactive molecular dynamic simulation

In the present study, the thermal decomposition characteristics of polyethylene (PE) in oxygen-free and low oxygen content circumstances were examined by molecular dynamic (MD) simulations at atomic scale using reactive force field (ReaxFF). Temporal evolutions of species were captured reasonably during the processes of thermal decomposition. The effects of oxygen content, temperature and heating rate were also analysed. In addition, the kinetic properties were predicted with reliable parameters. The results show good agreements with the available ones, which illustrate that the species with two carbon atoms are the vast majority of final products. Higher oxygen content and temperature promote the generation of small molecules with carbon atom number less than or equal to 10. In the presence of oxygen, greater activation energy span and reaction order are calculated with lower adjust R², which indicates complex reactions according to kinetic analysis. The initial decomposition temperature of PE is proportional to the heating rate owing to heat transfer lag.     

Learning chemistry with multiple first-principles simulations

Huge parallel high-performance computing (HPC) architectures are today available laboratories for modelling atomic forces with high accuracy and for large samples of atoms. Modern statistical tools allow to simulate the statistics of these samples, while first-principles molecular dynamics (MD) can probe the interactions within large atomic samples, including possible chemical reactions. But a proper statistical convergence for the ensemble, represented in terms of a bundle of trajectories, is still unsatisfactory in terms of comparisons with experiments. Can we learn something by these HPC experiments? In this contribution, we show one example, where the occurrence of a chemical reaction in a disordered system is probed. The complex of the copper ion and a segment of the amyloid-β peptide, of wide interest in understanding the progress of Alzheimer's disease, was modelled combining constructions based on empirical force fields with first-principles MD simulations. We simulate a bundle of 16 different structures, biasing different Cu coordination numbers and changing the charge (oxidation state) of the assembly. Even within the given approximations for forces and the poor sampling, we could identify the structures of the complex that are able to react with hydrogen peroxide. The observation explains, at a molecular level, one important linkage between Alzheimer's disease and oxidative stress. This is an example of a general strategy for exploiting reactive configurations within a large set of possible reasonable candidates.     

Molecular dynamics analysis of the transient temperature increase at void locations in shocked materials: RDX and Cu

Molecular dynamics (MD) simulations of high velocity impact (1–6 km/s) of RDX crystal with a nanometer-sized void, has been carried out to understand the mechanism of increase in temperature at void locations under shock loading. Similar simulations are then carried out on single-crystal copper for better interpretation of the results. A reactive potential that can simulate chemical reactions (ReaxFF) has been used for RDX, whereas an EAM potential has been used for Cu. Increased temperature at the void locations are observed under shock loading. The atomic motion, temperature, average potential energy per atom (PE), and average kinetic energy per atom (KE) in and around the voids are closely monitored in order to understand the reason for temperature increase. We compare our results with existing proposed mechanisms and show that some of the proposed mechanisms are not necessary for increased temperature at a void location. It is shown that the directed particle velocity is efficiently is converted into randomized velocity due to the presence of voids thereby increasing the local temperature transiently. In this initial stage (few picoseconds) of the shock, chemical reactions of energetic materials do not play a part in the temperature rise.     

Controllers for imposing continuum-to-molecular boundary conditions in arbitrary fluid flow geometries

We present a new parallelised controller for steering an arbitrary geometric region of a molecular dynamics (MD) simulation towards a desired thermodynamic and hydrodynamic state. We show that the controllers may be applied anywhere in the domain to set accurately an initial MD state, or solely at boundary regions to prescribe non-periodic boundary conditions (PBCs) in MD simulations. The mean molecular structure and velocity autocorrelation function remain unchanged (when sampled a few molecular diameters away from the constrained region) when compared with those distributions measured using PBCs. To demonstrate the capability of our new controllers, we apply them as non-PBCs in parallel to a complex MD mixing nano-channel and in a hybrid MD continuum simulation with a complex coupling region. The controller methodology is easily extendable to polyatomic MD fluids.     

A systematic methodology for defining coarse-grained sites in large biomolecules

Coarse-grained (CG) models of biomolecules have recently attracted considerable interest because they enable the simulation of complex biological systems on length-scales and timescales that are inaccessible for atomistic molecular dynamics simulation. A CG model is defined by a map that transforms an atomically detailed configuration into a CG configuration. For CG models of relatively small biomolecules or in cases that the CG and all-atom models have similar resolution, the construction of this map is relatively straightforward and can be guided by chemical intuition. However, it is more challenging to construct a CG map when large and complex domains of biomolecules have to be represented by relatively few CG sites. This work introduces a new and systematic methodology called essential dynamics coarse-graining (ED-CG). This approach constructs a CG map of the primary sequence at a chosen resolution for an arbitrarily complex biomolecule. In particular, the resulting ED-CG method variationally determines the CG sites that reflect the essential dynamics characterized by principal component analysis of an atomistic molecular dynamics trajectory. Numerical calculations illustrate this approach for the HIV-1 CA protein dimer and ATP-bound G-actin. Importantly, since the CG sites are constructed from the primary sequence of the biomolecule, the resulting ED-CG model may be better suited to appropriately explore protein conformational space than those from other CG methods at the same degree of resolution.     

Key structural features of the actin filament Arp2/3 complex branch junction revealed by molecular simulation

We investigated the structure, properties and dynamics of the actin filament branch junction formed by actin-related protein (Arp) 2/3 complex using all-atom molecular dynamics (MD) simulations based on a model fit to a reconstruction from electron tomograms. Simulations of the entire structure consisting of 31 protein subunits together with solvent molecules containing ～3 million atoms were performed for an aggregate time of 175 ns. One 75-ns simulation of the original reconstruction was compared to two 50-ns simulations of alternate structures, showing that the hypothesized branch junction structure is very stable. Our simulations revealed that the interface between Arp2/3 complex and the mother actin filament features a large number of salt bridges and hydrophobic contacts, many of which are dynamic and formed/broken on the timescale of the simulation. The simulations suggest that the DNase binding loops in Arp3, and possibly Arp2, form stabilizing contacts with the mother filament. Unbiased comparison of models sampled from the MD simulation trajectory with the primary experimental electron tomography data identified regions were snapshots from the simulation provide atomic details of the model structures and also pinpoints regions where the initial modeling based on the electron tomogram reconstruction may be suboptimal.     

Dynamic simulations of stimuli-responsive switching of azobenzene derivatives in self-assembled monolayers: reactive rotation potential and switching functions

Although the force field (FF)-based molecular dynamics (MD) simulation has been widely applied to rationalise the experimental observations and measurements in chemistry, physics, materials and life science for years, traditional FF suffers from the incapability for describing chemical reactions, which are crucial in many important transformation processes. In order to simulate the collective switching process in azobenzene-based self-assemble monolayers on Au(111) surface, reactive MD simulations with alternative FF were implemented. The classic torsion function has been modified to depict the diabatic potential energy curves for cis and trans isomers, respectively. A switching function is further introduced to connect two N = N rotation functions, and the surface hopping between the cis and trans curves is allowed. By using the reactive rotation potential and switching function, the collective effect of numerous reaction centres and the influence of environment on the quantum yield in the complex system were explored at mesoscopic dimension and timescales. The reactive FF may be also applicable for other complicated systems containing stilbene derivatives. Limitation and perspective for further developments for the other complicated reactions are also addressed.     

Multiply accelerated ReaxFF molecular dynamics: coupling parallel replica dynamics with collective variable hyper dynamics

ABSTRACT

To tackle the time scales required to study complex chemical reactions, methods performing accelerated molecular dynamics are necessary even with the recent advancement in high-performance computing. A number of different acceleration techniques are available. Here we explore potential synergies between two popular acceleration methods – Parallel Replica Dynamics (PRD) and Collective Variable Hyperdynamics (CVHD), by analysing the speedup obtained for the pyrolysis of n-dodecane. We observe that PRD?+?CVHD provides additional speedup to CVHD by reaching the required time scales for the reaction at an earlier wall-clock time. Although some speedup is obtained with the additional replicas, we found that the effectiveness of the inclusion of PRD is depreciated for systems where there is a dramatic increase in reaction rates induced by CVHD. Similar observations were made in the simulation of ethylene-carbonate/Li system, which is inherently more reactive than pyrolysis, indicate that the speedup obtained via the combination of the two acceleration methods can be generalised to most practical chemical systems.     

Defining Coarse-Grained Representations of Large Biomolecules and Biomolecular Complexes from Elastic Network Models

Coarse-grained (CG) models of large biomolecular complexes enable simulations of these systems over long timescales that are not accessible for atomistic molecular dynamics (MD) simulations. A systematic methodology, called essential dynamics coarse-graining (ED-CG), has been developed for defining coarse-grained sites in a large biomolecule. The method variationally determines the CG sites so that key dynamic domains in the protein are preserved in the CG representation. The original ED-CG method relies on a principal component analysis (PCA) of a MD trajectory. However, for many large proteins and multi-protein complexes such an analysis may not converge or even be possible. This work develops a new ED-CG scheme using an elastic network model (ENM) of the protein structure. In this procedure, the low-frequency normal modes obtained by ENM are used to define dynamic domains and to define the CG representation accordingly. The method is then applied to several proteins, such as the HIV-1 CA protein dimer, ATP-bound G-actin, and the Arp2/3 complex. Numerical results show that ED-CG with ENM (ENM-ED-CG) is much faster than ED-CG with PCA because no MD is necessary. The ENM-ED-CG models also capture functional essential dynamics of the proteins almost as well as those using full MD with PCA. Therefore, the ENM-ED-CG method may be better suited to coarse-grain a very large biomolecule or biomolecular complex that is too computationally expensive to be simulated by conventional MD, or when a high resolution atomic structure is not even available.     

Reactive molecular dynamics simulations on the thermal decomposition of poly alpha-methyl styrene

Using molecular dynamics simulations with ReaxFF reactive force field, the thermal decomposition mechanism of poly alpha-methyl styrene (PAMS) materials and the effects of heating rate and impurity fluorobenzene on PAMS thermal decompositions are studied. The results show that: 1) Pyrolysis mechanism of PAMS consists of initiation and propagation processes. In the initiation stage, random scissions of C-C backbone produce fragments, and in the propagation stage, depolymerizing reactions generate monomers and other products. 2) Higher decomposition temperature is needed for greater heating rate. 3) The presence of impurity fluorobenzene retards thermal decomposition of PAMS.     

Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.     

Integrating experimental data with molecular simulations to investigate RNA structural dynamics

Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule Förster resonance energy transfer, or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space resolutions. Their combination with accurate atomistic molecular dynamics (MD) simulations paves the way for quantitative and detailed studies of RNA dynamics. First, experiments provide a quantitative validation tool for MD simulations. Second, available data can be used to refine simulated structural ensembles to match experiments. Finally, comparison with experiments allows for improving MD force fields that are transferable to new systems for which data is not available. Here we review the recent literature and provide our perspective on this field.     

Photochemical Reaction Dynamics of the Primary Event of Vision Studied by Means of a Hybrid Molecular Simulation

The photoisomerization reaction dynamics of a retinal chromophore in the visual receptor rhodopsin was investigated by means of hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations. The photoisomerization reaction of retinal constitutes the primary step of vision and is known as one of the fastest reactions in nature. To elucidate the molecular mechanism of the high efficiency of the reaction, we carried out hybrid ab initio QM/MM MD simulations of the complete reaction process from the vertically excited state to the photoproduct via electronic transition in the entire chromophore-protein complex. An ensemble of reaction trajectories reveal that the excited-state dynamics is dynamically homogeneous and synchronous even in the presence of thermal fluctuation of the protein, giving rise to the very fast formation of the photoproduct. The synchronous nature of the reaction dynamics in rhodopsin is found to originate from weak perturbation of the protein surroundings and from dynamic regulation of volume-conserving motions of the chromophore. The simulations also provide a detailed view of time-dependent modulations of hydrogen-out-of-plane vibrations during the reaction process, and identify molecular motions underlying the experimentally observed dynamic spectral modulations.     

Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids

Many large protein-nucleic acid complexes exhibit allosteric regulation. In these systems, the propagation of the allosteric signaling is strongly coupled to conformational dynamics and catalytic function, challenging state-of-the-art analytical methods. Here, we review established and innovative approaches used to elucidate allosteric mechanisms in these complexes. Specifically, we report network models derived from graph theory and centrality analyses in combination with molecular dynamics (MD) simulations, introducing novel schemes that implement the synergistic use of graph theory with enhanced simulations methods and ab-initio MD. Accelerated MD simulations are used to construct “enhanced network models”, describing the allosteric response over long timescales and capturing the relation between allostery and conformational changes. “Ab-initio network models” combine graph theory with ab-initio MD and quantum mechanics/molecular mechanics (QM/MM) simulations to describe the allosteric regulation of catalysis by following the step-by-step dynamics of biochemical reactions. This approach characterizes how the allosteric regulation changes from reactants to products and how it affects the transition state, revealing a tense-to-relaxed allosteric regulation along the chemical step. Allosteric models and applications are showcased for three paradigmatic examples of allostery in protein-nucleic acid complexes: (i) the nucleosome core particle, (ii) the CRISPR-Cas9 genome editing system and (iii) the spliceosome. These methods and applications create innovative protocols to determine allosteric mechanisms in protein-nucleic acid complexes that show tremendous promise for medicine and bioengineering.     

Markov State Models Reveal a Two-Step Mechanism of miRNA Loading into the Human Argonaute Protein: Selective Binding followed by Structural Re-arrangement

Argonaute (Ago) proteins and microRNAs (miRNAs) are central components in RNA interference, which is a key cellular mechanism for sequence-specific gene silencing. Despite intensive studies, molecular mechanisms of how Ago recognizes miRNA remain largely elusive. In this study, we propose a two-step mechanism for this molecular recognition: selective binding followed by structural re-arrangement. Our model is based on the results of a combination of Markov State Models (MSMs), large-scale protein-RNA docking, and molecular dynamics (MD) simulations. Using MSMs, we identify an open state of apo human Ago-2 in fast equilibrium with partially open and closed states. Conformations in this open state are distinguished by their largely exposed binding grooves that can geometrically accommodate miRNA as indicated in our protein-RNA docking studies. miRNA may then selectively bind to these open conformations. Upon the initial binding, the complex may perform further structural re-arrangement as shown in our MD simulations and eventually reach the stable binary complex structure. Our results provide novel insights in Ago-miRNA recognition mechanisms and our methodology holds great potential to be widely applied in the studies of other important molecular recognition systems.     

Charge sensitivity approach to mutual polarization of reactants: molecular mechanics perspective

Charge sensitivity analysis (CSA) in force-field atoms resolution was applied to describe the mutual polarization of reactants as well as charge-transfer (CT) effects. An inclusion complex of β-cyclodextrin with salicylic acid was used as a model system. Three CSA models were taken into account and verified on a Born–Oppenheimer molecular dynamics (BOMD) trajectory. The models differed in terms of the equilibrium conditions imposed on the system. It was demonstrated that mutual polarization is an important source of stabilization, in contrast to the results obtained from static charge calculations. The energy lowering induced by CT was small and comparable to the CT stabilization that occurs in hydrogen-bonded systems. All models correctly described the main topological features of the BOMD energy surface. CSA in force-field atoms resolution qualitatively reproduced the charge reorganization accompanying hydrogen-bond formation. It was shown that CSA parameters are very sensitive to the bond formation process, which suggests that they could be applied in reactive force fields as detectors of newly formed chemical bonds.

Enhanced sampling of chemical and biochemical reactions with metadynamics

Metadynamics (MetaD) is a method that augments molecular dynamics (MD) calculations of all types (classical and quantum) to help systems overcome energy barriers and explore regions of phase space that would otherwise not be seen during a simulation. The method has seen wide ranging uses, and it has proven especially useful for the study of reactions in which bonds break and form. In such cases, the timescale challenges of MD are profoundly limiting, and the advent of this new paradigm for biasing simulations has proven to be incredibly useful. In this review, we set out to summarise the large body of work that uses MetaD for studying reactions so that others can more easily implement this method in their own work. After a brief introduction of the method, we provide detailed summaries of the method applied in various contexts including condensed phase and biological reactions.