Molecular Mechanics Model Research Articles

New Molecular-Mechanics Model for Simulations of Hydrogen Fluoride in Chemistry and Biology.

Hydrogen fluoride (HF) is the most polar diatomic molecule and one of the simplest molecules capable of hydrogen-bonding. HF deviates from ideality both in the gas phase and in solution and is thus of great interest from a fundamental standpoint. Pure and aqueous HF solutions are broadly used in chemical and industrial processes, despite their high toxicity. HF is a stable species also in some biological conditions, because it does not readily dissociate in water unlike other hydrogen halides; yet, little is known about how HF interacts with biomolecules. Here, we set out to develop a molecular-mechanics model to enable computer simulations of HF in chemical and biological applications. This model is based on a comprehensive high-level ab initio quantum chemical investigation of the structure and energetics of the HF monomer and dimer; (HF)n clusters, for n = 3-7; various clusters of HF and H2O; and complexes of HF with analogs of all 20 amino acids and of several commonly occurring lipids, both neutral and ionized. This systematic analysis explains the unique properties of this molecule: for example, that interacting HF molecules favor nonlinear geometries despite being diatomic and that HF is a strong H-bond donor but a poor acceptor. The ab initio data also enables us to calibrate a three-site molecular-mechanics model, with which we investigate the structure and thermodynamic properties of gaseous, liquid, and supercritical HF in a wide range of temperatures and pressures; the solvation structure of HF in water and of H2O in liquid HF; and the free diffusion of HF across a lipid bilayer, a key process underlying the high cytotoxicity of HF. Despite its inherent simplifications, the model presented significantly improves upon previous efforts to capture the properties of pure and aqueous HF fluids by molecular-mechanics methods and to our knowledge constitutes the first parameter set calibrated for biomolecular simulations.

Tensile properties of microtubules: A study by nonlinear molecular structural mechanics modelling

A nonlinear molecular structural mechanics (MSM) model is proposed in this paper for studying the tensile properties of microtubules (MTs). In the nonlinear MSM models, the interactions between tubulin monomers in MTs are treated as nonlinear axial and torsional springs, whose stiffness coefficients are extracted from all-atom molecular dynamics simulations. The Young's modulus and fracture properties of MTs under tension extracted from the present nonlinear MSM models are found to agree well with the existing simulation and experiment results, which shows the efficiency and accuracy of the proposed nonlinear MSM models. In addition, the nonlinear MSM models are also extended to investigate the tensile properties including Young's modulus and fracture strain of MTs possessing lattice defects. The results obtained from nonlinear MSM models are utilized to develop a predictive equation for quickly predicting the tensile properties of MTs with different lattice defect levels.

Dislocation nucleation in CoNiCrFeMn high entropy alloy

In this work, the homogeneous and heterogeneous nucleation of dislocations in a representative face-centered-cubic high entropy alloy (HEA) CoNiCrFeMn is studied by combining molecular dynamics simulations and continuum mechanics modeling. It is found that as compared to conventional metals such as Cu, HEAs have relatively low activation energy but require high athermal stress for dislocation nucleation. This seemingly odd behavior originates from the uniquely low (even negative) stacking fault energy in HEAs that leads to low critical nucleation radius and low activation volume for dislocation nucleation.

Mechanical properties of hexagonal boron nitride monolayers: Finite element and analytical predictions

The mechanical response of two-dimensional nanostructures may be significantly affected by their size. In this work, a molecular structural mechanics model is developed and is implemented in order to predict the nanomechanical behavior and calculate the corresponding elastic properties of hexagonal boron nitride sheets and describe their size-dependence. The finite element approach utilizes appropriate spring-like elements for the modeling of interactions between atoms within the hexagonal boron nitride structure, the stiffness constants of which are obtained by the molecular mechanics theory. Adopting conventional finite element techniques, the global stiffness matrix of the structure of a desired sheet size can be assembled. Applying appropriate boundary conditions, the governing equilibrium static equation can be solved and the elastic mechanical properties as Young’s modulus, shear modulus, and Poisson’s ratio of the structure can be calculated. Fitting the results of the mechanical properties calculated by the finite element analysis, analytical–empirical equations are proposed for their direct prediction for an hexagonal boron nitride sheet having the size parameters of the structure as independent variables.

Molecular mechanics modelling of amorphous silicon oxycarbide clusters by bottom-up approach

In this work, a large data set of SiCO amorphous clusters was created from predefined primary building units (PBUs), connected statistically using custom made Python interface to GULP program and employing ReaxFF force field. A series of amorphous SiCO clusters with various content of carbon incorporated into silica matrix, characterized by well-defined geometry were obtained, confirming that the proposed in this work bottom-up approach for amorphous materials modelling can be a good alternative to other methods, typically found in a literature (amorphous structure based on strongly distorted crystal structures, from a defined set of atoms via MD melt quenching or just by hand). The analysis of the structural properties of obtained clusters showed that the increasing content of carbon incorporated into cluster results in small elongation of Si–O bonds as well as shortening of Si–C bonds. Carbon content in a structure affects also the number of spontaneously formed Si3(C,O)3 cycles – the more carbon the greater number of cycles can be found.

Interaction potentials for modelling GaN precipitation and solid state polymorphism

We outline a molecular mechanics model for the interaction of gallium and nitride ions ranging from small complexes to nanoparticles and bulk crystals. While the current GaN force fields allow the modelling of either bulk crystals or single ions dispersed in solution, our model covers both and hence paves the way to describing aggregate formation and crystal growth processes from molecular simulations. The key to this is the use of formal +3 and −3 charges on the gallium and nitride ions, whilst accounting for the charge transfer in GaN crystals by means of additional potential energy terms. The latter are fitted against experimental data of GaN in the wurtzite structure and benchmarked for the zinc-blende and rock-salt polymorphs. Comparison to quantum chemical references and experiment shows reasonable agreement of structures and formation energy of [GaN]n aggregates, elastic properties of the bulk crystal, the transition pressure of the wurtzite to rock-salt transformation and intrinsic point defects. Furthermore, we demonstrate force field transferability towards the modelling of GaN nanoparticles from simulated annealing runs.

Signalling architectures can prevent cancer evolution

Cooperation between cells in multicellular organisms is preserved by an active regulation of growth through the control of cell division. Molecular signals used by cells for tissue growth are usually present during developmental stages, angiogenesis, wound healing and other processes. In this context, the use of molecular signals triggering cell division is a puzzle, because any molecule inducing and aiding growth can be exploited by a cancer cell, disrupting cellular cooperation. A significant difference is that normal cells in a multicellular organism have evolved in competition between high-level organisms to be altruistic, being able to send signals even if it is to their detriment. Conversely, cancer cells evolve their abuse over the cancer’s lifespan by out-competing their neighbours. A successful mutation leading to cancer must evolve to be adaptive, enabling a cancer cell to send a signal that results in higher chances to be selected. Using a mathematical model of such molecular signalling mechanism, this paper argues that a signal mechanism would be effective against abuse by cancer if it affects the cell that generates the signal as well as neighbouring cells that would receive a benefit without any cost, resulting in a selective disadvantage for a cancer signalling cell. We find that such molecular signalling mechanisms normally operate in cells as exemplified by growth factors. In scenarios of global and local competition between cells, we calculate how this process affects the fixation probability of a mutant cell generating such a signal, and find that this process can play a key role in limiting the emergence of cancer.

Self-Parametrizing System-Focused Atomistic Models

Computational studies of chemical reactions in complex environments such as proteins, nanostructures, or on surfaces require accurate and efficient atomistic models applicable to the nanometer scale. In general, an accurate parametrization of the atomistic entities will not be available for arbitrary system classes but demands a fast, automated, system-focused parametrization procedure to be quickly applicable, reliable, flexible, and reproducible. Here, we develop and combine an automatically parametrizable quantum chemically derived molecular mechanics model with machine-learned corrections under autonomous uncertainty quantification and refinement. Our approach first generates an accurate, physically motivated model from a minimum energy structure and its corresponding Hessian matrix by a partial Hessian fitting procedure of the force constants. This model is then the starting point to generate a large number of configurations for which additional off-minimum reference data can be evaluated on the fly. A Δ-machine learning model is trained on these data to provide a correction to energies and forces including uncertainty estimates. During the procedure, the flexibility of the machine learning model is tailored to the amount of available training data. The parametrization of large systems is enabled by a fragmentation approach. Due to their modular nature, all model construction steps allow for model improvement in a rolling fashion. Our approach may also be employed for the generation of system-focused electrostatic molecular mechanics embedding environments in a quantum-mechanical/molecular-mechanical hybrid model for arbitrary atomistic structures at the nanoscale.

Simulating protein-ligand binding with neural network potentials.

Drug molecules adopt a range of conformations both in solution and in their protein-bound state. The strain and reduced flexibility of bound drugs can partially counter the intermolecular interactions that drive protein–ligand binding. To make accurate computational predictions of drug binding affinities, computational chemists have attempted to develop efficient empirical models of these interactions, although these methods are not always reliable. Machine learning has allowed the development of highly-accurate neural-network potentials (NNPs), which are capable of predicting the stability of molecular conformations with accuracy comparable to state-of-the-art quantum chemical calculations but at a billionth of the computational cost. Here, we demonstrate that these methods can be used to represent the intramolecular forces of protein-bound drugs within molecular dynamics simulations. These simulations are shown to be capable of predicting the protein–ligand binding pose and conformational component of the absolute Gibbs energy of binding for a set of drug molecules. Notably, the conformational energy for anti-cancer drug erlotinib binding to its target was found to be considerably overestimated by a molecular mechanical model, while the NNP predicts a more moderate value. Although the ANI-1ccX NNP was not trained to describe ionic molecules, reasonable binding poses are predicted for charged ligands, but this method is not suitable for modeling charged ligands in solution.

Protective effects of Phlomis umbrosa extract on a monosodium iodoacetate–induced osteoarthritis model and prediction of molecular mechanisms using transcriptomics

Abstract Background Phlomis umbrosa Turczaninow root has been traditionally used to treat fractures, rheumatoid arthritis, and arthralgia. However, the effects and mechanisms of P. umbrosa on osteoarthritis (OA) remain poorly understood and a functional genomic approach has not been investigated. Aim The purpose of this study was to investigate the effects and mechanisms of P. umbrosa extract (PUE) on OA using transcriptomic analysis. Methods We performed joint diameter measurements, micro computed tomography, and histopathological analysis of monosodium iodoacetate (MIA)-induced OA rats treated with PUE (200 mg/kg) for 3 weeks. Gene expression profiling in articular cartilage tissue was then performed using RNA sequencing (RNA-seq) followed by signaling pathway analysis of regulatory genes. Results PUE treatment improved OA based on decreased joint diameter, increased joint morphological parameters, and histopathological features. Many genes involved in multiple signal transduction pathway and collagen activation in OA were differentially regulated by PUE. These included genes related to Wnt/β-catenin, OA pathway, and sonic hedgehog signaling activity. Furthermore, PUE treatment downregulated cartilage damage factors (MMP-9, MMP-13, ADAMTs4, and ADMATs5) and upregulated chondrogenesis (COL2A1 and SOX-9) by regulating the transcription factors SOX-9, Ctnnb1, and Epas1. Conclusion Based on the results of gene expression profiling, this study highlighted the molecular mechanisms underlying the effects of PUE in MIA-induced OA rats. The findings provide novel insight into the mechanisms by which PUE treatment-induced gene expression changes may influence OA disease progression. Taken together, the results suggest that PUE may be used as a source of therapeutic agents for OA.

Stereoelectronic Properties of 1,2,4-Triazole-Derived N-heterocyclic Carbenes - A Theoretical Study

Stereoelectronic Properties of 1,2,4-Triazole-Derived N-heterocyclic Carbenes - A Theoretical Study

Non-zero Lennard-Jones parameters for the Toukan–Rahman water model: more accurate calculations of the solvation free energy of organic substances

Application of a small radius of the hydrogen atom in molecular-mechanical models of hydrogen bonding improves the estimate of the solvation free energy of organic substances. At the same time, the density and evaporation heat of the bulk water vary slightly and are close to experimental values. Blind testing drug candidates in the SAMPL6 simulation competition showed that using the same Lennard-Jones hydrogen parameters for the hydroxyl, hydroxycarbonyl, amino, and amide groups is enough to predict log P octanol-water with MAE 0.67 and RMSD 0.75.

Enzymatic Preparation of 2'-5',3'-5'-Cyclic Dinucleotides, Their Binding Properties to Stimulator of Interferon Genes Adaptor Protein, and Structure/Activity Correlations.

Cyclic dinucleotides are second messengers in the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway, which plays an important role in recognizing tumor cells and viral or bacterial infections. They bind to the STING adaptor protein and trigger expression of cytokines via TANK binding kinase 1 (TBK1)/interferon regulatory factor 3 (IRF3) and inhibitor of nuclear factor-κB (IκB) kinase (IKK)/nuclear factor-κB (NFκB) signaling cascades. In this work, we describe an enzymatic preparation of 2'-5',3'-5'-cyclic dinucleotides (2'3'CDNs) with use of cyclic GMP-AMP synthases (cGAS) from human, mouse, and chicken. We profile substrate specificity of these enzymes by employing a small library of nucleotide-5'-triphosphate (NTP) analogues and use them to prepare 33 2'3'CDNs. We also determine affinity of these CDNs to five different STING haplotypes in cell-based and biochemical assays and describe properties needed for their optimal activity toward all STING haplotypes. Next, we study their effect on cytokine and chemokine induction by human peripheral blood mononuclear cells (PBMCs) and evaluate their cytotoxic effect on monocytes. Additionally, we report X-ray crystal structures of two new CDNs bound to STING protein and discuss structure-activity relationship by using quantum and molecular mechanical (QM/MM) computational modeling.

Study of the binding mechanism of aptamer to palytoxin by docking and molecular simulation

This paper provides a feasible model for molecular structure analysis and interaction mechanism of aptamer and micromolecule. In this study, modeling and dynamic simulation of ssDNA aptamer (P-18S2) and target (Palytoxin, PTX) were performed separately. Then, the complex structure between DNA and PTX was predicted, and docking results showed that PTX could combine steadily at the groove’s top of DNA model by strong hydrogen-bonds and electrostatic interaction. Thus, we truncated and optimized P-18S2 by simulating. At the same time, we also confirmed the reliability of simulation results by experiments. With the experimental and computational results, the study provided a more reasonable interpretation for the high affinity and specific binding of P-18S2 and PTX, which laid the foundation for further optimization and development of aptamers in molecular diagnostics and therapeutic applications.

Revealing the Sequence-Structure-Electronic Property Relation of Self-Assembling π-Conjugated Oligopeptides by Molecular and Quantum Mechanical Modeling.

Self-assembled nanoaggregates of π-conjugated synthetic peptides present a biocompatible and highly tunable alternative to silicon-based optical and electronic materials. Understanding the relationship between structural morphology and electronic properties of these assemblies is critical for understanding and controlling their mechanical, optical, and electronic responses. In this work, we combine all-atom classical molecular simulations with quantum mechanical electronic structure calculations to ascertain the sequence-structure-electronic property relationship within a family of Asp-X-X-quaterthiophene-X-X-Asp (DXX-OT4-XXD) oligopeptides in which X is one of the five amino acids {Ala, Phe, Gly, Ile, Val} ({A, F, G, I, V}). Molecular dynamics simulations reveal that smaller amino acid substituents (A, G) favor linear stacking within a peptide dimer, whereas larger groups (F, I, V) induce larger twist angles between the peptides. Density functional theory calculations on the dimer show the absorption spectrum to be dominated by transitions between carbon and sulfur p orbitals. Although the absorption spectrum is largely insensitive to the relative twist angle, the highest occupied molecular orbital strongly localizes onto one molecule within the dimer at large twist angles, impeding the efficiency of transport between molecules. Our results provide a fundamental understanding of the relation between peptide orientation and electronic structure and offer design precepts for rational engineering of these systems.

Temperature-related study on buckling properties of double-walled carbon nanotubes

In this paper, the influence of finite temperature on the axial buckling of double walled carbon nanotubes (DWCNTs) is investigated based on the non-local Timoshenko beam model. The double walled carbon nanotube with different nonlocal effects is considered as an elastic structure model of mechanics, which is composed of the Van der Waals' force between the two-layers/two walls of carbon nanotubes. Molecular structure mechanics model incorporating thermal temperature is developed to study the relation between Young's modulus and temperature. The temperature dependent Young's modulus is applied to study the mechanical property of double walled carbon nanotubes. It is found that the axial buckling properties of DWCNTs decrease with the increase of the finite temperature at high temperature, however, the axial buckling properties of DWCNTs increase with the increase of the finite temperature at low or room temperature. Moreover, it is noted that the continuous temperature has litter effect on the axial buckling property of DWCNTs at the low temperature. However, the influence of continuous temperature on the mechanical properties of DWCNTs can not be neglected at the high temperature.

Size and temperature effect of Young’s modulus of boron nitride nanosheet

Boron nitride nanosheets (BNNSs), a new type of wide bandgap nanomaterial, has attracted great attention due to their excellent properties and potential applications. Thus, it is necessary to have a comprehensive understanding of the mechanical properties of BNNSs in various working conditions. This paper presents an analytical model based on molecular mechanics to study the size effect and temperature effect on the Young’s modulus of BNNSs. A closed-form formulation is derived for Young’s modulus as a function of the length of B–N bonds and the out-plane displacement. It is shown that the chirality and the size of the BNNSs affect the length of BN bonds in molecular dynamic (MD) simulations. It is also found that the length of BN bonds and the out-plane displacement in a monolayer BNNS is remarkably temperature dependent. Therefore, the sizes and the temperatures can affect the Young’s modulus of BNNSs. The expressions developed in this paper are employed to investigate the Young’s modulus for zigzag and armchair BNNS with various sizes and temperatures. The present model, associating with a beam model, provides a simple method to calculate elastic properties which takes into account all bonded energies and force coefficient changes with atoms distance. The results of size effect and temperature effect are in good agreement with data of simulation performed in finite element method (FEM) simulation and MD simulation. The present study provides a molecular mechanics model to predict the Young’s modulus of a monolayer BNNS, and the present model may be applied to other two-dimensional (2D) materials in further study.

Mechanical deformations of carbon nanorings: a study by molecular dynamics and nonlocal continuum mechanics

Understanding of the elastic deformation behaviours of recently synthesised carbon nanorings (CNRs) is crucial in guiding their future applications, because the strain engineering provides an efficient means to modify their physical and chemical properties. In this paper, by using molecular dynamics simulations and nonlocal continuum mechanics models, we study the elastic deformations of CNRs with three different molecular structures, i.e., cycloparaphenylenes (CPPs), [4]cyclochrysenylenes and cyclacenes. Our results show that, compared to other two types of CNRs, CPPs have the smallest mechanical stiffness, which is attributed to the influence of numerous weak connecting carbon–carbon bonds existing between their component benzene rings. In addition to the molecular structure, the elastic deformation behaviours of CNRs are also found to strongly depend on the size. Specifically, the compressive stiffness of CNRs is found to increase as their size (radius) decreases. Meanwhile, the size reduction of CNRs can trigger the anisotropy of their compressive stiffness and can also aggravate the influence of small-scale effects on their elastic deformation behaviours, which can significantly reduce the compressive stiffness.

A Molecular Mechanics Model for Flavins.

Flavin containing molecules form a group of important cofactors that assist a wide range of enzymatic reactions. Flavins use the redox-active isoalloxazine system, which is capable of one- and two-electron transfer reactions and can exist in several protonation states. In this work, molecular mechanics force field parameters compatible with the CHARMM36 all-atom additive force field were derived for biologically important flavins, including riboflavin, flavin mononucleotide, and flavin adenine dinucleotide. The model was developed for important protonation and redox states of the isoalloxazine group. The partial charges were derived using the CHARMM force field parametrization strategy, where quantum mechanics water-solute interactions are used to target optimization. In addition to monohydrate energies and geometries, electrostatic potential around the compound was used to provide additional restraints during the charge optimization. Taking into account the importance of flavin-containing molecules special attention was given to the quality of bonded terms. All bonded terms, including stiff terms and torsion angle parameters, were parametrized using exhaustive potential energy surface scans. In particular, the model reproduces well the butterfly motion of isoalloxazine in the oxidized and reduced forms as predicted by quantum mechanics in gas phase. The model quality is illustrated by simulations of four flavoproteins. Overall, the presented molecular mechanics model will be of utility to model flavin cofactors in different redox states. © 2019 Wiley Periodicals, Inc.

Advanced molecular structural mechanics model for carbon nanotubes incorporating the 2nd generation REBO potential

Molecular mechanics models like the molecular structural mechanics (MSM) model have been proven to be a valuable tool for the investigation of carbon nanotubes. This class of models is based on a chemical force field representing the bonds present in the structure. Up to now, the underlying chemical force field applied in the MSM model is usually based on harmonic potentials. This simple approach comes with major drawbacks limiting the abilities of the MSM approach. In order to overcome these limitations, the present work integrates the 2nd generation reactive bond order potential (REBO), which is a sophisticated chemical force field, into the MSM approach. The development of this advanced MSM model is given in detail. As a demonstration of its capabilities, the elastic properties of different armchair and zig-zag CNTs are investigated numerically. It was found, that the results for the elastic properties differ significantly with the choice of the underlying chemical force field. The arising differences are discussed and reasons for the occurring behavior are given. The developed advanced MSM approach on the basis of the REBO potential strongly enhances the capabilities of the MSM approach while maintaining its excellent accessibility and applicability together with a low computational effort.