GROningen MAchine For Chemical Simulations Research Articles

ThermoPCD: a database of molecular dynamics trajectories of antibody-antigen complexes at physiologic and fever-range temperatures.

Progression of various cancers and autoimmune diseases is associated with changes in systemic or local tissue temperatures, which may impact current therapies. The role of fever and acute inflammation-range temperatures on the stability and activity of antibodies relevant for cancers and autoimmunity is unknown. To produce molecular dynamics (MD) trajectories of immune complexes at relevant temperatures, we used the Research Collaboratory for Structural Bioinformatics (RCSB) database to identify 50 antibody:antigen complexes of interest, in addition to single antibodies and antigens, and deployed Groningen Machine for Chemical Simulations (GROMACS) to prepare and run the structures at different temperatures for 100-500ns, in single or multiple random seeds. MD trajectories are freely available. Processed data include Protein Data Bank outputs for all files obtained every 50ns, and free binding energy calculations for some of the immune complexes. Protocols for using the data are also available. Individual datasets contain unique DOIs. We created a web interface, ThermoPCD, as a platform to explore the data. The outputs of ThermoPCD allow the users to relate thermally-dependent changes in epitopes:paratopes interfaces to their free binding energies, or against own experimentally derived binding affinities. ThermoPCD is a free to use database of immune complexes' trajectories at different temperatures that does not require registration and allows for all the data to be available for download. Database URL: https://sites.google.com/view/thermopcd/home.

Mechanism of long-range hydrophobic force based on cavitation of metastable liquid film

Hydrophobic force, a key driving force in colloid physicochemical system and biological macromolecular system, exhibits a distinct multi-scale effect. The prevailing scholarly consensus attributes long-range hydrophobic force to bubble bridging, facilitated by unstable liquid film cavitation, while short-range force is thought to arise from the reorganization of water molecules at the solid-liquid interface. However, a comprehensive theoretical study remains elusive. To further elucidate the mechanism of the long-range hydrophobic force based on unstable liquid film cavitation, we carry out systematic research on the long-range hydrophobic force between perfluorooctyl trichlorosilane hydrophobic particles and the surface, by utilizing atomic force microscopy (AFM) and molecular dynamics simulations. According to AFM force tests, the long-range hydrophobic force escalates incrementally with subsequent close contacts before reaching a plateau. On the tenth contact, the penetration curve exhibits a sudden jump to an adhesion distance of 502.01 nm. A distinct step in the retraction curve suggests the rupture of the cavitation bubble capillary bridge. Importantly, the classical capillary force mathematical model provides an effective fit for the penetration curve. Our calculations estimate the volume of the capillary bridge at 0.30 μm³, offering direct theoretical evidence of the unstable liquid film cavitation bubble capillary bridge. Further insights are gained from large-scale tensile molecular dynamics simulations by using GROningen MAchine for Chemical Simulations (GROMACS). The inherent correlation mechanism of the formation, evolution, and mechanical behavior of the cavitation bubble capillary bridge in the separation process of hydrophobic particles are further explored from a molecular perspective. The results demonstrate that the local pressure drop occurring at the moment of “jump-out” separation of the hydrophobic particles attracts nitrogen molecules to diffuse into the liquid film, thereby forming a cavitation bubble capillary bridge. Simultaneously, a jumping behavior is observed in the calculated spring potential curve at the moment of capillary bridge rupture. Finally, the influence of solution gas content on long-range hydrophobic force is investigated. There is a positive correlation between gas molecule content and both the growth rate of cavitation bubble capillary bridge volume and the length of capillary bridge stretch-rupture, further demonstrating the gas concentration dependence of long-range hydrophobic forces. In a word, revealing the long-range hydrophobic force mechanism based on the cavitation of unstable liquid film can enhance our understanding of the interaction between colloid physical chemistry and biological macromolecules. Meanwhile, hydrophobic force is the fundamental driving force of particle-bubble adhesion in mineral flotation system, and the revelation of its action mechanism has important guiding significance for regulating the actual mineral flotation process.

In vitro and in silico evaluations of actinomycin X2and actinomycin D as potent anti-tuberculosis agents.

Multidrug-resistant tuberculosis (MDR-TB) is one of the world's most devastating contagious diseases and is caused by the MDR-Mycobacterium tuberculosis (MDR-Mtb) bacteria. It is therefore essential to identify novel anti-TB drug candidates and target proteins to treat MDR-TB. Here, in vitro and in silico studies were used to investigate the anti-TB potential of two newly sourced actinomycins, actinomycin-X2 (act-X2) and actinomycin-D (act-D), from the Streptomyces smyrnaeus strain UKAQ_23 (isolated from the Jubail industrial city of Saudi Arabia). The anti-TB activity of the isolated actinomycins was assessed in vitro using the Mtb H37Ra, Mycobacterium bovis (BCG), and Mtb H37Rv bacterial strains, using the Microplate Alamar Blue Assay (MABA) method. In silico molecular docking studies were conducted using sixteen anti-TB drug target proteins using the AutoDock Vina 1.1.2 tool. The molecular dynamics (MD) simulations for both actinomycins were then performed with the most suitable target proteins, using the GROningen MAchine For Chemical Simulations (GROMACS) simulation software (GROMACS 2020.4), with the Chemistry at HARvard Macromolecular Mechanics 36m (CHARMM36m) forcefield for proteins and the CHARMM General Force Field (CGenFF) for ligands. In vitro results for the Mtb H37Ra, BCG, and Mtb H37Rv strains showed that act-X2 had minimum inhibitory concentration (MIC) values of 1.56 ±0.0, 1.56 ±0.0, and 2.64 ±0.07 µg/mL and act-D had MIC values of 1.56 ±0.0, 1.56 ±0.0, and 1.80 ±0.24 µg/mL respectively. The in silico molecular docking results showed that protein kinase PknB was the preferred target for both actinomycins, while KasA and pantothenate synthetase were the least preferred targets for act-X2and act-D respectively. The molecular dynamics (MD) results demonstrated that act-X2 and act-D remained stable inside the binding region of PknB throughout the simulation period. The MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) binding energy calculations showed that act-X2 was more potent than act-D. In conclusion, our results suggest that both actinomycins X2 and D are highly potent anti-TB drug candidates. We show that act-X2is better able to antagonistically interact with the protein kinase PknB target than act-D, and thus has more potential as a new anti-TB drug candidate.

An Overview of Molecular Dynamics Simulation for Food Products and Processes

Molecular dynamics (MD) simulation is a particularly useful technique in food processing. Normally, food processing techniques can be optimized to favor the creation of higher-quality, safer, more functional, and more nutritionally valuable food products. Modeling food processes through the application of MD simulations, namely, the Groningen Machine for Chemical Simulations (GROMACS) software package, is helpful in achieving a better understanding of the structural changes occurring at the molecular level to the biomolecules present in food products during processing. MD simulations can be applied to define the optimal processing conditions required for a given food product to achieve a desired function or state. This review presents the development history of MD simulations, provides an in-depth explanation of the concept and mechanisms employed through the running of a GROMACS simulation, and outlines certain recent applications of GROMACS MD simulations in the food industry for the modeling of proteins in food products, including peanuts, hazelnuts, cow’s milk, soybeans, egg whites, PSE chicken breast, and kiwifruit.

Visualizing structural changes of egg avidin to thermal and electric field stresses by molecular dynamics simulation

Eggs are one of the most common ingredients used by human beings due to their nutritional attributes and health benefits. However, eggs also contain an anti-nutrient known as avidin, which forms an avidin-biotin complex, resulting in biotin unavailable in the body for absorption. In the present study, molecular dynamics (MD) simulation was used to evaluate the effect of external stresses, including thermal and oscillating electric field (0.05 V/nm, 2450 MHz) at 300–353 K on the structural properties of avidin. The modeling was performed using a GROningen MAchine for Chemical Simulations (GROMACS) software. The alteration in conformation of avidin was evaluated in terms of the number of hydrogen bonds, root mean square deviation, the radius of gyration, and solvent accessible surface area. The application of thermal stress and electric field resulted in conformational changes in the avidin protein. The results also showed that hydrogen bonds have a significant influence on the stability of alpha-helices, which are responsible for the compactness of the molecule. Change in the hydrogen bonds can increase the surface area and hence the surface properties of avidin significantly. Thermal combined with electric field showed an application in inhibiting the activity of avidin present in egg white.

Diffusion of oxytocin in water: a molecular dynamics study

Classical molecular dynamics simulation is performed to estimate the diffusion coefficient of oxytocin in water at different temperatures, 288 K, 300 K, 313 K, 323 K, using GROningen Machine for Chemical Simulations (GROMOCS). The simulation is carried out using GROMOS43A1 force field and extended simple point charge (SPC/E) water model. The stability of the system is evaluated from energy profile of potential and kinetic energy, which assures well equilibrated molecular system. The self-diffusion coefficient of oxytocin and water is obtained from Einstein’s relation and binary diffusion coefficient is obtained from Darken’s relation. As temperature increases the diffusion coefficient also increases as per expectation. The diffusion coefficients of water from the present calculations agree well with the previously reported values, within the 10% of deviation. Furthermore, the activation energy has been studied using Arrhenius Plot.
 BIBECHANA 18 (2021) 108-117

A Computational Study to Identify Potential Inhibitors of SARS-CoV-2 Main Protease (Mpro) from Eucalyptus Active Compounds

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found to be a severe threat to global public health in late 2019. Nevertheless, no approved medicines have been found to inhibit the virus effectively. Anti-malarial and antiviral medicines have been reported to target the SARS-CoV-2 virus. This paper chose eight natural eucalyptus compounds to study their binding interactions with the SARS-CoV-2 main protease (Mpro) to assess their potential for becoming herbal drugs for the new SARS-CoV-2 infection virus. In-silico methods such as molecular docking, molecular dynamics (MD) simulations, and Molecular Mechanics Poisson Boltzmann Surface Area (MM/PBSA) analysis were used to examine interactions at the atomistic level. The results of molecular docking indicate that Mpro has good binding energy for all compounds studied. Three docked compounds, α-gurjunene, aromadendrene, and allo-aromadendrene, with highest binding energies of −7.34 kcal/mol (−30.75 kJ/mol), −7.23 kcal/mol (−30.25 kJ/mol), and −7.17 kcal/mol (−29.99 kJ/mol) respectively, were simulated with GROningen MAchine for Chemical Simulations (GROMACS) to measure the molecular interactions between Mpro and inhibitors in detail. Our MD simulation results show that α-gurjunene has the strongest binding energy of −20.37 kcal/mol (−85.21 kJ/mol), followed by aromadendrene with −18.99 kcal/mol (−79.45 kJ/mol), and finally allo-aromadendrene with −17.91 kcal/mol (−74.95 kJ/mol). The findings indicate that eucalyptus may be used to inhibit the Mpro enzyme as a drug candidate. This is the first computational analysis that gives an insight into the potential role of structural flexibility during interactions with eucalyptus compounds. It also sheds light on the structural design of new herbal medicinal products against Mpro.

Identification of Selective Novel Hits against Plasmodium falciparum Prolyl tRNA Synthetase Active Site and a Predicted Allosteric Site Using in silico Approaches.

Recently, there has been increased interest in aminoacyl tRNA synthetases (aaRSs) as potential malarial drug targets. These enzymes play a key role in protein translation by the addition of amino acids to their cognate tRNA. The aaRSs are present in all Plasmodium life cycle stages, and thus present an attractive malarial drug target. Prolyl tRNA synthetase is a class II aaRS that functions in charging tRNA with proline. Various inhibitors against Plasmodium falciparum ProRS (PfProRS) active site have been designed. However, none have gone through clinical trials as they have been found to be highly toxic to human cells. Recently, a possible allosteric site was reported in PfProRS with two possible allosteric modulators: glyburide and TCMDC-124506. In this study, we sought to identify novel selective inhibitors targeting PfProRS active site and possible novel allosteric modulators of this enzyme. To achieve this, virtual screening of South African natural compounds against PfProRS and the human homologue was carried out using AutoDock Vina. The modulation of protein motions by ligand binding was studied by molecular dynamics (MD) using the GROningen MAchine for Chemical Simulations (GROMACS) tool. To further analyse the protein global motions and energetic changes upon ligand binding, principal component analysis (PCA), and free energy landscape (FEL) calculations were performed. Further, to understand the effect of ligand binding on the protein communication, dynamic residue network (DRN) analysis of the MD trajectories was carried out using the MD-TASK tool. A total of ten potential natural hit compounds were identified with strong binding energy scores. Binding of ligands to the protein caused observable global and residue level changes. Dynamic residue network calculations showed increase in betweenness centrality (BC) metric of residues at the allosteric site implying these residues are important in protein communication. A loop region at the catalytic domain between residues 300 and 350 and the anticodon binding domain showed significant contributions to both PC1 and PC2. Large motions were observed at a loop in the Z-domain between residues 697 and 710 which was also in agreement with RMSF calculations that showed increase in flexibility of residues in this region. Residues in this loop region are implicated in ATP binding and thus a change in dynamics may affect ATP binding affinity. Free energy landscape (FEL) calculations showed that the holo protein (protein-ADN complex) and PfProRS-SANC184 complexes were stable, as shown by the low energy with very few intermediates and hardly distinguishable low energy barriers. In addition, FEL results agreed with backbone RMSD distribution plots where stable complexes showed a normal RMSD distribution while unstable complexes had multimodal RMSD distribution. The betweenness centrality metric showed a loss of functional importance of key ATP binding site residues upon allosteric ligand binding. The deep basins in average L observed at the allosteric region imply that there is high accessibility of residues at this region. To further analyse BC and average L metrics data, we calculated the ΔBC and ΔL values by taking each value in the holo protein BC or L matrix less the corresponding value in the ligand-bound complex BC or L matrix. Interestingly, in allosteric complexes, residues located in a loop region implicated in ATP binding had negative ΔL values while in orthosteric complexes these residues had positive ΔL values. An increase in contact frequency between residues Ser263, Thr267, Tyr285, and Leu707 at the allosteric site and residues Thr397, Pro398, Thr402, and Gln395 at the ATP binding TXE loop was observed. In summary, this study identified five potential orthosteric inhibitors and five allosteric modulators against PfProRS. Allosteric modulators changed ATP binding site dynamics, as shown by RMSF, PCA, and DRN calculations. Changes in dynamics of the ATP binding site and increased contact frequency between residues at the proposed allosteric site and the ATP binding site may explain how allosteric modulators distort the ATP binding site and thus might inhibit PfProRS. The scaffolds of the identified hits in the study can be used as a starting point for antimalarial inhibitor development with low human cytotoxicity.

A computational approach for investigating the mutational landscape of RAC-alpha serine/threonine-protein kinase (AKT1) and screening inhibitors against the oncogenic E17K mutation causing breast cancer

Breast cancer (BC) is the most commonly diagnosed cancer among females worldwide, and among the BC-associated mutations in various proteins, mutations in the RAC-alpha serine/threonine-protein kinase (AKT1) remain the most dominant. We thus attempted to understand the potential molecular pathogenicity profile of the mutations in AKT1 using a comprehensive computational protocol involving analyses of biochemistry-disruption and destabilizing properties and conservation. Our predictions revealed that E17K, R67W, V164G, E319G, R391G, D32Y, L52H, L52R, and W80R were the most pathogenic mutations. In addition, the change of glutamate to lysine at position 17 of AKT1 (E17K) was found to be highly predominant. An extensive two-step molecular dynamics (simple and complex) simulation (MDS) using GROMACS (GROningen MAchine for Chemical Simulations) was then initiated to analyze and understand the structural impact of the E17K mutation on the function of AKT1. The simple MDS analysis revealed that the E17K mutation decreases the compactness and intramolecular hydrogen bonds of the protein. We also performed a virtual screening analysis with 19 AKT inhibitors obtained from the Selleck Chemicals website those satisfied the Lipinski rule of 5. Among these 19 compounds, Akti-1/2 exhibited the best binding affinity with both native AKT1 and the E17K mutant. The molecular interaction study also revealed that the co-crystallized AKT1 inhibitor N-(4-(5-(3-acetamidophenyl)-2-(2-aminopyridin-3-yl)-3H-imidazo [4,5-b]pyridin-3-yl)benzyl)-3-fluorobenzamide (12j) exhibited a better interaction with native AKT1 compared with the E17K mutant AKT1 protein, whereas, Akti-1/2 exhibited the opposite effects, i.e., a better interaction with the E17K mutant AKT1 than the native AKT1. These findings from the interaction analysis were further supported by the complex MDS, which measured the compactness and intermolecular hydrogen bonds of the proteins. The results obtained in this study suggest that Akti-1/2 might be a better inhibitor for the treatment of BC caused by the E17K mutation in AKT1.

Numerical modelling of free energy for methanol and water mixtures for biodiesel production

As the demand for energy is ever increasing, biodiesel has become a major alternative to fossil fuels, primarily due to the latter’s depletion rate. In methanol-water rectification, a vital part of the biodiesel production process, distillation is the preferred technique to recover methanol from water. This study aims to investigate the excess Gibbs free energy (ΔG) behavior on methanol in a water mixture, for the binary system. The study was conducted using the GROningen MAchine for Chemical Simulations (GROMACS©). The effect of several important parameters, namely, sub-atmospheric pressure, temperature and methanol concentration, were investigated on the excess Gibbs free energy of methanol in water. The simulation results were partially validated, since the experimental data was limited. The results demonstrate that the excess Gibbs free energy of methanol in a water mixture positively increases with an increase in methanol concentration, until it reaches a threshold concentration of 0.5. The positive excess Gibbs free energy of the mixture system indicates that the process is not spontaneous and requires additional energy to occur. Increasing the temperature directly increases the excess Gibbs free energy of the system. Increasing the pressure does not have a significant increase on the excess Gibbs free energy. The simulation results are comparable with the experimental results; as validated by the Pearson correlation coefficient (ρ) = +0.9982. This study is beneficial to predict the thermodynamic behavior of methanol in a water system, in order to contribute to biodiesel production process optimization.

Maximizing resource usage in multifold molecular dynamics with rCUDA

The full-understanding of the dynamics of molecular systems at the atomic scale is of great relevance in the fields of chemistry, physics, materials science, and drug discovery just to name a few. Molecular dynamics (MD) is a widely used computer tool for simulating the dynamical behavior of molecules. However, the computational horsepower required by MD simulations is too high to obtain conclusive results in real-world scenarios. This is mainly motivated by two factors: (1) the long execution time required by each MD simulation (usually in the nanoseconds and microseconds scale, and beyond) and (2) the large number of simulations required in drug discovery to study the interactions between a large library of compounds and a given protein target. To deal with the former, graphics processing units (GPUs) have come up into the scene. The latter has been traditionally approached by launching large amounts of simulations in computing clusters that may contain several GPUs on each node. However, GPUs are targeted as a single node that only runs one MD instance at a time, which translates into low GPU occupancy ratios and therefore low throughput. In this work, we propose a strategy to increase the overall throughput of MD simulations by increasing the GPU occupancy through virtualized GPUs. We use the remote CUDA (rCUDA) middleware as a tool to decouple GPUs from CPUs, and thus enabling multi-tenancy of the virtual GPUs. As a working test in the drug discovery field, we studied the binding process of a novel flavonol to DNA with the GROningen MAchine for Chemical Simulations (GROMACS) MD package. Our results show that the use of rCUDA provides with a 1.21× speed-up factor compared to the CUDA counterpart version while requiring a similar power budget.

Application of the interface potential approach for studying wetting behavior within a molecular dynamics framework.

We introduce a means to implement the interface potential approach for computing wetting properties within a molecular dynamics framework. The general approach provides a means to determine the contact angle of a liquid droplet on a solid substrate in a mother vapor. We present a framework for implementing "spreading" and "drying" versions of the method within an isothermal-isobaric ensemble. Two free energy methods are considered: cumulative integration of average force profile and multistate Bennett acceptance ratio. An umbrella sampling strategy is used to restrain volume fluctuations and to ensure adequate sampling of a broad volume range. We explore implementation of the approach with the GROningen MAchine for Chemical Simulations and the Large-scale Atomic/Molecular Massively Parallel Simulator. We test the accuracy and efficiency of the method with models consisting of a monoatomic Lennard-Jones fluid in the vicinity of a structureless or atomistically detailed substrate. Our results show that one can successfully generate the drying potential within the framework pursued here. The efficiency of the method is strongly dependent upon how one handles the dynamics of the two confining walls. These decisions impact the rate of volume fluctuations, and therefore, the quality of the volume distributions collected. Our efforts to implement the spreading method with molecular dynamics alone proved unsuccessful. The rate at which the configuration space of the vapor phase evolves is insufficient. We show how one can overcome this challenge by implementing a coupled molecular dynamics/Monte Carlo approach. Finally, we show how one can determine the variation in interfacial properties with temperature and substrate strength.

Discovery of Small Molecules that Target Vascular Endothelial Growth Factor Receptor-2 Signalling Pathway Employing Molecular Modelling Studies.

Angiogenesis is defined as the formation of new blood vessels and is a key phenomenon manifested in a host of cancers during which tyrosine kinases play a crucial role. Vascular endothelial growth factor receptor-2 (VEGFR-2) is pivotal in cancer angiogenesis, which warrants the urgency of discovering new anti-angiogenic inhibitors that target the signalling pathways. To obtain this objective, a structure-based pharmacophore model was built from the drug target VEGFR-2 (PDB code: 4AG8), complexed with axitinib and was subsequently validated and employed as a 3D query to retrieve the candidate compounds with the key inhibitory features. The model was escalated to molecular docking studies resulting in seven candidate compounds. The molecular docking studies revealed that the seven compounds displayed a higher dock score than the reference-cocrystallised compound. The GROningen MAchine for Chemical Simulations (GROMACS) package guided molecular dynamics (MD) results determined their binding mode and affirmed stable root mean square deviation. Furthermore, these compounds have preserved their key interactions with the residues Glu885, Glu917, Cys919 and Asp1046. The obtained findings deem that the seven compounds could act as novel anti-angiogenic inhibitors and may further assist as the prototype in designing and developing new inhibitors.

Accuracy and precision of simulated free energies: water permeation of hydrated DPPC bilayers as a paradigm

ABSTRACTFree energies play a determining role in the transmembrane permeability of lipid bilayers to small molecules. The precision of the calculated free energies, in particular, can seriously affect the reliability of simulations of permeation events. Free energy profiles are evaluated with different known techniques for a water molecule inside a hydrated bilayer in order to assess the accuracy and precision of free energy calculations as well as the associated computational cost within the popular Groningen Machine for Chemical Simulations (GROMACS) software package. The different computational approaches employed include the method of constrained particles, umbrella sampling and thermodynamic integration. When free energy profiles computed from MD trajectories of similar timescales are compared, umbrella sampling is found to afford the best precision among the methods investigated, albeit at the expense of computational effort.

A generalised Landau-Lifshitz fluctuating hydrodynamics model for concurrent simulations of liquids at atomistic and continuum resolution.

A new hybrid molecular dynamics-hydrodynamics method based on the analogy with two-phase flows is implemented that takes into account the feedback of molecular dynamics on hydrodynamics consistently. The consistency is achieved by deriving a discrete system of fluctuating hydrodynamic equations whose solution converges to the locally averaged molecular dynamics field exactly in terms of the locally averaged fields. The new equations can be viewed as a generalisation of the classical continuum Landau-Lifshitz fluctuating hydrodynamics model in statistical mechanics to include a smooth transition from large-scale continuum hydrodynamics that obeys a Gaussian statistics to all-atom molecular dynamics. Similar to the classical Landau-Lifshitz fluctuating hydrodynamics model, the suggested generalised Landau-Lifshitz fluctuating hydrodynamics equations are too complex for analytical solution; hence, a computational scheme for solving these equations is suggested. The scheme is implemented in a popular open-source molecular dynamics code GROMACS (GROningen MAchine for Chemical Simulations), and numerical examples are provided for liquid argon simulations under equilibrium conditions and under macroscopic flow effects.

On the Performance and Energy Consumption of Molecular Dynamics Applications for Heterogeneous CPU-GPU Platforms Based on Gromacs

Abstract High Performance Computing (HPC) accelerates life science discoveries by enabling scientists to analyze large data sets, to develop detailed models of entire biological systems and to simulate complex biological processes. As computational experiments, molecular dynamics simulations are widely used in life sciences to evaluate the equilibrium nature of classical many-body systems The modelling and molecular dynamics study of surfactant, polymer solutions and the stability of proteins and nucleic acids under different conditions, as well as deoxyribonucleic acid proteins are studied. The study aims to understand the scaling behavior of Gromacs (Groningen machine for chemical simulations) on various platforms, and the maximum performance in the prospect of energy consumption that can be accomplished by tuning the hardware and software parameters. Different system sizes (48K, 64K, and 272K) from scientific investigations have been studied show that the GPU (Graphics Processing Unit) scales rather beneficial than other resources, i.e., with GPU support. We track 2-3 times speedup compared to the latest multi-core CPUs. However, the so-called “threading effect” leads to the better results.

Understanding the molecular mechanism of improved proliferation and osteogenic potential of human mesenchymal stem cells grown on a polyelectrolyte complex derived from non-mulberry silk fibroin and chitosan

The development of engineered bone tissue, as a promising alternative to conventional bone grafts, has so far not proven successful and still remains challenging. Thus, attempts have been made in the present study to synthesize polyelectrolyte complex (PEC) scaffolds by blending chitosan (CS) to silk fibroin (SF) derived from the non-mulberry silkworm (Antheraea pernyi) at three different pH values (5.0, 6.0, and 7.0), and to characterize them in terms of morphology, ultrastructure and mechanical properties with scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy, x-ray diffraction and tensile strength analyses. The prepared PEC scaffolds showed a mean pore size of 130 μm, as revealed by SEM analysis, and a comparatively higher compressive strength. The findings of in vitro cytocompatibility, in vivo biocompatibility and osteogenic marker (genes/proteins) analysis suggest that the PECs blended at pH 7.0 showed greater stability and enhanced growth and an osteogenic differentiation capability of human mesenchymal stem cells (MSCs). To aid our understanding of protein–polyion binding mechanisms, we employed a molecular docking and simulation study of SF macrodomains and CS oligomer using Schrödinger 14 and GROMACS (Groningen Machine for Chemical Simulations) software. The study involved analytical techniques for macromolecular solution characterization and theoretical simulations based on molecular dynamics. The computational studies confirmed the presence of an integral RGD sequence that played a vital role in superior cell-attachment, proliferation and osteogenic differentiation of MSCs grown on the developed SF–CS PEC scaffolds.

Study of structural and transport properties of argon, krypton, and their binary mixtures at different temperatures.

Molecular dynamics simulation of argon, krypton, and their binary mixtures were performed at different temperatures and constant pressure (P = 1.013 bar) using GROMACS - Groningen Machine for Chemical Simulations. The gases are modeled by Lennard-Jones pair potential, with parameters taken from the literature. The study of radial distribution functions (RDFs) shows a single peak which indicates that there is no packing effect in gaseous state for argon, krypton, and their binary mixtures. The self-diffusion coefficients of argon and krypton is determined by using mean-square displacement(MSD) method and the mutual diffusion coefficients of binary mixtures are determined using Darken's relation. The values of simulated diffusion coefficients are compared with their corresponding theoretical values, numerical estimation, and experimental data. A good agreement between these sets of data is found. The diffusion coefficients obey Arrhenius behavior to a good extent for both pure components and binary mixtures. The values of simulated diffusion coefficient are used to estimate viscosities and thermal conductivities which agree with theoretical values, numerical estimation, and experimental data within 10 %. These results support that the LJ potential is sufficient for description of molecular interactions in argon and krypton.

Molecular Dynamics Simulation and Analysis of the Antimicrobial Peptide-Lipid Bilayer Interactions.

A great deal of research has been undertaken in order to discover antimicrobial peptides (AMPs) with unexploited mechanisms of action to counteract the health-threatening issues associated with bacterial resistance. The intrinsic effectiveness of AMPs is strongly influenced by their initial interactions with the bacterial cell membrane. Understanding these interactions in the atomistic details is important for the design of the less prone bacteria-resistant peptides. However, these studies always require labor-intensive and difficult steps. With this regard, modeling studies of the AMPs binding to simple lipid membrane systems, e.g., lipid bilayers, is of great advantage. In this chapter, we present an applicable step-by-step protocol to run the molecular dynamics (MD) simulation of the interaction between cyclo-RRWFWR (c-WFW) (a small cyclic AMP) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer using the Groningen machine for chemical simulations (GROMACS) package. The protocol as described here may simply be optimized for other peptide-lipid systems of interest.

Water nanodroplet on a graphene surface—a new old system

The major subject of our study is the accuracy of contact angle calculations. Reporting new simulation data for graphene-water systems, we show that the majority of previously reported data should be treated with caution, since the proper contact angle can be recorded only after a sufficiently long simulation time. It has been proven that—if one wants to gain accuracy greater than 0.1°—long calculations (exceeding 50 ns) are required. Finally, we also show, using both a Groningen Machine for Chemical Simulations (GROMACS) package and our new molecular dynamics (MD) code, that the changes in the contact angle, caused by graphene bottom layer rotation, are within the range of calculation error. We also propose a novel definition of the bottom of the droplet as the height where the density is half the density of liquid water. This new definition is applied in the method of the contact angle calculation from the MD simulation data.