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Artykuły w czasopismach na temat "Complex systems- Molecular dynamics study"
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Borodin, Vladislav, Mikhail Bubenchikov, Alexey Bubenchikov, Dmitriy Mamontov, Sergey Azheev, and Alexandr Azheev. "Study of the Unstable Rotational Dynamics of a Tor-Fullerene Molecular System." Crystals 13, no. 2 (2023): 181. http://dx.doi.org/10.3390/cryst13020181.
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This work is devoted to modeling the dynamics of large molecules. The key issue in modeling the dynamics of real molecular systems is to correctly represent the temperature of the system using the available theoretical tools. In most works on molecular dynamics, vibrations of atoms inside a molecule are modeled with enviable persistence, which has nothing to do with physical temperature. These vibrations represent the energy internal to the molecule. Therefore, it should not be present in problems in the dynamics of inert molecular systems. In this work, by means of classical mechanics, it is shown that the simplest system containing only three molecular bodies, due to multiple acts of pair interactions of these bodies, reproduces the temperature even in an extremely complex unstable motion of the system. However, at the same time, it is necessary to separate the stochastic part of the movement from the deterministic one. Calculations also show that translational fluctuations in the motion of molecules make the greatest contribution to temperature. The contribution of rotational energy to the total energy of fluctuation motions is small. It follows from these results that the thermal state of the system is determined only by the translational temperature. The latter, in turn, opens up possibilities for a simplified description of many complex systems composed of carbon molecules such as fullerenes and nanotori.
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Kahana, Amit, and Doron Lancet. "Protobiotic Systems Chemistry Analyzed by Molecular Dynamics." Life 9, no. 2 (2019): 38. http://dx.doi.org/10.3390/life9020038.
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Systems chemistry has been a key component of origin of life research, invoking models of life’s inception based on evolving molecular networks. One such model is the graded autocatalysis replication domain (GARD) formalism embodied in a lipid world scenario, which offers rigorous computer simulation based on defined chemical kinetics equations. GARD suggests that the first pre-RNA life-like entities could have been homeostatically-growing assemblies of amphiphiles, undergoing compositional replication and mutations, as well as rudimentary selection and evolution. Recent progress in molecular dynamics has provided an experimental tool to study complex biological phenomena such as protein folding, ligand-receptor interactions, and micellar formation, growth, and fission. The detailed molecular definition of GARD and its inter-molecular catalytic interactions make it highly compatible with molecular dynamics analyses. We present a roadmap for simulating GARD’s kinetic and thermodynamic behavior using various molecular dynamics methodologies. We review different approaches for testing the validity of the GARD model by following micellar accretion and fission events and examining compositional changes over time. Near-future computational advances could provide empirical delineation for further system complexification, from simple compositional non-covalent assemblies towards more life-like protocellular entities with covalent chemistry that underlies metabolism and genetic encoding.
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Rapaport, D. C. "GPU molecular dynamics: Algorithms and performance." Journal of Physics: Conference Series 2241, no. 1 (2022): 012007. http://dx.doi.org/10.1088/1742-6596/2241/1/012007.
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Abstract A previous study of MD algorithms designed for GPU use is extended to cover more recent developments in GPU architecture. Algorithm modifications are described, togther with extensions to more complex systems. New measurements include the effects of increased parallelism on GPU performance, as well as comparisons with multiple-core CPUs using multitasking based on CPU threads and message passing. The results show that the GPU retains a significant performance advantage.
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Wang, Xiunan, Yi Liu, Jingcheng Xu, et al. "Molecular Dynamics Study of Stability and Diffusion of Graphene-Based Drug Delivery Systems." Journal of Nanomaterials 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/872079.
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Graphene, a two-dimensional nanomaterial with unique biomedical properties, has attracted great attention due to its potential applications in graphene-based drug delivery systems (DDS). In this work graphene sheets with various sizes and graphene oxide functionalized with polyethylene glycol (GO-PEG) are utilized as nanocarriers to load anticancer drug molecules including CE6, DOX, MTX, and SN38. We carried out molecular dynamics calculations to explore the energetic stabilities and diffusion behaviors of the complex systems with focuses on the effects of the sizes and functionalization of graphene sheets as well as the number and types of drug molecules. Our study shows that the binding of graphene-drug complex is favorable when the drug molecules and finite graphene sheets become comparable in sizes. The boundaries of finite sized graphene sheets restrict the movement of drug molecules. The double-side loading often slows down the diffusion of drug molecules compared with the single-side loading. The drug molecules bind more strongly with GO-PEG than with pristine graphene sheets, demonstrating the advantages of functionalization in improving the stability and biocompatibility of graphene-based DDS.
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Puzyrkov, Dmitry, Sergey Polyakov, Viktoriia Podryga, and Sergey Markizov. "Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics." EPJ Web of Conferences 173 (2018): 05014. http://dx.doi.org/10.1051/epjconf/201817305014.
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At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.
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Benton, Tim G., Stewart J. Plaistow, and Tim N. Coulson. "Complex population dynamics and complex causation: devils, details and demography." Proceedings of the Royal Society B: Biological Sciences 273, no. 1591 (2006): 1173–81. http://dx.doi.org/10.1098/rspb.2006.3495.
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Population dynamics result from the interplay of density-independent and density-dependent processes. Understanding this interplay is important, especially for being able to predict near-term population trajectories for management. In recent years, the study of model systems—experimental, observational and theoretical—has shed considerable light on the way that the both density-dependent and -independent aspects of the environment affect population dynamics via impacting on the organism's life history and therefore demography. These model-based approaches suggest that (i) individuals in different states differ in their demographic performance, (ii) these differences generate structure that can fluctuate independently of current total population size and so can influence the dynamics in important ways, (iii) individuals are strongly affected by both current and past environments, even when the past environments may be in previous generations and (iv) dynamics are typically complex and transient due to environmental noise perturbing complex population structures. For understanding population dynamics of any given system, we suggest that ‘the devil is in the detail’. Experimental dissection of empirical systems is providing important insights into the details of the drivers of demographic responses and therefore dynamics and should also stimulate theory that incorporates relevant biological mechanism.
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Pieroni, Michele, Francesco Madeddu, Jessica Di Martino, et al. "MD–Ligand–Receptor: A High-Performance Computing Tool for Characterizing Ligand–Receptor Binding Interactions in Molecular Dynamics Trajectories." International Journal of Molecular Sciences 24, no. 14 (2023): 11671. http://dx.doi.org/10.3390/ijms241411671.
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Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand–receptor binding interactions (lrbi) to be studied. In this study, we present MD–ligand–receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand–receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand–receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations.
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Domínguez, D., A. R. Bishop, and N. Grønbech-Jensen. "Coherence and Complexity in Condensed Matter: Josephson Junction Arrays." International Journal of Bifurcation and Chaos 07, no. 05 (1997): 979–88. http://dx.doi.org/10.1142/s0218127497000790.
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The importance of the mesoscopic bridge between microscopic and mesoscopic descriptions of complex, nonlinear-nonequilibrium extended dynamical systems is illustrated in a condensed matter context through three-dimensional Josephson junction arrays. Large-scale Langevin molecular dynamics is used to study novel transformer and melting effects, emphasizing the central roles of topological excitations (flux vortex lines) in determining mesoscopic patterns and dynamics — through flux line creation, annihilation, interaction and statistical mechanics.
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Hordijk, Wim, Mike Steel, and Stuart Kauffman. "Molecular Diversity Required for the Formation of Autocatalytic Sets." Life 9, no. 1 (2019): 23. http://dx.doi.org/10.3390/life9010023.
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Systems chemistry deals with the design and study of complex chemical systems. However, such systems are often difficult to investigate experimentally. We provide an example of how theoretical and simulation-based studies can provide useful insights into the properties and dynamics of complex chemical systems, in particular of autocatalytic sets. We investigate the issue of the required molecular diversity for autocatalytic sets to exist in random polymer libraries. Given a fixed probability that an arbitrary polymer catalyzes the formation of other polymers, we calculate this required molecular diversity theoretically for two particular models of chemical reaction systems, and then verify these calculations by computer simulations. We also argue that these results could be relevant to an origin of life scenario proposed recently by Damer and Deamer.
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Cassone, Giuseppe, Adriano Sofia, Jiri Sponer, A. Marco Saitta, and Franz Saija. "Ab Initio Molecular Dynamics Study of Methanol-Water Mixtures under External Electric Fields." Molecules 25, no. 15 (2020): 3371. http://dx.doi.org/10.3390/molecules25153371.
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Intense electric fields applied on H-bonded systems are able to induce molecular dissociations, proton transfers, and complex chemical reactions. Nevertheless, the effects induced in heterogeneous molecular systems such as methanol-water mixtures are still elusive. Here we report on a series of state-of-the-art ab initio molecular dynamics simulations of liquid methanol-water mixtures at different molar ratios exposed to static electric fields. If, on the one hand, the presence of water increases the proton conductivity of methanol-water mixtures, on the other, it hinders the typical enhancement of the chemical reactivity induced by electric fields. In particular, a sudden increase of the protonic conductivity is recorded when the amount of water exceeds that of methanol in the mixtures, suggesting that important structural changes of the H-bond network occur. By contrast, the field-induced multifaceted chemistry leading to the synthesis of e.g., hydrogen, dimethyl ether, formaldehyde, and methane observed in neat methanol, in 75:25, and equimolar methanol-water mixtures, completely disappears in samples containing an excess of water and in pure water. The presence of water strongly inhibits the chemical reactivity of methanol.