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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.
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Vieira, Ana Paula Bastos Ferreira, Natália de Farias Silva, Davi do Socorro Barros Brasil, José Otávio Carréra Silva Junior, and Roseane Maria Ribeiro Costa. "Computational simulation of nanostructured lipid carrier containing lipids from Cupuassu (Theobroma grandiflorum) seed fat: Design, interaction and molecular dynamic study." Research, Society and Development 9, no. 11 (2020): e92191110433. http://dx.doi.org/10.33448/rsd-v9i11.10433.
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Drug delivery systems are constantly evolving and developing, as well as the search for promising and effective formulations for drug delivery. Computational simulation methods enable the development of complex systems, such as nanostructured lipid carriers (NLC), the understanding of interaction and dynamics between drug molecule and its transporter. In this work, aimed to simulate a NLC containing cupuassu fat triacylglycerols, carnauba wax and caprylic/capric acid triacylglycerol, stabilized with Tween 80 and Pluronic and ketoconazole enantiomer as drug was simulated. Initially, lipid mixtures were studied by Differential Scanning Calorimetry and X-ray diffraction. Subsequently, computational studies were carried out, among which Molecular Docking of ketoconazole to the lipid mixture and Molecular Dynamics of NLC system containing ketoconazole. From the results obtained it was possible to observe the main binding affinities of the drug and provide a better NLC formulation. It was also possible to propose a three-dimensional NLC model that was stable after molecular dynamics and ideal for future experimental studies.
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Chavent, Matthieu, Tyler Reddy, Joseph Goose, et al. "Methodologies for the analysis of instantaneous lipid diffusion in md simulations of large membrane systems." Faraday Discuss. 169 (2014): 455–75. http://dx.doi.org/10.1039/c3fd00145h.
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Interactions between lipids and membrane proteins play a key role in determining the nanoscale dynamic and structural properties of biological membranes. Molecular dynamics (MD) simulations provide a valuable tool for studying membrane models, complementing experimental approaches. It is now possible to simulate large membrane systems, such as simplified models of bacterial and viral envelope membranes. Consequently, there is a pressing need to develop tools to visualize and quantify the dynamics of these immense systems, which typically comprise millions of particles. To tackle this issue, we have developed visual and quantitative analyses of molecular positions and their velocity field using path line, vector field and streamline techniques. This allows us to highlight large, transient flow-like movements of lipids and to better understand crowding within the lipid bilayer. The current study focuses on visualization and analysis of lipid dynamics. However, the methods are flexible and can be readily applied to e.g. proteins and nanoparticles within large complex membranes. The protocols developed here are readily accessible both as a plugin for the molecular visualization program VMD and as a module for the MDAnalysis library.
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Wysocka, Emilia M., Matthew Page, James Snowden, and T. Ian Simpson. "Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network." PeerJ 10 (December 15, 2022): e14516. http://dx.doi.org/10.7717/peerj.14516.
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Dynamic modelling has considerably improved our understanding of complex molecular mechanisms. Ordinary differential equations (ODEs) are the most detailed and popular approach to modelling the dynamics of molecular systems. However, their application in signalling networks, characterised by multi-state molecular complexes, can be prohibitive. Contemporary modelling methods, such as rule- based (RB) modelling, have addressed these issues. The advantages of RB modelling over ODEs have been presented and discussed in numerous reviews. In this study, we conduct a direct comparison of the time courses of a molecular system founded on the same reaction network but encoded in the two frameworks. To make such a comparison, a set of reactions that underlie an ODE model was manually encoded in the Kappa language, one of the RB implementations. A comparison of the models was performed at the level of model specification and dynamics, acquired through model simulations. In line with previous reports, we confirm that the Kappa model recapitulates the general dynamics of its ODE counterpart with minor differences. These occur when molecules have multiple sites binding the same interactor. Furthermore, activation of these molecules in the RB model is slower than in the ODE one. As reported for other molecular systems, we find that, also for the DARPP-32 reaction network, the RB representation offers a more expressive and flexible syntax that facilitates access to fine details of the model, easing model reuse. In parallel with these analyses, we report a refactored model of the DARPP-32 interaction network that can serve as a canvas for the development of more complex dynamic models to study this important molecular system.
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Salehi, Mitra, Hanifeh Shariatifar, Morteza Ghanbari Johkool, and Alireza Farasat. "A comprehensive study of HSA interaction with TMP using molecular docking and molecular dynamics methods: as an appropriate tool for drug delivery systems." Journal of Qazvin University of Medical Sciences 25, no. 2 (2022): 6. http://dx.doi.org/10.32598/jqums.25.2.2125.1.
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Background: Human serum albumin (HSA) is one of the most prominent protein in human blood. Trimethoprim (TMP) is an efficient antibiotic drug for treatment of pneumocystis pneumonia (PCP). Patients with HIV/AIDS and cancer are extremely affected by the disease due to immune system deficiency. Objective: The aim of this study is to evaluate the molecular dynamics simulation (MD) of HSA with TMP for drug delivery systems. Materials and methods: In the first step, the 3D structure of HSA and TMP were provided by PDB and PubChem respectively. Then, the molecular docking was done via AutoDock Vina software and the best complex was selected due to the lowest binding energy. Finally, the structural characteristics of the above complex was evaluated. Results: The results showed that TMP binds to the HSA molecule with a binding energy of -7.3 kcal/mol and this binding causes changes in third and second structure of the HSA. Thus, the RMSD and RG results proved the third structural changes and the results obtained from DSSP confirmed the second structural modifications. The TMP-HSA complex formation accompanied with hydrophobic interaction between residues; Tyr150 and Ala291, His288, Leu238, Leu219, Lys199, Lys195, Glu153 and TMP. The TMP molecule had two hydrogen bond with Arg222 residue and three with Ser192. Furthermore, the final PDB file of the MD simulation process showed that the TMP molecule had reaction HSA (IIA chain). Conclusion: Due to the extensive application of TMP in infectious disease and appropriate interaction with HSA, the complex could be used for targeted transport of nanoparticles in the future.
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JAKSE, NOEL, and ALAIN PASTUREL. "LOCAL ORDER OF LIQUID AND UNDERCOOLED TRANSITION METAL BASED SYSTEMS: AB INITIO MOLECULAR DYNAMICS STUDY." Modern Physics Letters B 20, no. 12 (2006): 655–74. http://dx.doi.org/10.1142/s0217984906011177.
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An overview of a recent series of ab initio molecular dynamics (MD) simulations for pure liquid transition metals as well as for transition metals (TM) based liquid alloys is presented. The aim is to investigate the local structure of these systems and their evolution upon undercooling, and our results are analyzed through a three-dimensional picture of the short-ranger order (SRO) by means of the common-neighbor analysis. Recent diffraction experiments indicate that the structure of both pure metals and alloys in undercooled states is dominated by an icosahedral SRO. We find that the five-fold symmetry is already present in the liquid state of all the studied systems. However our findings show that the five-fold symmetry in the liquid state as well as its evolution upon undercooling depends on the system under consideration. For Ni , Zr , and Ta , local configurations are more complex than that given by the simple icosahedron. For Al 80 Ni 20 and Al 80 Mn 20 alloys, local configurations are the result of a strong competition between chemical and topological effects; the key role played by the occurrence of localized magnetic moments of Mn atoms to interpret their short-range arrangements is emphasized, and the time evolution of the configurations is examined in terms of the mean square displacements.
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Grest, Gary S., Martin-D. Lacasse, and Michael Murat. "Molecular-Dynamics Simulations of Polymer Surfaces and Interfaces." MRS Bulletin 22, no. 1 (1997): 27–31. http://dx.doi.org/10.1557/s0883769400032309.
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From a single chain in a dilute solution to an entangled polymer melt, from bulk systems to more complex interfacial problems, computer simulations have played a critical role not only in testing the basic assumptions of various theoretical models but also in interpreting experimental results. Early computer simulations of polymers were mostly carried out on a lattice using Monte Carlo methods. This approach has led to significant progress in recent years and will continue to do so in many areas. In some cases however, for example in the study of shear, lattice models have serious limitations. For this reason and also due to the availability of more powerful computers, continuum, off-lattice polymer models have recently become popular. In this article, we review some of the recent progress in studying polymers at surfaces and interfaces using continuum models.
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Thorneywork, Alice L., Jannes Gladrow, Yujia Qing, et al. "Direct detection of molecular intermediates from first-passage times." Science Advances 6, no. 18 (2020): eaaz4642. http://dx.doi.org/10.1126/sciadv.aaz4642.
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All natural phenomena are governed by energy landscapes. However, the direct measurement of this fundamental quantity remains challenging, particularly in complex systems involving intermediate states. Here, we uncover key details of the energy landscapes that underpin a range of experimental systems through quantitative analysis of first-passage time distributions. By combined study of colloidal dynamics in confinement, transport through a biological pore, and the folding kinetics of DNA hairpins, we demonstrate conclusively how a short-time, power-law regime of the first-passage time distribution reflects the number of intermediate states associated with each of these processes, despite their differing length scales, time scales, and interactions. We thereby establish a powerful method for investigating the underlying mechanisms of complex molecular processes.
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Uratani, Hiroki. "(Invited) Simulating Dynamic Excitons Via Quantum Molecular Dynamics: A Case Study in Lead Halide Perovskites." ECS Meeting Abstracts MA2022-01, no. 13 (2022): 904. http://dx.doi.org/10.1149/ma2022-0113904mtgabs.
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The ultrafast electronic and structural dynamics invoked by photoexcitation, i.e., “dynamic exciton” phenomena, not only are important in the context of practical applications such as solar cells, but also raise many questions from the viewpoint of fundamental science. Experimental measurement, computational simulations, and theoretical interpretation will be the three pillars for deciphering the dynamic exciton phenomena. From the viewpoint of computational simulations, molecular dynamics (MD) techniques combined with quantum chemical calculations, i.e., quantum molecular dynamics (QMD), has been the popular tool to simulate the dynamic exciton phenomena. The quantum chemical calculations, which are typically conducted on the basis of the density-functional theory (DFT), require the large computational resources and time. These have been the limiting factors for the accessible spatial and time scales by the QMD simulations. To extend the coverage of simulations to more complex, large-scale systems, we have developed efficient excited-state QMD methods that can include nonadiabatic effects. Our method combines the density-functional tight binding (DFTB) method, which is an approximate DFT, and the surface hopping method, which is a theoretical framework to incorporate the nonadiabatic effects into the QMD simulations. The method was further improved to be suitable for condensed-phase simulations explicitly including the environment, i.e., solvent, by using a “divide-and-conquer” style quantum chemical calculation technique. These theoretical framework enables us to simulate the coupled electronic–structural dynamics in excited states of systems consisting of 102–103 atoms[1,2,3]. In addition, using the developed method, we conducted the real-time simulations of the ultrafast processes invoked by photoexcitation of lead iodide perovskites, which are known as the key materials for perovskite solar cells. The dissociation of the exciton into the positive and negative charge carriers was observed. Moreover, the hot carrier cooling, where the charge carriers dissipate excess energy via the electron–phonon coupling and relax to the band edges, was also tracked. Finally, the direct evidence of the polaron formation, where the structural deformation is induced by the presence of charge carriers, was observed. These results highlight the importance of the coupling between electronic and structural degrees of freedom. In the talk, recent improvements in the methodology and future perspectives will also be presented[5]. References [1] H. Uratani and H. Nakai, J. Chem. Phys. 152, 224109 (2020). [2] H. Uratani, T. Morioka, T. Yoshikawa, and H. Nakai, J. Chem. Theory Comput. 16, 7299 (2020). [3] H. Uratani, T. Yoshikawa, and H. Nakai, J. Chem. Theory Comput. 17, 1290 (2021). [4] H. Uratani and H. Nakai, J. Phys. Chem. Lett. 11, 4448 (2020). [5] H. Uratani and H. Nakai, J. Chem. Theory Comput. in press. Figure 1
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Hofer, Thomas S. "Perspectives for hybrid ab initio/molecular mechanical simulations of solutions: from complex chemistry to proton-transfer reactions and interfaces." Pure and Applied Chemistry 86, no. 2 (2014): 105–17. http://dx.doi.org/10.1515/pac-2014-5019.
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Abstract As a consequence of the ongoing development of enhanced computational resources, theoretical chemistry has become an increasingly valuable field for the investigation of a variety of chemical systems. Simulations employing a hybrid quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) technique have been shown to be a particularly promising approach, whenever ultrafast (i.e., picosecond) dynamical properties are to be studied, which are in many cases difficult to access via experimental techniques. Details of the quantum mechanical charge field (QMCF) ansatz, an advanced QM/MM protocol, are discussed and simulation results for various systems ranging from simple ionic hydrates to solvated organic molecules and coordination complexes in solution are presented. A particularly challenging application is the description of proton-transfer reactions in chemical simulations, which is a prerequisite to study acidified and basic systems. The methodical requirements for a combination of the QMCF methodology with a dissociative potential model for the description of the solvent are discussed. Furthermore, the possible extension of QM/MM approaches to solid/liquid interfaces is outlined.
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Monachino, Enrico, Lisanne M. Spenkelink, and Antoine M. van Oijen. "Watching cellular machinery in action, one molecule at a time." Journal of Cell Biology 216, no. 1 (2016): 41–51. http://dx.doi.org/10.1083/jcb.201610025.
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Single-molecule manipulation and imaging techniques have become important elements of the biologist’s toolkit to gain mechanistic insights into cellular processes. By removing ensemble averaging, single-molecule methods provide unique access to the dynamic behavior of biomolecules. Recently, the use of these approaches has expanded to the study of complex multiprotein systems and has enabled detailed characterization of the behavior of individual molecules inside living cells. In this review, we provide an overview of the various force- and fluorescence-based single-molecule methods with applications both in vitro and in vivo, highlighting these advances by describing their applications in studies on cytoskeletal motors and DNA replication. We also discuss how single-molecule approaches have increased our understanding of the dynamic behavior of complex multiprotein systems. These methods have shown that the behavior of multicomponent protein complexes is highly stochastic and less linear and deterministic than previously thought. Further development of single-molecule tools will help to elucidate the molecular dynamics of these complex systems both inside the cell and in solutions with purified components.
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Yuhara, Daisuke, Brian C. Barnes, Donguk Suh, et al. "Nucleation rate analysis of methane hydrate from molecular dynamics simulations." Faraday Discussions 179 (2015): 463–74. http://dx.doi.org/10.1039/c4fd00219a.
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Clathrate hydrates are solid crystalline structures most commonly formed from solutions that have nucleated to form a mixed solid composed of water and gas. Understanding the mechanism of clathrate hydrate nucleation is essential to grasp the fundamental chemistry of these complex structures and their applications. Molecular dynamics (MD) simulation is an ideal method to study nucleation at the molecular level because the size of the critical nucleus and formation rate occur on the nano scale. Various analysis methods for nucleation have been developed through MD to analyze nucleation. In particular, the mean first-passage time (MFPT) and survival probability (SP) methods have proven to be effective in procuring the nucleation rate and critical nucleus size for monatomic systems. This study assesses the MFPT and SP methods, previously used for monatomic systems, when applied to analyzing clathrate hydrate nucleation. Because clathrate hydrate nucleation is relatively difficult to observe in MD simulations (due to its high free energy barrier), these methods have yet to be applied to clathrate hydrate systems. In this study, we have analyzed the nucleation rate and critical nucleus size of methane hydrate using MFPT and SP methods from data generated by MD simulations at 255 K and 50 MPa. MFPT was modified for clathrate hydrate from the original version by adding the maximum likelihood estimate and growth effect term. The nucleation rates calculated by MFPT and SP methods are within 5%, and the critical nucleus size estimated by the MFPT method was 50% higher, than values obtained through other more rigorous but computationally expensive estimates. These methods can also be extended to the analysis of other clathrate hydrates.
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Černušák, Ivan, Jozef Federič, Pavel Jungwirth, and Milan Uhlár. "Effects of micro-hydration in proton transfer from H2S·NO+ complex to water: Ab initio and molecular dynamics study." Collection of Czechoslovak Chemical Communications 76, no. 5 (2011): 585–603. http://dx.doi.org/10.1135/cccc2011047.
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We have studied several microhydrated (H2O)n·NO+·H2S structures (n = 1–3) and their fragments using wave-function based approach (coupled-clusters including single, double and non-iterative triple substitutions – CCSD(T) and second-order perturbation theory – MP2) and also employing density functional theory (with BLYP and ωB97XD functional). MP2 energetics is very close to CCSD(T) one. Both functionals provide reasonable binding energies compared to MP2, the ωB97XD being superior to BLYP. The exploratory ab initio molecular dynamics performed on four- and five-body clusters revealed that the hydrogen bonds network and cooperativity in these systems play a crucial role in the proton transfer from H2S·NO+ to H2O and its conversion to thionitrous acid.
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Hanel, Rudolf, Manfred Pöchacker, and Stefan Thurner. "Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1933 (2010): 5583–96. http://dx.doi.org/10.1098/rsta.2010.0267.
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Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems , their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network , and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.
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Jadhav, Pankaj Vilas, Vikrant Kumar Sinha, Saurabh Chugh, et al. "2.09 Å Resolution structure of E. coli HigBA toxin–antitoxin complex reveals an ordered DNA-binding domain and intrinsic dynamics in antitoxin." Biochemical Journal 477, no. 20 (2020): 4001–19. http://dx.doi.org/10.1042/bcj20200363.
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The toxin–antitoxin (TA) systems are small operon systems that are involved in important physiological processes in bacteria such as stress response and persister cell formation. Escherichia coli HigBA complex belongs to the type II TA systems and consists of a protein toxin called HigB and a protein antitoxin called HigA. The toxin HigB is a ribosome-dependent endoribonuclease that cleaves the translating mRNAs at the ribosome A site. The antitoxin HigA directly binds the toxin HigB, rendering the HigBA complex catalytically inactive. The existing biochemical and structural studies had revealed that the HigBA complex forms a heterotetrameric assembly via dimerization of HigA antitoxin. Here, we report a high-resolution crystal structure of E. coli HigBA complex that revealed a well-ordered DNA binding domain in HigA antitoxin. Using SEC-MALS and ITC methods, we have determined the stoichiometry of complex formation between HigBA and a 33 bp DNA and report that HigBA complex as well as HigA homodimer bind to the palindromic DNA sequence with nano molar affinity. Using E. coli growth assays, we have probed the roles of key, putative active site residues in HigB. Spectroscopic methods (CD and NMR) and molecular dynamics simulations study revealed intrinsic dynamic in antitoxin in HigBA complex, which may explain the large conformational changes in HigA homodimer in free and HigBA complexes observed previously. We also report a truncated, heterodimeric form of HigBA complex that revealed possible cleavage sites in HigBA complex, which can have implications for its cellular functions.
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KIRKILIONIS, MARKUS, and LUCA SBANO. "AN AVERAGING PRINCIPLE FOR COMBINED INTERACTION GRAPHS — CONNECTIVITY AND APPLICATIONS TO GENETIC SWITCHES." Advances in Complex Systems 13, no. 03 (2010): 293–326. http://dx.doi.org/10.1142/s0219525910002669.
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Time-continuous dynamical systems defined on graphs are often used to model complex systems with many interacting components in a non-spatial context. In the reverse sense attaching meaningful dynamics to given "interaction diagrams" is a central bottleneck problem in many application areas, especially in cell biology where various such diagrams with different conventions describing molecular regulation are presently in use. In most situations these diagrams can only be interpreted by the use of both discrete and continuous variables during the modelling process, corresponding to both deterministic and stochastic hybrid dynamics. The conventions in genetics are well known, and therefore we use this field for illustration purposes. In [25] and [26] the authors showed that with the help of a multi-scale analysis stochastic systems with both continuous variables and finite state spaces can be approximated by dynamical systems whose leading order time evolution is given by a combination of ordinary differential equations (ODEs) and Markov chains. The leading order term in these dynamical systems is called average dynamics and turns out to be an adequate concept to analyze a class of simplified hybrid systems. Once the dynamics is defined the mutual interaction of both ODEs and Markov chains can be analyzed through the (reverse) introduction of the so-called Interaction Graph, a concept originally invented for time-continuous dynamical systems, see [5]. Here we transfer this graph concept to the average dynamics, which itself is introduced as a heuristic tool to construct models of reaction or contact networks. The graphical concepts introduced form the basis for any subsequent study of the qualitative properties of hybrid models in terms of connectivity and (feedback) loop formation.
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Rose-Sperling, Dania, Mai Anh Tran, Luca M. Lauth, Benedikt Goretzki, and Ute A. Hellmich. "19F NMR as a versatile tool to study membrane protein structure and dynamics." Biological Chemistry 400, no. 10 (2019): 1277–88. http://dx.doi.org/10.1515/hsz-2018-0473.
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AbstractTo elucidate the structures and dynamics of membrane proteins, highly advanced biophysical methods have been developed that often require significant resources, both for sample preparation and experimental analyses. For very complex systems, such as membrane transporters, ion channels or G-protein coupled receptors (GPCRs), the incorporation of a single reporter at a select site can significantly simplify the observables and the measurement/analysis requirements. Here we present examples using19F nuclear magnetic resonance (NMR) spectroscopy as a powerful, yet relatively straightforward tool to study (membrane) protein structure, dynamics and ligand interactions. We summarize methods to incorporate19F labels into proteins and discuss the type of information that can be readily obtained for membrane proteins already from relatively simple NMR spectra with a focus on GPCRs as the membrane protein family most extensively studied by this technique. In the future, these approaches may be of particular interest also for many proteins that undergo complex functional dynamics and/or contain unstructured regions and thus are not amenable to X-ray crystallography or cryo electron microscopy (cryoEM) studies.
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Malinowski, Adrian, and Maciej Śmiechowski. "Solvent Exchange around Aqueous Zn(II) from Ab Initio Molecular Dynamics Simulations." Liquids 2, no. 3 (2022): 243–57. http://dx.doi.org/10.3390/liquids2030015.
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Hydrated zinc(II) cations, due to their importance in biological systems, are the subject of ongoing research concerning their hydration shell structure and dynamics. Here, ab initio molecular dynamics (AIMD) simulations are used to study solvent exchange events around aqueous Zn2+, for which observation in detail is possible owing to the considerable length of the generated trajectory. While the hexacoordinated Zn(H2O)62+ is the dominant form of Zn(II) in an aqueous solution, there is a non-negligible contribution of the pentacoordinated Zn(H2O)52+ complex which presence is linked to the dissociative solvent exchange events around Zn2+. The pentacoordinated Zn(II) has a much tighter hydration sphere and is characterized by a trigonal bipyramidal structure, in contrast to the usual octahedral symmetry of the hexacoordinated complex. In total, two full exchange events are registered in the analyzed trajectory. AIMD simulations on an adequate length scale thus provide a direct way of studying such solvent exchange events around ions in molecular detail.
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Feskov, Sergey. "The Green’s Function Method for Evaluating the Transient Spectra of Non-Equilibrium Molecular Systems." Mathematical Physics and Computer Simulation, no. 4 (December 2022): 95–106. http://dx.doi.org/10.15688/mpcm.jvolsu.2022.4.8.
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Interest in ultrafast photochemical processes is due to their role in wildlife and the possibility of using them in solar energy conversion devices. Significant part of experimental research in this area is carried out using different spectroscopic techniques, for example, based on recording the dynamic response of the system to optical excitation by a short laser pulse. This method is basic for photochemistry and is used for studying both small inorganic molecules in liquids or mixtures, and complex biological objects, such as photosynthetic reaction centers of bacteria and plants. Time-resolved luminescence/absorption spectra contain information about the processes of population of the electronic and vibrational states of the system, and therefore make it possible to study the mechanisms of photoreactions. At the same time, the question of the correct interpretation of experimental data in the case of ultrafast reactions at picosecond timescales is still relevant. The traditional approach is based on the decomposition of transient spectra into the dynamic components, associated with different electronic states. This state-associated analysis turns out to be much less accurate in ultrafast nonequilibrium reactions. The spectral dynamics of the system in this case depends not only on chemical transformations (that is, changes in state populations), but also on the evolution of the spectral response for each of the states. Particularly, relaxation of high-frequency intramolecular vibrations in ultrafast reactions was shown to cause not only a shift in the luminescence spectrum, but also significant changes in spectral profiles themselves. An assumption about the invariable shape of individual spectral components cannot be justified here. Relevant analysis of spectral dynamics in such systems thus requires taking into account the nonequilibrium state of intramolecular degrees of freedom and the environment. Development of theoretical models of nonequilibrium processes, as well as software tools for numerical simulation of spectral dynamics and the fitting techniques for experimental results data, allows us to improve the relevance of the analysis. This study is devoted to the development of a mathematical model of spectral dynamics of macromolecular systems, in which photoexcitation triggers a series of ultrafast electron transfer reactions involving several redox centers. The main attention is paid to accounting for nonequilibrium states of the medium and intramolecular degrees of freedom formed both at the stage of photoexcitation and in the course of a multistage reaction. This allows us to expand the range of phenomena under study and apply the model for interpretation of experimental data on multistage charge transfer in biological objects. The model is based on the semiclassical theory of multistage electron transfer in a multicomponent non-Debye solvent, as well as the Green’s function method for the classical (polarization) and quantum (intramolecular) coordinates of the system.
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Granick, Steve. "Molecular Tribology." MRS Bulletin 16, no. 10 (1991): 33–35. http://dx.doi.org/10.1557/s0883769400055809.
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Molecular tribology—the study of tribology at atomic and molecular scales—constitutes a new frontier of tribology research. In a major surge of activity, experimental methods have recently been developed to measure dynamic interfacial forces in shear. Building partly on earlier, somewhat neglected friction studies, striking new findings have been obtained. The new methods include the surface forces apparatus for measuring adhesion and static interfacial forces as a function of surface separation, new molecular tribometers for measuring friction in shear, atomic force microscopy, use of UHV tribometers, and the quartz-crystal microbalance. Theoretical calculations and molecular dynamics simulations are also emerging for friction in dry and lubricated sliding.On the scientific side, appreciation is growing that scientific understanding of these systems, so complex and so far from equilibrium, is possible. Tribology is becoming recognized as an area with many exciting and useful surface science opportunities.The engineering significance is that while tribology design and tribology-based applications are rooted in our economic life, too often the technologies and formulations are empirically derived. One tends to take friction, wear, and tear for granted. A scientific understanding is needed so that better design can emerge by rational extension.This review seeks to bring out the excitement of new developments. The reader is referred to the original literature for full accounts.
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Alameddine, Abdallah K., Frederick Conlin, and Brian Binnall. "An Introduction to the Mathematical Modeling in the Study of Cancer Systems Biology." Cancer Informatics 17 (January 2018): 117693511879975. http://dx.doi.org/10.1177/1176935118799754.
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Background: Frequently occurring in cancer are the aberrant alterations of regulatory onco-metabolites, various oncogenes/epigenetic stochasticity, and suppressor genes, as well as the deficient mismatch repair mechanism, chronic inflammation, or those deviations belonging to the other cancer characteristics. How these aberrations that evolve overtime determine the global phenotype of malignant tumors remains to be completely understood. Dynamic analysis may have potential to reveal the mechanism of carcinogenesis and can offer new therapeutic intervention. Aims: We introduce simplified mathematical tools to model serial quantitative data of cancer biomarkers. We also highlight an introductory overview of mathematical tools and models as they apply from the viewpoint of known cancer features. Methods: Mathematical modeling of potentially actionable genomic products and how they proceed overtime during tumorigenesis are explored. This report is intended to be instinctive without being overly technical. Results: To date, many mathematical models of the common features of cancer have been developed. However, the dynamic of integrated heterogeneous processes and their cross talks related to carcinogenesis remains to be resolved. Conclusions: In cancer research, outlining mathematical modeling of experimentally obtained data snapshots of molecular species may provide insights into a better understanding of the multiple biochemical circuits. Recent discoveries have provided support for the existence of complex cancer progression in dynamics that span from a simple 1-dimensional deterministic system to a stochastic (ie, probabilistic) or to an oscillatory and multistable networks. Further research in mathematical modeling of cancer progression, based on the evolving molecular kinetics (time series), could inform a specific and a predictive behavior about the global systems biology of vulnerable tumor cells in their earlier stages of oncogenesis. On this footing, new preventive measures and anticancer therapy could then be constructed.
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Prawesh, Shankar, and Balaji Padmanabhan. "A complex systems perspective of news recommender systems: Guiding emergent outcomes with feedback models." PLOS ONE 16, no. 1 (2021): e0245096. http://dx.doi.org/10.1371/journal.pone.0245096.
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Algorithms are increasingly making decisions regarding what news articles should be shown to online users. In recent times, unhealthy outcomes from these systems have been highlighted including their vulnerability to amplifying small differences and offering less choice to readers. In this paper we present and study a new class of feedback models that exhibit a variety of self-organizing behaviors. In addition to showing important emergent properties, our model generalizes the popular “top-N news recommender systems” in a manner that provides media managers a mechanism to guide the emergent outcomes to mitigate potentially unhealthy outcomes driven by the self-organizing dynamics. We use complex adaptive systems framework to model the popularity evolution of news articles. In particular, we use agent-based simulation to model a reader’s behavior at the microscopic level and study the impact of various simulation hyperparameters on overall emergent phenomena. This simulation exercise enables us to show how the feedback model can be used as an alternative recommender to conventional top-N systems. Finally, we present a design framework for multi-objective evolutionary optimization that enables recommendation systems to co-evolve with the changing online news readership landscape.
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Yletyinen, Johanna, Örjan Bodin, Benjamin Weigel, Marie C. Nordström, Erik Bonsdorff, and Thorsten Blenckner. "Regime shifts in marine communities: a complex systems perspective on food web dynamics." Proceedings of the Royal Society B: Biological Sciences 283, no. 1825 (2016): 20152569. http://dx.doi.org/10.1098/rspb.2015.2569.
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Species composition and habitats are changing at unprecedented rates in the world's oceans, potentially causing entire food webs to shift to structurally and functionally different regimes. Despite the severity of these regime shifts, elucidating the precise nature of their underlying processes has remained difficult. We address this challenge with a new analytic approach to detect and assess the relative strength of different driving processes in food webs. Our study draws on complexity theory, and integrates the network-centric exponential random graph modelling (ERGM) framework developed within the social sciences with community ecology. In contrast to previous research, this approach makes clear assumptions of direction of causality and accommodates a dynamic perspective on the emergence of food webs. We apply our approach to analysing food webs of the Baltic Sea before and after a previously reported regime shift. Our results show that the dominant food web processes have remained largely the same, although we detect changes in their magnitudes. The results indicate that the reported regime shift may not be a system-wide shift, but instead involve a limited number of species. Our study emphasizes the importance of community-wide analysis on marine regime shifts and introduces a novel approach to examine food webs.
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Marquet, Franck, Filip Stojceski, Gianvito Grasso, Viorica Patrulea, Andrea Danani, and Gerrit Borchard. "Characterization of the Interaction of Polymeric Micelles with siRNA: A Combined Experimental and Molecular Dynamics Study." Polymers 14, no. 20 (2022): 4409. http://dx.doi.org/10.3390/polym14204409.
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The simulation of large molecular systems remains a daunting challenge, which justifies the exploration of novel methodologies to keep computers as an ideal companion tool for everyday laboratory work. Whole micelles, bigger than 20 nm in size, formed by the self-assembly of hundreds of copolymers containing more than 50 repeating units, have until now rarely been simulated, due to a lack of computational power. Therefore, a flexible amphiphilic triblock copolymer (mPEG45-α-PLL10-PLA25) containing a total of 80 repeating units, has been emulated and synthesized to embody compactified nanoconstructs of over 900 assembled copolymers, sized between 80 and 100 nm, for siRNA complexing purposes. In this study, the tailored triblock copolymers containing a controlled number of amino groups, were used as a support model to address the binding behavior of STAT3-siRNA, in the formation of micelleplexes. Since increasingly complex drug delivery systems require an ever more optimized physicochemical characterization, a converging description has been implemented by a combination of experimentation and computational simulations. The computational data were advantageous in allowing for the assumption of an optimal N/P ratio favoring both conformational rigidifications of STAT3-siRNA with low competitive phenomena at the binding sites of the micellar carriers. These calculations were consistent with the experimental data showing that an N/P ratio of 1.5 resulted in a sufficient amount of complexed STAT3-siRNA with an electrical potential at the slipping plane of the nanopharmaceuticals, close to the charge neutralization.
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Naudi-Fabra, Samuel, Martin Blackledge, and Sigrid Milles. "Synergies of Single Molecule Fluorescence and NMR for the Study of Intrinsically Disordered Proteins." Biomolecules 12, no. 1 (2021): 27. http://dx.doi.org/10.3390/biom12010027.
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Single molecule fluorescence and nuclear magnetic resonance spectroscopy (NMR) are two very powerful techniques for the analysis of intrinsically disordered proteins (IDPs). Both techniques have individually made major contributions to deciphering the complex properties of IDPs and their interactions, and it has become evident that they can provide very complementary views on the distance-dynamics relationships of IDP systems. We now review the first approaches using both NMR and single molecule fluorescence to decipher the molecular properties of IDPs and their interactions. We shed light on how these two techniques were employed synergistically for multidomain proteins harboring intrinsically disordered linkers, for veritable IDPs, but also for liquid–liquid phase separated systems. Additionally, we provide insights into the first approaches to use single molecule Förster resonance energy transfer (FRET) and NMR for the description of multiconformational models of IDPs.
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Karch, Rudolf, Claudia Stocsits, Nevena Ilieva, and Wolfgang Schreiner. "Intramolecular Domain Movements of Free and Bound pMHC and TCR Proteins: A Molecular Dynamics Simulation Study." Cells 8, no. 7 (2019): 720. http://dx.doi.org/10.3390/cells8070720.
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The interaction of antigenic peptides (p) and major histocompatibility complexes (pMHC) with T-cell receptors (TCR) is one of the most important steps during the immune response. Here we present a molecular dynamics simulation study of bound and unbound TCR and pMHC proteins of the LC13-HLA-B*44:05-pEEYLQAFTY complex to monitor differences in relative orientations and movements of domains between bound and unbound states of TCR-pMHC. We generated local coordinate systems for MHC α1- and MHC α2-helices and the variable T-cell receptor regions TCR Vα and TCR Vβ and monitored changes in the distances and mutual orientations of these domains. In comparison to unbound states, we found decreased inter-domain movements in the simulations of bound states. Moreover, increased conformational flexibility was observed for the MHC α2-helix, the peptide, and for the complementary determining regions of the TCR in TCR-unbound states as compared to TCR-bound states.
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Tolstova, Anna P., Alexander A. Makarov та Alexei A. Adzhubei. "Zinc Induced Aβ16 Aggregation Modeled by Molecular Dynamics". International Journal of Molecular Sciences 22, № 22 (2021): 12161. http://dx.doi.org/10.3390/ijms222212161.
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It is widely accepted that the addition of zinc leads to the formation of neurotoxic nonfibrillar aggregates of beta-amyloid peptides Aβ40 and Aβ42 and at the same time destabilizes amyloid fibrils. However, the mechanism of the effect of zinc on beta-amyloid is not fully understood. In this study, a fast zinc-induced aggregation of Aβ16 (as compared to a system without zinc) via the formation of Aβ16 dimers with one zinc ion coordinated in the metal-binding site 11EVHH14, followed by their polymerization, has been studied by molecular dynamics. The best aggregation was shown by the system composed of Aβ16 dimers bound by one zinc ion, with no additional zinc in solution. The presence of Aβ16 dimers was a major condition, sufficient for fast aggregation into larger complexes. It has been shown that the addition of zinc to a system with already formed dimers does not substantially affect the characteristics and rate of aggregation. At the same time, an excessive concentration of zinc at the early stages of the formation of conglomerates can negatively affect aggregation, since in systems where zinc ions occupied the 11EVHH14 coordination center and the His6 residue of every Aβ16 monomer, the aggregation proceeded more slowly and the resulting complexes were not as large as in the zinc-free Aβ system. Thus, this study has shown that the formation of Aβ16 dimers bound through zinc ions at the 11EVHH14 sites of the peptides plays an important role in the formation of neurotoxic non-fibrillar aggregates of beta-amyloid peptide Aβ16. The best energetically favorable structure has been obtained for the complex of two Aβ16 dimers with two zinc ions.
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Paciolla, Mariarita, Daniel J. Arismendi-Arrieta, and Angel J. Moreno. "Coarsening Kinetics of Complex Macromolecular Architectures in Bad Solvent." Polymers 12, no. 3 (2020): 531. http://dx.doi.org/10.3390/polym12030531.
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This study reports a general scenario for the out-of-equilibrium features of collapsing polymeric architectures. We use molecular dynamics simulations to characterize the coarsening kinetics, in bad solvent, for several macromolecular systems with an increasing degree of structural complexity. In particular, we focus on: flexible and semiflexible polymer chains, star polymers with 3 and 12 arms, and microgels with both ordered and disordered networks. Starting from a powerful analogy with critical phenomena, we construct a density field representation that removes fast fluctuations and provides a consistent characterization of the domain growth. Our results indicate that the coarsening kinetics presents a scaling behaviour that is independent of the solvent quality parameter, in analogy to the time–temperature superposition principle. Interestingly, the domain growth in time follows a power-law behaviour that is approximately independent of the architecture for all the flexible systems; while it is steeper for the semiflexible chains. Nevertheless, the fractal nature of the dense regions emerging during the collapse exhibits the same scaling behaviour for all the macromolecules. This suggests that the faster growing length scale in the semiflexible chains originates just from a faster mass diffusion along the chain contour, induced by the local stiffness. The decay of the dynamic correlations displays scaling behavior with the growing length scale of the system, which is a characteristic signature in coarsening phenomena.
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Contreras-Riquelme, Sebastián, Jose-Antonio Garate, Tomas Perez-Acle, and Alberto J. M. Martin. "RIP-MD: a tool to study residue interaction networks in protein molecular dynamics." PeerJ 6 (December 7, 2018): e5998. http://dx.doi.org/10.7717/peerj.5998.
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Protein structure is not static; residues undergo conformational rearrangements and, in doing so, create, stabilize or break non-covalent interactions. Molecular dynamics (MD) is a technique used to simulate these movements with atomic resolution. However, given the data-intensive nature of the technique, gathering relevant information from MD simulations is a complex and time consuming process requiring several computational tools to perform these analyses. Among different approaches, the study of residue interaction networks (RINs) has proven to facilitate the study of protein structures. In a RIN, nodes represent amino-acid residues and the connections between them depict non-covalent interactions. Here, we describe residue interaction networks in protein molecular dynamics (RIP-MD), a visual molecular dynamics (VMD) plugin to facilitate the study of RINs using trajectories obtained from MD simulations of proteins. Our software generates RINs from MD trajectory files. The non-covalent interactions defined by RIP-MD include H-bonds, salt bridges, VdWs, cation-π, π–π, Arginine–Arginine, and Coulomb interactions. In addition, RIP-MD also computes interactions based on distances between Cαs and disulfide bridges. The results of the analysis are shown in an user friendly interface. Moreover, the user can take advantage of the VMD visualization capacities, whereby through some effortless steps, it is possible to select and visualize interactions described for a single, several or all residues in a MD trajectory. Network and descriptive table files are also generated, allowing their further study in other specialized platforms. Our method was written in python in a parallelized fashion. This characteristic allows the analysis of large systems impossible to handle otherwise. RIP-MD is available at http://www.dlab.cl/ripmd.
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Kolesnikov, Andrey V. "Space and Molecular Human in the Process of Social Systems Digital Transformation in Belarus and Russia." AEROSPACE SPHERE JOURNAL, no. 2 (June 26, 2021): 84–97. http://dx.doi.org/10.30981/2587-7992-2020-107-2-84-97.
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To develop a strategy for building the Union State of Russia and Belarus’ better future, it is necessary to understand the mechanisms and identify the main causes that govern the dynamics of this complex and specifi c social system. As the main factor determining the social dynamics of a given civilization cluster, we consider the competition of two basic sociotypes. They are conditionally designated as a molecular man and a space man. A molecular person is a consumer whose social behavior is based on the power of the selfi sh gene and consumer society’s ideals. A space person is passionate, driven by the creative imperative of cognition and synthesis of culture. In our opinion, it is this fundamental confl ict that forms the social dynamics of the civilization cluster of the Union State. The scenario of its future development will depend on the resolution of this confl ict. In order to better understand this process, we have developed a cellular-automate computer model of competition between the two sociotypes in the framework of a unifi ed social system. This computer model can be considered as a simplifi ed cognitive proto-construct of the social system dynamics. By examining it, one can transfer the properties and features of its behavior to an unknown object under study - a society.
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Banerjee, Sourav, Zoltan Jurek, Malik Muhammad Abdullah, and Robin Santra. "Chemical effects on the dynamics of organic molecules irradiated with high intensity x rays." Structural Dynamics 9, no. 5 (2022): 054101. http://dx.doi.org/10.1063/4.0000166.
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The interaction of a high intensity x-ray pulse with matter causes ionization of the constituent atoms through various atomic processes, and the system eventually goes through a complex structural dynamics. Understanding this whole process is important from the perspective of structure determination of molecules using single particle imaging. XMDYN, which is a classical molecular dynamics-Monte Carlo based hybrid approach, has been successful in simulating the dynamical evolution of various systems under intense irradiation over the past years. The present study aims for extending the XMDYN toolkit to treat chemical bonds using the reactive force field. In order to study its impact, a highly intense x-ray pulse was made to interact with the simplest amino acid, glycine. Different model variants were used to highlight the consequences of charge rearrangement and chemical bonds on the time evolution. The charge-rearrangement-enhanced x-ray ionization of molecules effect is also discussed to address the capability of a classical MD based approach, i.e., XMDYN, to capture such a molecular phenomenon.
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Gross, Thilo, Korinna T. Allhoff, Bernd Blasius, et al. "Modern models of trophic meta-communities." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1814 (2020): 20190455. http://dx.doi.org/10.1098/rstb.2019.0455.
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Dispersal and foodweb dynamics have long been studied in separate models. However, over the past decades, it has become abundantly clear that there are intricate interactions between local dynamics and spatial patterns. Trophic meta-communities, i.e. meta-foodwebs, are very complex systems that exhibit complex and often counterintuitive dynamics. Over the past decade, a broad range of modelling approaches have been used to study these systems. In this paper, we review these approaches and the insights that they have revealed. We focus particularly on recent papers that study trophic interactions in spatially extensive settings and highlight the common themes that emerged in different models. There is overwhelming evidence that dispersal (and particularly intermediate levels of dispersal) benefits the maintenance of biodiversity in several different ways. Moreover, some insights have been gained into the effect of different habitat topologies, but these results also show that the exact relationships are much more complex than previously thought, highlighting the need for further research in this area. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.
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Ischenko, A. A., Y. I. Tarasov, and L. Schäfer. "STRUCTURAL DYNAMICS OF FREE MOLECULES AND CONDENSED MATTER. Part I. THEORY AND EXPERIMENTAL TECHNIQUE." Fine Chemical Technologies 12, no. 2 (2017): 5–33. http://dx.doi.org/10.32362/2410-6593-2017-12-2-5-33.
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To understand the dynamic features of molecular systems with a complex landscape of potential energy surfaces, it is necessary to study them in the associated 4D space-time continuum. The introduction of time in the diffraction methods and the development of coherent principles of the research process opened up new approaches for the study of the dynamics of wave packets, intermediates and transient states of the chemical reactions, short-lived compounds in the gaseous and condensed media. Time-resolved electron diffraction, the new method for the structural dynamic studies of free molecules, clusters and condensed matter, differs from the traditional method of electron diffraction both in the experimental part and in the theoretical approaches used in the interpretation of diffraction data. Here there is particularly pronounced the need of a corresponding theoretical basis for the processing of the electron diffraction data and the results of spectral investigations of the coherent dynamics in the field of intense ultrashort laser radiation. Such unified and integrated approach can be formulated using the adiabatic potential energy surfaces of the ground and excited states of the systems under study. The combination of state-of-the-art optical techniques and electron diffraction methods based on different physical phenomena, but complementing each other, opens up new possibilities of the structural studies at time sequences of ultrashort duration. It provides the required integration of the triad, "structure - dynamics - functions" in chemistry, biology and materials science.
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RAFIKOV, MARAT, JOSÉ MANOEL BALTHAZAR, and HUBERTUS F. VON BREMEN. "MANAGEMENT OF COMPLEX SYSTEMS: MODELING THE BIOLOGICAL PEST CONTROL." Biophysical Reviews and Letters 03, no. 01n02 (2008): 241–56. http://dx.doi.org/10.1142/s1793048008000721.
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The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction.
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Li, Conghui, Xiaolu Han, Xiaoxuan Hong, et al. "Study on the Complexation and Release Mechanism of Methylphenidate Hydrochloride Ion Exchange Resin Complex." Polymers 13, no. 24 (2021): 4394. http://dx.doi.org/10.3390/polym13244394.
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Since the advent of ion exchange resin, it has been widely used in many fields, including drug delivery systems. The drug binds to the resin through an exchange reaction to form a drug–resin complex, which can gradually release drugs through the exchange of physiological ions in the gastrointestinal tract, to realize functions such as taste masking and regulating release. In this study, the complexes of methylphenidate hydrochloride and Amberlite IRP69 were prepared and evaluated to explore the mechanism of complexation, influencing factors and release mechanism at a molecular level. Firstly, with the properties of the selected complexes, molecular dynamics simulation was innovatively used to find that the intermolecular interaction between drug molecules and ion exchange resin molecules is mainly caused by the stacking effect of π and salt bridges. Secondly, with the drug loading status as an indicator, the factors affecting the compounding process of the drug and resin were explored. Finally, the release mechanism of the drug–resin complex was studied by mathematical model fitting. In summary, a variety of methods were used to study the mechanism of complexation and release between drug and resin, providing a theoretical basis for promoting the marketing of ion−exchange resin−mediated oral preparations.
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Poghosyan, Armen, Hrachya Astsatryan, Wahi Narsisian, and Yevgeni Mamasakhlisov. "On the Performance and Energy Consumption of Molecular Dynamics Applications for Heterogeneous CPU-GPU Platforms Based on Gromacs." Cybernetics and Information Technologies 17, no. 5 (2017): 68–80. http://dx.doi.org/10.1515/cait-2017-0056.
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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.
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Liu, Gang, and Yi Ping Yao. "Large Scale Molecular Dynamics Simulation of Femtosecond Laser Ablation of Silicon Using Sensing-VISICOM." Advanced Materials Research 418-420 (December 2011): 1330–37. http://dx.doi.org/10.4028/www.scientific.net/amr.418-420.1330.
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Silicon is widely used as substrate material for the fabrication of micro-electro and micromechanical components. Since silicon is very brittle, how to cut it into complex shapes remains a hot topic. Thanks to the small spot diameter, laser cutting is a promising alternative. However, during laser cutting, different kinds of defects can be generated depending on the beam-material interaction phenomena (ablation, melting, etc). Molecular Dynamics simulation is an effective way to study the beam-material interaction phenomena. Lots of work has been done to develop MD models of laser ablation of silicon. However, due to lack of support from high performance parallel simulation platform, the scale of the molecular systems is limited. This paper presents a component-based parallel simulation platform Sensing-VISICOM, for large scale molecular dynamics simulation. To test its runtime performance, a molecular system of femtosecond laser ablation of silicon is designed and implemented under Sensing-VISICOM. The results of the simulation show the platform can scales well to millions of atoms.
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Bruner, Barry D., Zdeněk Mašín, Matteo Negro, et al. "Multidimensional high harmonic spectroscopy of polyatomic molecules: detecting sub-cycle laser-driven hole dynamics upon ionization in strong mid-IR laser fields." Faraday Discussions 194 (2016): 369–405. http://dx.doi.org/10.1039/c6fd00130k.
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High harmonic generation (HHG) spectroscopy has opened up a new frontier in ultrafast science, where electronic dynamics can be measured on an attosecond time scale. The strong laser field that triggers the high harmonic response also opens multiple quantum pathways for multielectron dynamics in molecules, resulting in a complex process of multielectron rearrangement during ionization. Using combined experimental and theoretical approaches, we show how multi-dimensional HHG spectroscopy can be used to detect and follow electronic dynamics of core rearrangement on sub-laser cycle time scales. We detect the signatures of laser-driven hole dynamics upon ionization and reconstruct the relative phases and amplitudes for relevant ionization channels in a CO<sub>2</sub> molecule on a sub-cycle time scale. Reconstruction of channel-resolved complex ionization amplitudes on attosecond time scales has been a long-standing goal of high harmonic spectroscopy. Our study brings us one step closer to fulfilling this initial promise and developing robust schemes for sub-femtosecond imaging of multielectron rearrangement in complex molecular systems.
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Escalona, Yerko, Drazen Petrov, Edgar Galicia-Andrés, and Chris Oostenbrink. "Exploring the Macroscopic Properties of Humic Substances Using Modeling and Molecular Simulations." Agronomy 13, no. 4 (2023): 1044. http://dx.doi.org/10.3390/agronomy13041044.
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Soil organic matter (SOM) is composed of a complex and heterogeneous mixture of organic compounds, which poses a challenge in understanding it on an atomistic level. Based on the progress of molecular dynamics simulations and our efforts to create molecular systems that resemble SOM, in this work, we expanded our knowledge of SOM through the use of humic substances (HSs). Specifically, we studied the standardized samples of HS of the International Humic Substances Society (IHSS). This society provided the elemental and organic composition used as input parameters for our Vienna Soil Organic Matter Modeler 2 (VSOMM2). We modeled and simulated different HS samples from various sources, including soil, peat, leonardite, and blackwater river. In order to compare between different HS, we reduced the organic composition information to two principal components, which are associated principally with the amount of carboxyl and aromatic groups in the HS, denominated as PCacid and PCarom, respectively. We performed a plethora of analyses to characterize the structure and dynamics of the systems, including the total potential energy, density, diffusion, preferential solvation, hydrogen bonds, and salt bridges. In general terms, at the water content value of 0.2, we observed that most properties depend on the carboxyl group protonation state. The Coulombic interactions from this ionic specie and the interaction with cations determine the overall behavior of the studied systems. Furthermore, the type of cations and the pH influence those properties. This study exemplifies the importance of molecular dynamics to explain macroscopic properties from the structure and dynamics of the molecules modeled, such as the interaction network, i.e., hydrogen bonds or salt bridges of molecules presented in the system and their mobility.
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Zhang, Shitao, Shuai Lv, Xueqi Fu, Lu Han, Weiwei Han, and Wannan Li. "Molecular Dynamics Simulations Study of the Interactions between Human Dipeptidyl-Peptidase III and Two Substrates." Molecules 26, no. 21 (2021): 6492. http://dx.doi.org/10.3390/molecules26216492.
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Human dipeptidyl-peptidase III (hDPP III) is capable of specifically cleaving dipeptides from the N-terminal of small peptides with biological activity such as angiotensin II (Ang II, DRVYIHPF), and participates in blood pressure regulation, pain modulation, and the development of cancers in human biological activities. In this study, 500 ns molecular dynamics simulations were performed on free-hDPP III (PDB code: 5E33), hDPP III-Ang II (PDB code: 5E2Q), and hDPP III-IVYPW (PDB code: 5E3C) to explore how these two peptides affect the catalytic efficiency of enzymes in terms of the binding mode and the conformational changes. Our results indicate that in the case of the hDPP III-Ang II complex, subsite S1 became small and hydrophobic, which might be propitious for the nucleophile to attack the substrate. The structures of the most stable conformations of the three systems revealed that Arg421-Lys423 could form an α-helix with the presence of Ang II, but only part of the α-helix was produced in hDPP III-IVYPW. As the hinge structure in hDPP III, the conformational changes that took place in the Arg421-Lys423 residue could lead to the changes in the shape and space of the catalytic subsites, which might allow water to function as a nucleophile to attack the substrate. Our results may provide new clues to enable the design of new inhibitors for hDPP III in the future.
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Sefidkar, Narmin, Samira Fathizadeh, Fatemeh Nemati та Constantinos Simserides. "Energy Transport along α-Helix Protein Chains: External Drives and Multifractal Analysis". Materials 15, № 8 (2022): 2779. http://dx.doi.org/10.3390/ma15082779.
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Energy transport within biological systems is critical for biological functions in living cells and for technological applications in molecular motors. Biological systems have very complex dynamics supporting a large number of biochemical and biophysical processes. In the current work, we study the energy transport along protein chains. We examine the influence of different factors such as temperature, salt concentration, and external mechanical drive on the energy flux through protein chains. We obtain that energy fluctuations around the average value for short chains are greater than for longer chains. In addition, the external mechanical load is the most effective agent on bioenergy transport along the studied protein systems. Our results can help design a functional nano-scaled molecular motor based on energy transport along protein chains.