Journal articles: 'Interactive molecular simulations'

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Rapaport, D. C., and Harvey Gould. "An introduction to interactive molecular-dynamics simulations." Computers in Physics 11, no. 4 (1997): 337. http://dx.doi.org/10.1063/1.168612.

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Lanrezac, André, Benoist Laurent, Hubert Santuz, Nicolas Férey, and Marc Baaden. "Fast and Interactive Positioning of Proteins within Membranes." Algorithms 15, no. 11 (November 7, 2022): 415. http://dx.doi.org/10.3390/a15110415.

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(1) Background: We developed an algorithm to perform interactive molecular simulations (IMS) of protein alignment in membranes, allowing on-the-fly monitoring and manipulation of such molecular systems at various scales. (2) Methods: UnityMol, an advanced molecular visualization software; MDDriver, a socket for data communication; and BioSpring, a Spring network simulation engine, were extended to perform IMS. These components are designed to easily communicate with each other, adapt to other molecular simulation software, and provide a development framework for adding new interaction models to simulate biological phenomena such as protein alignment in the membrane at a fast enough rate for real-time experiments. (3) Results: We describe in detail the integration of an implicit membrane model for Integral Membrane Protein And Lipid Association (IMPALA) into our IMS framework. Our implementation can cover multiple levels of representation, and the degrees of freedom can be tuned to optimize the experience. We explain the validation of this model in an interactive and exhaustive search mode. (4) Conclusions: Protein positioning in model membranes can now be performed interactively in real time.

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Delalande, Olivier, Nicolas Férey, Gilles Grasseau, and Marc Baaden. "Complex molecular assemblies at hand via interactive simulations." Journal of Computational Chemistry 30, no. 15 (November 30, 2009): 2375–87. http://dx.doi.org/10.1002/jcc.21235.

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Lahlali, Abdelouahed, Nadia Chafiq, Mohamed Radid, Kamal Moundy, and Chaibia Srour. "The Effect of Integrating Interactive Simulations on the Development of Students’ Motivation, Engagement, Interaction and School Results." International Journal of Emerging Technologies in Learning (iJET) 18, no. 12 (June 21, 2023): 193–207. http://dx.doi.org/10.3991/ijet.v18i12.39755.

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The concept of chemical bonding and related concepts are essential topics for the fundamental understanding of chemistry courses by secondary school students. Because of the abstraction aspect, students find it difficult to understand this topic. The aim of this study is to improve students' motivation, engagement, interaction and school results by integrating interactive simulations into the teaching-learning process of chemical bonding concepts. The study was conducted in a secondary school in the Kingdom of Morocco, with a sample of 56 students in the qualifying secondary education cycle. The sample was divided into an experimental group and a control group. The experimental group is taught using more molecular models PhET simulations, while the control group follows the traditional teaching method. Using a quantitative research method with a pre- and post-test design, and an observation grid measuring students' motivation, engagement and interaction before and after the integration of interactive simulations. The data were then analysed using the IBM SPSS 25 program. The results showed that students in the experimental group working with PhET interactive simulations scored significantly higher (p<.01) than students in the control group after the post-test, thus the study showed that there is a positive correlation between students' motivation, engagement, and interaction and their school results during instruction using PhET computer simulations combined with molecular models. Therefore, the results of this study suggest that the teaching-learning of chemistry topics related to chemical bonding can be enhanced using PhET interactive simulations combined with molecular models. This research highlights the usefulness of integrating interactive simulations into the chemistry teaching-learning process.

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Dunn, Justin, and Umesh Ramnarain. "The Effect of Simulation-Supported Inquiry on South African Natural Sciences Learners’ Understanding of Atomic and Molecular Structures." Education Sciences 10, no. 10 (October 14, 2020): 280. http://dx.doi.org/10.3390/educsci10100280.

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This study investigated the effect of interactive computer simulation-supported inquiry on South African grade 8 learners’ comprehension of atoms and molecular structures. Two sample groups of 34 learners per sample group were used, one acting as a control group who were exposed to a teacher-directed pedagogy while the experimental group used simulations in inquiry-based learning as an intervention to enhance their understanding of atomic and molecular structures. Data were collected by means of conceptual tests, a questionnaire survey, and individual interviews. A statistical analysis of quantitative data gleaned from the post-test showed that the learners in the experimental group performed better than the control group learners. This reflects that the interactive simulations using in an inquiry activity impacted more favorably on the conceptual understanding of learners compared to a teacher-directed approach. The results of the questionnaire survey indicated that learners in the experimental class had a positive experience of using the simulations. They recognized that the simulations enhanced their visualization of abstract concepts, and they reflected on their efficacy in manipulating the simulation.

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Goret, G., B. Aoun, and E. Pellegrini. "MDANSE: An Interactive Analysis Environment for Molecular Dynamics Simulations." Journal of Chemical Information and Modeling 57, no. 1 (January 6, 2017): 1–5. http://dx.doi.org/10.1021/acs.jcim.6b00571.

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White, Brian T., and Ethan D. Bolker. "Interactive computer simulations of genetics, biochemistry, and molecular biology." Biochemistry and Molecular Biology Education 36, no. 1 (January 2008): 77–84. http://dx.doi.org/10.1002/bmb.20152.

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Sego, T. J., James P. Sluka, Herbert M. Sauro, and James A. Glazier. "Tissue Forge: Interactive biological and biophysics simulation environment." PLOS Computational Biology 19, no. 10 (October 23, 2023): e1010768. http://dx.doi.org/10.1371/journal.pcbi.1010768.

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Tissue Forge is an open-source interactive environment for particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create, simulate and explore models and virtual experiments based on soft condensed matter physics at multiple scales, from the molecular to the multicellular, using a simple, consistent interface. While Tissue Forge is designed to simplify solving problems in complex subcellular, cellular and tissue biophysics, it supports applications ranging from classic molecular dynamics to agent-based multicellular systems with dynamic populations. Tissue Forge users can build and interact with models and simulations in real-time and change simulation details during execution, or execute simulations off-screen and/or remotely in high-performance computing environments. Tissue Forge provides a growing library of built-in model components along with support for user-specified models during the development and application of custom, agent-based models. Tissue Forge includes an extensive Python API for model and simulation specification via Python scripts, an IPython console and a Jupyter Notebook, as well as C and C++ APIs for integrated applications with other software tools. Tissue Forge supports installations on 64-bit Windows, Linux and MacOS systems and is available for local installation via conda.

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Cruz-neira, C., R. Langley, and P. A. Bash. "Interactive Molecular Modeling with Virtual Reality and Empirical Energy Simulations." SAR and QSAR in Environmental Research 9, no. 1-2 (January 1998): 39–51. http://dx.doi.org/10.1080/10629369808039148.

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McCluskey, Andrew R., James Grant, Adam R. Symington, Tim Snow, James Doutch, Benjamin J. Morgan, Stephen C. Parker, and Karen J. Edler. "An introduction to classical molecular dynamics simulation for experimental scattering users." Journal of Applied Crystallography 52, no. 3 (May 7, 2019): 665–68. http://dx.doi.org/10.1107/s1600576719004333.

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Classical molecular dynamics simulations are a common component of multi-modal analyses of scattering measurements, such as small-angle scattering and diffraction. Users of these experimental techniques often have no formal training in the theory and practice of molecular dynamics simulation, leading to the possibility of these simulations being treated as a `black box' analysis technique. This article describes an open educational resource (OER) designed to introduce classical molecular dynamics to users of scattering methods. This resource is available as a series of interactive web pages, which can be easily accessed by students, and as an open-source software repository, which can be freely copied, modified and redistributed by educators. The topics covered in this OER include classical atomistic modelling, parameterizing interatomic potentials, molecular dynamics simulations, typical sources of error and some of the approaches to using simulations in the analysis of scattering data.

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Glowacki, David R., Michael O'Connor, Gaetano Calabró, James Price, Philip Tew, Thomas Mitchell, Joseph Hyde, David P. Tew, David J. Coughtrie, and Simon McIntosh-Smith. "A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors." Faraday Discuss. 169 (2014): 63–87. http://dx.doi.org/10.1039/c4fd00008k.

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With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human–computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3–4 orders of magnitude.

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Astsatryan, Hrachya, Wahi Narsisian, Eliza Gyulgyulyan, Vardan Baghdasaryan, Armen Poghosyan, Yevgeni Mamasakhlisov, and Peter Wittenburg. "An Integrated Web-based Interactive Data Platform for Molecular Dynamics Simulations." Scalable Computing: Practice and Experience 19, no. 2 (May 10, 2018): 131–38. http://dx.doi.org/10.12694/scpe.v19i2.1337.

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The article aims to introduce an integrated web-based interactive data platform for molecular dynamic simulations using the datasets generated by different life science communities from Armenia. The suggested platform, consisting of data repository and workflow management services, is vital for current and future scientific discoveries in the life science domain. We focus on interactive data visualization workflow service as a key to perform more in-depth analyzes of research data outputs, helping to understand the problems efficiently and to consolidate the data into one collective illustration platform. The functionalities of the integrated data platform is presented as an advanced integrated environment to capture, analyze, process and visualize the scientific data.

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Byška, J., T. Trautner, S. M. Marques, J. Damborský, B. Kozlíková, and M. Waldner. "Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization." Computer Graphics Forum 38, no. 3 (June 2019): 441–53. http://dx.doi.org/10.1111/cgf.13701.

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Whitworth, Karen, Sarah Leupen, Chistopher Rakes, and Mauricio Bustos. "Interactive Computer Simulations as Pedagogical Tools in Biology Labs." CBE—Life Sciences Education 17, no. 3 (September 2018): ar46. http://dx.doi.org/10.1187/cbe.17-09-0208.

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Student learning in biology may be impaired by instructional environments that emphasize technical methodology over analysis. We hypothesized that time gained by experimenting with accurate computer simulations could be used to engage students in analytical, creative learning. The effects of treatments that combined a week of simulated lab instruction with a week of standard lab instruction in different order (E-to-S and S-to-E) were examined using a controlled experimental design with random assignment of lab sections and hierarchical linear modeling analysis to account for possible clustering within sections. Data from a large sample of students ( N = 515) revealed a significant increase (1.59 SD) in posttest scores for both treatment groups over the control. We posit as a plausible explanation the reinforcement of psychomotor learning due to strong engagement of cognitive processes facilitated by the computer simulation. This study supports a wider use of computer simulations as learning tools in laboratory courses.

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Dreher, Matthieu, Jessica Prevoteau-Jonquet, Mikael Trellet, Marc Piuzzi, Marc Baaden, Bruno Raffin, Nicolas Ferey, Sophie Robert, and Sébastien Limet. "ExaViz: a flexible framework to analyse, steer and interact with molecular dynamics simulations." Faraday Discuss. 169 (2014): 119–42. http://dx.doi.org/10.1039/c3fd00142c.

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The amount of data generated by molecular dynamics simulations of large molecular assemblies and the sheer size and complexity of the systems studied call for new ways to analyse, steer and interact with such calculations. Traditionally, the analysis is performed off-line once the huge amount of simulation results have been saved to disks, thereby stressing the supercomputer I/O systems, and making it increasingly difficult to handle post-processing and analysis from the scientist's office. The ExaViz framework is an alternative approach developed to couple the simulation with analysis tools to process the data as close as possible to their source of creation, saving a reduced, more manageable and pre-processed data set to disk. ExaViz supports a large variety of analysis and steering scenarios. Our framework can be used for live sessions (simulations short enough to be fully followed by the user) as well as batch sessions (long-time batch executions). During interactive sessions, at runtime, the user can display plots from analysis, visualise the molecular system and steer the simulation with a haptic device. We also emphasise how a CAVE-like immersive environment could be used to leverage such simulations, offering a large display surface to view and intuitively navigate the molecular system.

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Poppleton, Erik, Roger Romero, Aatmik Mallya, Lorenzo Rovigatti, and Petr Šulc. "OxDNA.org: a public webserver for coarse-grained simulations of DNA and RNA nanostructures." Nucleic Acids Research 49, W1 (May 1, 2021): W491—W498. http://dx.doi.org/10.1093/nar/gkab324.

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Abstract OxDNA and oxRNA are popular coarse-grained models used by the DNA/RNA nanotechnology community to prototype, analyze and rationalize designed DNA and RNA nanostructures. Here, we present oxDNA.org, a graphical web interface for running, visualizing and analyzing oxDNA and oxRNA molecular dynamics simulations on a GPU-enabled high performance computing server. OxDNA.org automatically generates simulation files, including a multi-step relaxation protocol for structures exported in non-physical states from DNA/RNA design tools. Once the simulation is complete, oxDNA.org provides an interactive visualization and analysis interface using the browser-based visualizer oxView to facilitate the understanding of simulation results for a user’s specific structure. This online tool significantly lowers the entry barrier of integrating simulations in the nanostructure design pipeline for users who are not experts in the technical aspects of molecular simulation. The webserver is freely available at oxdna.org.

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Colubri, Andrés, Molly Kemball, Kian Sani, Chloe Boehm, Karen Mutch-Jones, Ben Fry, Todd Brown, and Pardis C. Sabeti. "Preventing Outbreaks through Interactive, Experiential Real-Life Simulations." Cell 182, no. 6 (September 2020): 1366–71. http://dx.doi.org/10.1016/j.cell.2020.08.042.

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ROBLES, MIGUEL, VILLE MUSTONEN, and KIMMO KASKI. "MOLECULAR DYNAMIC STUDY OF A SINGLE DISLOCATION IN A TWO-DIMENSIONAL LENNARD–JONES SYSTEM." International Journal of Modern Physics C 14, no. 04 (May 2003): 407–21. http://dx.doi.org/10.1142/s0129183103004620.

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In this work the motion of a single dislocation in a two-dimensional triangular lattice is studied by using classical Molecular Dynamics method with the Lennard–Jones inter-atomic potential. The dislocation motion is investigated with an interactive simulation program developed to track automatically the movement of lattice defects. Constant strain and constant strain-rate deformations were applied to the system. From constant strain simulations a curve of shear stress versus dislocation velocity is obtained, showing a nonlinear power law relation. An equation of motion for the dislocation is proposed and found to be applicable when the movement of dislocation follows a quasi-static process. Numerical simulations at different strain rates show an elastic-to-plastic transition that modifies the dynamics of the dislocation motion.

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Pandi, Sangavi, Langeswaran Kulanthaivel, Gowtham Kumar Subbaraj, Sangeetha Rajaram, and Senthilkumar Subramanian. "Screening of Potential Breast Cancer Inhibitors through Molecular Docking and Molecular Dynamics Simulation." BioMed Research International 2022 (June 28, 2022): 1–9. http://dx.doi.org/10.1155/2022/3338549.

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Cyclooxygenase-2 (COX-2) is a key enzyme involved in overexpression in several human cancerous diseases including breast cancer. By performing efficient virtual screening in a series of active molecules or compounds from the Maybridge, NCI (National Cancer Institute), and Enamine databases, potential identification of COX-2 inhibitors could lead to new prognostic strategies in the treatment of breast cancer. Based on a 50% structural similitude, compounds were chosen as the inductive model of COX-2 inhibitions from these databases. Selected compounds were filtered and tested with Lipinski’s rule of five followed by absorption, distribution, metabolism, and excretion (ADME) properties. Subsequently, molecular docking was performed to achieve accuracy in screening and also to find an interactive mechanism between hit compounds with their respective binding sites. Simultaneously, molecular simulations of top-scored compounds were selected and coded such as Maybridge_55417, NCI_30552, and Enamine_62410. Chosen compounds were analyzed and interpreted with COX-2 affinity. Results endorsed that hydrophobic affinity and optimum hydrogen bonds were the forces driven in the interactive mechanism of in silico hits compounds with COX-2 and can be used as efficient alternative therapeutic agents targeting deleterious breast cancer. With these in silico findings, compounds identified may prevent the action of the COX-2 enzyme and thereby diminish the incidence of breast cancer.

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Dubois, Marc-André, Xavier Bouju, and Alain Rochefort. "Toward interactive scanning tunneling microscopy simulations of large-scale molecular systems in real time." Journal of Applied Physics 124, no. 4 (July 28, 2018): 044301. http://dx.doi.org/10.1063/1.5037443.

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Marforio, Tainah Dorina, Alessandro Calza, Edoardo Jun Mattioli, Francesco Zerbetto, and Matteo Calvaresi. "Dissecting the Supramolecular Dispersion of Fullerenes by Proteins/Peptides: Amino Acid Ranking and Driving Forces for Binding to C60." International Journal of Molecular Sciences 22, no. 21 (October 26, 2021): 11567. http://dx.doi.org/10.3390/ijms222111567.

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Molecular dynamics simulations were used to quantitatively investigate the interactions between the twenty proteinogenic amino acids and C60. The conserved amino acid backbone gave a constant energetic interaction ~5.4 kcal mol−1, while the contribution to the binding due to the amino acid side chains was found to be up to ~5 kcal mol−1 for tryptophan but lower, to a point where it was slightly destabilizing, for glutamic acid. The effects of the interplay between van der Waals, hydrophobic, and polar solvation interactions on the various aspects of the binding of the amino acids, which were grouped as aromatic, charged, polar and hydrophobic, are discussed. Although π–π interactions were dominant, surfactant-like and hydrophobic effects were also observed. In the molecular dynamics simulations, the interacting residues displayed a tendency to visit configurations (i.e., regions of the Ramachandran plot) that were absent when C60 was not present. The amino acid backbone assumed a “tepee-like” geometrical structure to maximize interactions with the fullerene cage. Well-defined conformations of the most interactive amino acids (Trp, Arg, Met) side chains were identified upon C60 binding.

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Gauthier, Andrea. "Game and Simulation Stimulate Conceptual Change about Molecular Emergence in Different Ways, with Potential Cultural Implications." Education Sciences 14, no. 4 (March 31, 2024): 366. http://dx.doi.org/10.3390/educsci14040366.

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Many undergraduate students hold robust misconceptions about the emergent nature of molecular processes, believing them to be directed rather than random. Interactive simulations might help transform such misconceptions by visualizing stochastic processes in a time-independent medium and enabling students to manipulate the environment to test their naïve hypotheses. Furthermore, game-based learning (GBL) might enhance the effectiveness of such simulations by promoting productive negativity (PN), i.e., learning from failure. In a randomized controlled trial with pre-test, post-test and delayed one-year follow-up, undergraduates (n = 84) engaged with either a GBL or interactive simulation (SIM) environment for 20–45 min and were compared to a baseline group (n = 138). GBL (p = 0.035) and SIM (p = 0.069) resolved more misconceptions than baseline but did not differ from each other (p = 0.992). GBL group also trended toward more positive long-term conceptual change. In-game interactions generated in response to PN were predictive of conceptual change in the GBL group alone, suggesting that PN may only be effective when supported by game design. Participants’ native English-speaking status had a moderating effect, with native-speakers performing well in GBL and poorly in SIM environment, while the opposite was true for non-native-speakers, which, as discussed herein, may be aligned with cultural differences in acceptability of GBL. The GBL intervention generated longer voluntary use (p = 0.005), especially amongst frequent game-players. The results inform how GBL/SIM approaches can implement PN as a mechanism for conceptual change about molecular emergence.

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Yang, Jiantao, and Tairen Sun. "Finite-Time Interactive Control of Robots with Multiple Interaction Modes." Sensors 22, no. 10 (May 11, 2022): 3668. http://dx.doi.org/10.3390/s22103668.

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This paper proposes a finite-time multi-modal robotic control strategy for physical human–robot interaction. The proposed multi-modal controller consists of a modified super-twisting-based finite-time control term that is designed in each interaction mode and a continuity-guaranteed control term. The finite-time control term guarantees finite-time achievement of the desired impedance dynamics in active interaction mode (AIM), makes the tracking error of the reference trajectory converge to zero in finite time in passive interaction mode (PIM), and also guarantees robotic motion stop in finite time in safety-stop mode (SSM). Meanwhile, the continuity-guaranteed control term guarantees control input continuity and steady interaction modes transition. The finite-time closed-loop control stability and the control effectiveness is validated by Lyapunov-based theoretical analysis and simulations on a robot manipulator.

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Torrens-Fontanals, Mariona, Alejandro Peralta-García, Carmine Talarico, Ramon Guixà-González, Toni Giorgino, and Jana Selent. "SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions." Nucleic Acids Research 50, no. D1 (November 11, 2021): D858—D866. http://dx.doi.org/10.1093/nar/gkab977.

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Abstract SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function.

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Sellis, Diamantis, Dimitrios Vlachakis, and Metaxia Vlassi. "Gromita: A Fully Integrated Graphical user Interface to Gromacs 4." Bioinformatics and Biology Insights 3 (January 2009): BBI.S3207. http://dx.doi.org/10.4137/bbi.s3207.

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Gromita is a fully integrated and efficient graphical user interface (GUI) to the recently updated molecular dynamics suite Gromacs, version 4. Gromita is a cross-platform, perl/tcl-tk based, interactive front end designed to break the command line barrier and introduce a new user-friendly environment to run molecular dynamics simulations through Gromacs. Our GUI features a novel workflow interface that guides the user through each logical step of the molecular dynamics setup process, making it accessible to both advanced and novice users. This tool provides a seamless interface to the Gromacs package, while providing enhanced functionality by speeding up and simplifying the task of setting up molecular dynamics simulations of biological systems. Gromita can be freely downloaded from http://bio.demokritos.gr/gromita/ .

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Abdi, Sayed Aliul Hasan, Amena Ali, Shabihul Fatma Sayed, Mohamed Jawed Ahsan, Abu Tahir, Wasim Ahmad, Shatrunajay Shukla, and Abuzer Ali. "Morusflavone, a New Therapeutic Candidate for Prostate Cancer by CYP17A1 Inhibition: Exhibited by Molecular Docking and Dynamics Simulation." Plants 10, no. 9 (September 14, 2021): 1912. http://dx.doi.org/10.3390/plants10091912.

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Morusflavone, a flavonoid from Morus alba L., was evaluated for its interactive ability and stability with CYP17A1, in comparison with abiraterone, which is a Food and Drug Administration (FDA)-approved CYP17A1 inhibitor. CYP17A1 inhibition is an important therapeutic target for prostate cancer. The CHAMM36 force field was used to perform molecular dynamics (MD) simulations in this study. The results show that Morusflavone has significant interactive ability and stability for CYP17A1, in comparison with abiraterone. The final interaction energies for the Morusflavone–CYP17A1 and abiraterone–CYP17A1 complexes were −246.252 KJ/mol and −207.86 KJ/mol, respectively. Since there are only limited therapeutic agents available, such as abiraterone, galeterone, and seviteronel, which are being developed for prostate cancer, information on any potent natural anticancer compounds, such as vinca alkaloids, for prostate cancer treatment is limited. The results of this study show that CYP17A1 inhibition by Morusflavone could be an important therapeutic target for prostate cancer. Further preclinical and clinical evaluations of the lead compound Morusflavone are required to evaluate whether it can serve as a potential inhibitor of CYP17A1, which will be a new hope for prostate cancer treatment.

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Loya, Adil, Antash Najib, Fahad Aziz, Asif Khan, Guogang Ren, and Kun Luo. "Comparative molecular dynamics simulations of thermal conductivities of aqueous and hydrocarbon nanofluids." Beilstein Journal of Nanotechnology 13 (July 7, 2022): 620–28. http://dx.doi.org/10.3762/bjnano.13.54.

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The addition of metal oxide nanoparticles to fluids has been used as a means of enhancing the thermal conductive properties of base fluids. This method formulates a heterogeneous fluid conferred by nanoparticles and can be used for high-end fluid heat-transfer applications, such as phase-change materials and fluids for internal combustion engines. These nanoparticles can enhance the properties of both polar and nonpolar fluids. In the current paper, dispersions of nanoparticles were carried out in hydrocarbon and aqueous-based fluids using molecular dynamic simulations (MDS). The MDS results have been validated using the autocorrelation function and previous experimental data. Highly concurrent trends were achieved for the obtained results. According to the obtained results of MDS, adding CuO nanoparticles increased the thermal conductivity of water by 25% (from 0.6 to 0.75 W·m−1·K−1). However, by adding these nanoparticles to hydrocarbon-based fluids (i.e., alkane) the thermal conductivity was increased three times (from 0.1 to 0.4 W·m−1·K−1). This approach to determine the thermal conductivity of metal oxide nanoparticles in aqueous and nonaqueous fluids using visual molecular dynamics and interactive autocorrelations demonstrate a great tool to quantify thermophysical properties of nanofluids using a simulation environment. Moreover, this comparison introduces data on aqueous and nonaqueous suspensions in one study.

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Allain, Ariane, Isaure Chauvot de Beauchêne, Florent Langenfeld, Yann Guarracino, Elodie Laine, and Luba Tchertanov. "Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs." Faraday Discuss. 169 (2014): 303–21. http://dx.doi.org/10.1039/c4fd00024b.

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Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach – MOdular NETwork Analysis (MONETA) – based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins – a crucial basis to guide the discovery of next-generation allosteric drugs.

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Clarke, Kenneth A. "Microcomputer Simulations of Mechanical Properties of Skeletal Muscle for Undergraduate Classes." Alternatives to Laboratory Animals 15, no. 3 (March 1988): 183–87. http://dx.doi.org/10.1177/026119298801500303.

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In a previous paper, the development of interactive simulations of neurophysiology experiments for undergraduate classes was described. Similar voltage/time displays are used in other areas of undergraduate physiology classes and could therefore be simulated in this way. One such area is in the study of the mechanical properties of muscle, in which a transducer is used to translate muscle length or tension changes into voltages. This paper describes the development and class use of interactive simulations of experiments using isometric recordings from isolated frog muscle.

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Molza, A. E., N. Férey, M. Czjzek, E. Le Rumeur, J. F. Hubert, A. Tek, B. Laurent, M. Baaden, and O. Delalande. "Innovative interactive flexible docking method for multi-scale reconstruction elucidates dystrophin molecular assembly." Faraday Discuss. 169 (2014): 45–62. http://dx.doi.org/10.1039/c3fd00134b.

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At present, our molecular knowledge of dystrophin, the protein encoded by the DMD gene and mutated in myopathy patients, remains limited. To get around the absence of its atomic structure, we have developed an innovative interactive docking method based on the BioSpring software in combination with Small-angle X-ray Scattering (SAXS) data. BioSpring allows interactive handling of biological macromolecules thanks to an augmented Elastic Network Model (aENM) that combines the spring network with non-bonded terms between atoms or pseudo-atoms. This approach can be used for building molecular assemblies even on a desktop or a laptop computer thanks to code optimizations including parallel computing and GPU programming. By combining atomistic and coarse-grained models, the approach significantly simplifies the set-up of multi-scale scenarios. BioSpring is remarkably efficient for the preparation of numeric simulations or for the design of biomolecular models integrating qualitative experimental data restraints. The combination of this program and SAXS allowed us to propose the first high-resolution models of the filamentous central domain of dystrophin, covering repeats 11 to 17. Low-resolution interactive docking experiments driven by a potential grid enabled us to propose how dystrophin may associate with F-actin and nNOS. This information provides an insight into medically relevant discoveries to come.

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Nakano, Aiichiro, Rajiv K. Kalia, Priya Vashishta, Timothy J. Campbell, Shuji Ogata, Fuyuki Shimojo, and Subhash Saini. "Scalable Atomistic Simulation Algorithms for Materials Research." Scientific Programming 10, no. 4 (2002): 263–70. http://dx.doi.org/10.1155/2002/203525.

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A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD) simulations and quantum-mechanical (QM) calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.

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Hokkanen, J. E. "Visual simulations, artificial animals and virtual ecosystems." Journal of Experimental Biology 202, no. 23 (December 1, 1999): 3477–84. http://dx.doi.org/10.1242/jeb.202.23.3477.

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This review is about a field that does not traditionally belong to biological sciences. A branch of computer animation has its mission to create active self-powered objects living artificial lives in the theoretical biology zone. Selected work, of particular interest to biologists, is presented here. These works include animated simulations of legged locomotion, flexible-bodied animals swimming and crawling, artificial fish in virtual ecosystems, automated learning of swimming and the evolution of virtual creatures with respect to morphology, locomotion and behaviour. The corresponding animations are available for downloading via the Internet. I hope that watching these intriguing pieces of visual simulation will stimulate digitally oriented biologists to seize the interactive methods made possible by ever-increasing computing power.

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Rusu, Victor H., Denys E. S. Santos, Marcelo D. Poleto, Marcelo M. Galheigo, Antônio T. A. Gomes, Hugo Verli, Thereza A. Soares, and Roberto D. Lins. "Rotational Profiler: A Fast, Automated, and Interactive Server to Derive Torsional Dihedral Potentials for Classical Molecular Simulations." Journal of Chemical Information and Modeling 60, no. 12 (November 19, 2020): 5923–27. http://dx.doi.org/10.1021/acs.jcim.0c01168.

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Ertl, Thomas, Michael Krone, Stefan Kesselheim, Katrin Scharnowski, Guido Reina, and Christian Holm. "Visual analysis for space–time aggregation of biomolecular simulations." Faraday Discuss. 169 (2014): 167–78. http://dx.doi.org/10.1039/c3fd00156c.

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Conducting a current through a nanopore allows for the analysis of molecules inside the pore because a current modulation caused by the electrostatic properties of the passing molecules can be measured. This mechanism shows great potential for DNA sequencing, as the four different nucleotide bases induce different current modulations. We present a visualisation approach to investigate this phenomenon in our simulations of DNA within a nanopore by combining state-of-the-art molecular visualisation with vector field illustration. By spatial and temporal aggregation of the ions transported through the pore, we construct a velocity field which exhibits the induced current modulations caused by ion flux. In our interactive analysis using parametrisable three-dimensional visualisations, we encountered regions where the ion motion unexpectedly opposes the direction of the applied electric field.

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Stone, John E., Ryan McGreevy, Barry Isralewitz, and Klaus Schulten. "GPU-accelerated analysis and visualization of large structures solved by molecular dynamics flexible fitting." Faraday Discuss. 169 (2014): 265–83. http://dx.doi.org/10.1039/c4fd00005f.

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Hybrid structure fitting methods combine data from cryo-electron microscopy and X-ray crystallography with molecular dynamics simulations for the determination of all-atom structures of large biomolecular complexes. Evaluating the quality-of-fit obtained from hybrid fitting is computationally demanding, particularly in the context of a multiplicity of structural conformations that must be evaluated. Existing tools for quality-of-fit analysis and visualization have previously targeted small structures and are too slow to be used interactively for large biomolecular complexes of particular interest today such as viruses or for long molecular dynamics trajectories as they arise in protein folding. We present new data-parallel and GPU-accelerated algorithms for rapid interactive computation of quality-of-fit metrics linking all-atom structures and molecular dynamics trajectories to experimentally-determined density maps obtained from cryo-electron microscopy or X-ray crystallography. We evaluate the performance and accuracy of the new quality-of-fit analysis algorithmsvis-à-visexisting tools, examine algorithm performance on GPU-accelerated desktop workstations and supercomputers, and describe new visualization techniques for results of hybrid structure fitting methods.

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Dewhurst, David G., Guy J. Brown, and Anthony S. Meehan. "Microcomputer Simulations of Laboratory Experiments in Physiology." Alternatives to Laboratory Animals 15, no. 4 (June 1988): 280–89. http://dx.doi.org/10.1177/026119298801500403.

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Three interactive computer-assisted learning programs based on simulations of simple experiments in physiology (frog sciatic nerve, frog sciatic nerve-gastrocnemius muscle and frog heart) are described. The programs use experimental data to generate realistic, high-resolution graphic simulations of results and present these either on a simulated oscilloscope or on a continuously scrolling display to simulate a chart recorder. Students can thus conduct an experiment and take measurements directly from the monitor, as they would in the real situation. The programs fulfil most of the main objectives of practical physiology teaching and offer an alternative to animal experiments. They are most suitable either for students of biology and health-related subjects, where physiology is an essential component but dissection and tissue handling skills are of minor importance, or in institutions (for example schools, and colleges of further education) where animal experiments are not permitted or the expensive equipment or technical expertise required are lacking. The feasibility of using computer simulation programs to replace animal experiments in teaching is discussed in relation to the teaching objectives of practical physiology classes.

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Woods, Christopher J., Maturos Malaisree, Julien Michel, Ben Long, Simon McIntosh-Smith, and Adrian J. Mulholland. "Rapid decomposition and visualisation of protein–ligand binding free energies by residue and by water." Faraday Discuss. 169 (2014): 477–99. http://dx.doi.org/10.1039/c3fd00125c.

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Recent advances in computational hardware, software and algorithms enable simulations of protein–ligand complexes to achieve timescales during which complete ligand binding and unbinding pathways can be observed. While observation of such events can promote understanding of binding and unbinding pathways, it does not alone provide information about the molecular drivers for protein–ligand association, nor guidance on how a ligand could be optimised to better bind to the protein. We have developed the waterswap (C. J. Woods et al., J. Chem. Phys., 2011, 134, 054114) absolute binding free energy method that calculates binding affinities by exchanging the ligand with an equivalent volume of water. A significant advantage of this method is that the binding free energy is calculated using a single reaction coordinate from a single simulation. This has enabled the development of new visualisations of binding affinities based on free energy decompositions to per-residue and per-water molecule components. These provide a clear picture of which protein–ligand interactions are strong, and which active site water molecules are stabilised or destabilised upon binding. Optimisation of the algorithms underlying the decomposition enables near-real-time visualisation, allowing these calculations to be used either to provide interactive feedback to a ligand designer, or to provide run-time analysis of protein–ligand molecular dynamics simulations.

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Zou, Rui, Yubin Liu, Jie Zhao, and Hegao Cai. "A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory." Sensors 20, no. 17 (September 3, 2020): 5005. http://dx.doi.org/10.3390/s20175005.

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In order to analyze the complex interactive behaviors between the robot and two humans, this paper presents an adaptive optimal control framework for human-robot-human physical interaction. N-player linear quadratic differential game theory is used to describe the system under study. N-player differential game theory can not be used directly in actual scenerie, since the robot cannot know humans’ control objectives in advance. In order to let the robot know humans’ control objectives, the paper presents an online estimation method to identify unknown humans’ control objectives based on the recursive least squares algorithm. The Nash equilibrium solution of human-robot-human interaction is obtained by solving the coupled Riccati equation. Adaptive optimal control can be achieved during the human-robot-human physical interaction. The effectiveness of the proposed method is demonstrated by rigorous theoretical analysis and simulations. The simulation results show that the proposed controller can achieve adaptive optimal control during the interaction between the robot and two humans. Compared with the LQR controller, the proposed controller has more superior performance.

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Zhang, Yuqi, Li Chen, Xiaoyu Wang, Yanyan Zhu, Yongsheng Liu, Huiyu Li, and Qingjie Zhao. "Interactive Mechanism of Potential Inhibitors with Glycosyl for SARS-CoV-2 by Molecular Dynamics Simulation." Processes 9, no. 10 (September 29, 2021): 1749. http://dx.doi.org/10.3390/pr9101749.

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Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a type of Ribonucleic Acid (RNA) coronavirus and it has infected and killed many people around the world. It is reported that the receptor binding domain of the spike protein (S_RBD) of the SARS-CoV-2 virus is responsible for attachment to human angiotensin converting enzyme II (ACE2). Many researchers are attempting to search potential inhibitors for fighting SARS-CoV-2 infection using theoretical or experimental methods. In terms of experimental and theoretical research, Cefuroxime, Erythromycin, Lincomycin and Ofloxacin are the potential inhibitors of SARS-CoV-2. However, the interactive mechanism of the protein SARS-CoV-2 and the inhibitors are still elusive. Here, we investigated the interactions between S_RBD and the inhibitors using molecular dynamics (MD) simulations. Interestingly, we found that there are two binding sites of S_RBD for the four small molecules. In addition, our analysis also illustrated that hydrophobic and π-π stacking interactions play crucial roles in the interactions between S_RBD and the small molecules. In our work, we also found that small molecules with glycosyl group have more effect on the conformation of S_RBD than other inhibitors, and they are also potential inhibitors for the genetic variants of SARS-CoV-2. This study provides in silico-derived mechanistic insights into the interactions of S_RBD and inhibitors, which may provide new clues for fighting SARS-CoV-2 infection.

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Jungck, John R., Holly Gaff, and Anton E. Weisstein. "Mathematical Manipulative Models: In Defense of “Beanbag Biology”." CBE—Life Sciences Education 9, no. 3 (September 2010): 201–11. http://dx.doi.org/10.1187/cbe.10-03-0040.

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Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process—1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets—we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project ( http://bioquest.org/esteem ) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount ). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

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Stevens, Ron, David F. Johnson, and Amy Soller. "Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills." Cell Biology Education 4, no. 1 (March 2005): 42–57. http://dx.doi.org/10.1187/cbe.04-03-0036.

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The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning.

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Tieleman, D. P., B. I. Sejdiu, E. A. Cino, P. Smith, E. Barreto-Ojeda, H. M. Khan, and V. Corradi. "Insights into lipid-protein interactions from computer simulations." Biophysical Reviews 13, no. 6 (November 3, 2021): 1019–27. http://dx.doi.org/10.1007/s12551-021-00876-9.

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Abstract Lipid-protein interactions play an important direct role in the function of many membrane proteins. We argue they are key players in membrane structure, modulate membrane proteins in more subtle ways than direct binding, and are important for understanding the mechanism of classes of hydrophobic drugs. By directly comparing membrane proteins from different families in the same, complex lipid mixture, we found a unique lipid environment for every protein. Extending this work, we identified both differences and similarities in the lipid environment of GPCRs, dependent on which family they belong to and in some cases their conformational state, with particular emphasis on the distribution of cholesterol. More recently, we have been studying modes of coupling between protein conformation and local membrane properties using model proteins. In more applied approaches, we have used similar methods to investigate specific hypotheses on interactions of lipid and lipid-like molecules with ion channels. We conclude this perspective with some considerations for future work, including a new more sophisticated coarse-grained force field (Martini 3), an interactive visual exploration framework, and opportunities to improve sampling.

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Yang, Peng, Peng Liu, and Junmao Li. "The Regulatory Network of Gastric Cancer Pathogenesis and Its Potential Therapeutic Active Ingredients of Traditional Chinese Medicine Based on Bioinformatics, Molecular Docking, and Molecular Dynamics Simulation." Evidence-Based Complementary and Alternative Medicine 2022 (November 26, 2022): 1–17. http://dx.doi.org/10.1155/2022/5005498.

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Objective. This study aims to investigate the functional gene network in gastric carcinogenesis by using bioinformatics; besides, the diagnostic utility of key genes and potential active ingredients of traditional Chinese medicine (TCM) for treatment in gastric cancer have been explored. Methods. The Cancer Genome Atlas and Gene Expression Omnibus databases have been applied to analyze the differentially expressed genes (DEGs) between gastric cancer and normal gastric tissues. Then, the DEGs underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the Metascape database. The STRING database and the Cytoscape software were utilized for the protein-protein interaction network of DEGs and hub genes screening. Furthermore, survival and expression analyses of hub genes were conducted using Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases. By using the Comparative Toxicogenomics Database, the hub genes interconnected with active ingredients of TCM were analyzed to provide potential information for the treatment of gastric cancer. After the molecular docking of the active ingredients of TCM to specific hub gene receptor proteins, the molecular dynamics simulation GROMACS was applied to validate the conformation of the strongest binding ability in the molecular docking. Results. A total of 291 significant DEGs were found, from which 12 hub genes were screened out. Among these hub genes, the expressions of five hub genes including COL1A1, COL5A2, MMP12, SERPINE1, and VCAN were significantly correlated with the overall survival. Furthermore, four potential therapeutic active ingredients of TCM were acquired, including quercetin, resveratrol, emodin, and schizandrin B. In addition, the molecular docking results exhibited that the active ingredients of TCM formed stable binding with the hub gene targets. SERPINE1 (3UT3)-Emodin and COL1A1 (7DV6)-Quercetin were subjected to molecular dynamics simulations as conformations of continuing research significance, and both were found to be stably bound as a result of the interaction of van der Waals potentials, electrostatic, and hydrogen bonding. Conclusion. Our findings may provide novel insights and references for the screening of biomarkers, the prognostic evaluation, and the identification of potential active ingredients of TCM for gastric cancer treatment.

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Loftus, Neil, and Husnu S. Narman. "Use of Machine Learning in Interactive Cybersecurity and Network Education." Sensors 23, no. 6 (March 9, 2023): 2977. http://dx.doi.org/10.3390/s23062977.

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Cybersecurity is a complex subject for students to pursue. Hands-on online learning through labs and simulations can help students become more familiar with the subject at security classes to pursue cybersecurity education. There are several online tools and simulation platforms for cybersecurity education. However, those platforms need more constructive feedback mechanisms, and customizable hands-on exercises for users, or they oversimplify or misrepresent the content. In this paper, we aim to develop a platform for cybersecurity education that can be used either with a user interface or command line and provide auto constructive feedback for command line practices. Moreover, the platform currently has nine levels to practice for different subjects of networking and cybersecurity and a customizable level to create a customized network structure to test. The difficulty of objectives increases at each level. Moreover, an automatic feedback mechanism is developed by using a machine learning model to warn users about their typographical errors while using the command line to practice. A trial was performed with students completing a survey before and after using the application to test the effects of auto-feedback on users’ understanding of the subjects and engagement with the application. The machine learning-based version of the application has a net increase in the user ratings of almost every survey field, such as user-friendliness and overall experience.

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Brown, Guy J., Godfrey G. S. Collins, David G. Dewhurst, and Ian E. Hughes. "Computer Simulations in Teaching Neuromuscular Pharmacology—Time for a Change from Traditional Methods?" Alternatives to Laboratory Animals 16, no. 2 (December 1988): 163–74. http://dx.doi.org/10.1177/026119298801600207.

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Two interactive computer programs are described which illustrate different approaches to teaching the pharmacology of neuromuscular transmission. Both programs are based on a simulation of the in vivo sciatic nerve–tibialis anterior muscle preparation of the cat. Program 1 simulates the preparation and allows students to follow a schedule set by the teacher, or design experiments themselves using drugs (including unknowns) and procedures selected from an extensive menu. The sequence of events and the doses used are entirely in the hands of the user and students “learn by discovery”. Program 2 is an interactive, computer-assisted learning package based on a software simulation of experiments which can be performed on this preparation to illustrate the fundamental pharmacology. The program is menu-driven, contains extensive textual information, makes use of animated graphics, and is accompanied by educational support material and assessments. Details of each program are presented and their use as alternatives to animal experiments is discussed in relation to the primary teaching objectives of practical classes.

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Chakrabarty, Broto, Varun Naganathan, Kanak Garg, Yash Agarwal, and Nita Parekh. "NAPS update: network analysis of molecular dynamics data and protein–nucleic acid complexes." Nucleic Acids Research 47, W1 (May 20, 2019): W462—W470. http://dx.doi.org/10.1093/nar/gkz399.

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Abstract Network theory is now a method of choice to gain insights in understanding protein structure, folding and function. In combination with molecular dynamics (MD) simulations, it is an invaluable tool with widespread applications such as analyzing subtle conformational changes and flexibility regions in proteins, dynamic correlation analysis across distant regions for allosteric communications, in drug design to reveal alternative binding pockets for drugs, etc. Updated version of NAPS now facilitates network analysis of the complete repertoire of these biomolecules, i.e., proteins, protein–protein/nucleic acid complexes, MD trajectories, and RNA. Various options provided for analysis of MD trajectories include individual network construction and analysis of intermediate time-steps, comparative analysis of these networks, construction and analysis of average network of the ensemble of trajectories and dynamic cross-correlations. For protein–nucleic acid complexes, networks of the whole complex as well as that of the interface can be constructed and analyzed. For analysis of proteins, protein–protein complexes and MD trajectories, network construction based on inter-residue interaction energies with realistic edge-weights obtained from standard force fields is provided to capture the atomistic details. Updated version of NAPS also provides improved visualization features, interactive plots and bulk execution. URL: http://bioinf.iiit.ac.in/NAPS/

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Zou, Yu, Zhiwei Liu, Zhiqiang Zhu, and Zhenyu Qian. "Structural Influence and Interactive Binding Behavior of Dopamine and Norepinephrine on the Greek-Key-Like Core of α-Synuclein Protofibril Revealed by Molecular Dynamics Simulations." Processes 7, no. 11 (November 13, 2019): 850. http://dx.doi.org/10.3390/pr7110850.

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The pathogenesis of Parkinson’s disease (PD) is closely associated with the aggregation of α-synuclein (αS) protein. Finding the effective inhibitors of αS aggregation has been considered as the primary therapeutic strategy for PD. Recent studies reported that two neurotransmitters, dopamine (DA) and norepinephrine (NE), can effectively inhibit αS aggregation and disrupt the preformed αS fibrils. However, the atomistic details of αS-DA/NE interaction remain unclear. Here, using molecular dynamics simulations, we investigated the binding behavior of DA/NE molecules and their structural influence on αS44–96 (Greek-key-like core of full length αS) protofibrillar tetramer. Our results showed that DA/NE molecules destabilize αS protofibrillar tetramer by disrupting the β-sheet structure and destroying the intra- and inter-peptide E46–K80 salt bridges, and they can also destroy the inter-chain backbone hydrogen bonds. Three binding sites were identified for both DA and NE molecules interacting with αS tetramer: T54–T72, Q79–A85, and F94–K96, and NE molecules had a stronger binding capacity to these sites than DA. The binding of DA/NE molecules to αS tetramer is dominantly driven by electrostatic and hydrogen bonding interactions. Through aromatic π-stacking, DA and NE molecules can bind to αS protofibril interactively. Our work reveals the detailed disruptive mechanism of protofibrillar αS oligomer by DA/NE molecules, which is helpful for the development of drug candidates against PD. Given that exercise as a stressor can stimulate DA/NE secretion and elevated levels of DA/NE could delay the progress of PD, this work also enhances our understanding of the biological mechanism by which exercise prevents and alleviates PD.

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Byregowda, Bharath Harohalli, Krishnaprasad Baby, Swastika Maity, Usha Yogendra Nayak, Gayathri S, Shaik Mohammad Fayaz, and Yogendra Nayak. "Network pharmacology and in silico approaches to uncover multitargeted mechanism of action of Zingiber zerumbet rhizomes for the treatment of idiopathic pulmonary fibrosis." F1000Research 13 (March 22, 2024): 216. http://dx.doi.org/10.12688/f1000research.142513.1.

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Background Idiopathic pulmonary fibrosis (IPF) is a disease with high mortality, and there are only two specific drugs available for therapeutic management with limitations. The study aims to identify comprehensive therapeutic mechanisms of Zingiber zerumbet rhizomes (ZZR) to treat IPF by using network pharmacology followed battery of in silico studies. Methods The protein-protein interaction network was developed using Cytoscape to obtain core disease targets involved in IPF and their interactive molecules of ZZR. Based on the pharmacophore properties of phytomolecules from ZZR, the drug targets in IPF were explored. Protein-protein interaction network was built in Cytoscape to screen potential targets and components of ZZR. Molecular docking and dynamics were conducted as an empirical study to investigate the mechanism explored through network pharmacology in relation to the hub targets. Results The network analysis conferred kaempferol derivatives that had demonstrated a promising therapeutic effect on the perturbed, robust network hubs of TGF-β1, EGFR, TNF-α, MMP2 & MMP9 reported to alter the biological process of mesenchymal transition, myofibroblast proliferation, and cellular matrix deposition in pulmonary fibrosis. The phytomolecules of ZZR act on two major significant pathways, namely the TGF-β-signaling pathway and the FOXO-signaling pathway, to inhibit IPF. Confirmational molecular docking and dynamics simulation studies possessed good stability and interactions of the protein-ligand complexes by RMSD, RMSF, rGyr, SASA, and principal component analysis (PCA). Validated molecular docking and dynamics simulations provided new insight into exploring the mechanism and multi-target effect of ZZR to treat pulmonary fibrosis by restoring the alveolar phenotype through cellular networking. Conclusions Network pharmacology and in silico studies confirm the multitargeted activity of ZZR in the treatment of IPF. Further in vitro and in vivo studies are to be conducted to validate these findings.

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Pavlov, Evgen, Makoto Taiji, Arturs Scukins, Anton Markesteijn, Sergey Karabasov, and Dmitry Nerukh. "Visualising and controlling the flow in biomolecular systems at and between multiple scales: from atoms to hydrodynamics at different locations in time and space." Faraday Discuss. 169 (2014): 285–302. http://dx.doi.org/10.1039/c3fd00159h.

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A novel framework for modelling biomolecular systems at multiple scales in space and time simultaneously is described. The atomistic molecular dynamics representation is smoothly connected with a statistical continuum hydrodynamics description. The system behaves correctly at the limits of pure molecular dynamics (hydrodynamics) and at the intermediate regimes when the atoms move partly as atomistic particles, and at the same time follow the hydrodynamic flows. The corresponding contributions are controlled by a parameter, which is defined as an arbitrary function of space and time, thus, allowing an effective separation of the atomistic ‘core’ and continuum ‘environment’. To fill the scale gap between the atomistic and the continuum representations our special purpose computer for molecular dynamics, MDGRAPE-4, as well as GPU-based computing were used for developing the framework. These hardware developments also include interactive molecular dynamics simulations that allow intervention of the modelling through force-feedback devices.

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Park, Chailim, and Heewon Kye. "Efficient Massive Computing for Deformable Volume Data Using Revised Parallel Resampling." Sensors 22, no. 16 (August 20, 2022): 6276. http://dx.doi.org/10.3390/s22166276.

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In this paper, we propose an improved parallel resampling technique. Parallel resampling is a deformable object generation method based on volume data applied to medical simulations. Existing parallel resampling is not suitable for massive computing, because the number of samplings is high and floating-point precision problems may occur. This study addresses these problems to obtain improved user latency when performing medical simulations. Specifically, instead of interpolating values after volume sampling, the efficiency is improved by performing volume sampling after coordinate interpolation. Next, the floating-point error in the calculation of the sampling position is described, and the advantage of barycentric interpolation using a reference point is discussed. The experimental results showed a significant improvement over the existing method. Volume data comprising more than 600 images used in clinical practice were deformed and rendered at interactive speed. In an Internet of Everything environment, medical imaging systems are an important application, and simulation image generation is also valuable in the overall system. Through the proposed method, the performance of the whole system can be improved.

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Journal articles on the topic 'Interactive molecular simulations'

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