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arXiv 2018年

作者： Kapil, Venkat Rossi, Mariana Marsalek, Ondrej Petraglia, Riccardo Litman, Yair Spura, Thomas Cheng, Bingqing Cuzzocrea, Alice Meißner, Robert H. Wilkins, David M. Juda, Przemyslaw Bienvenue, Sébastien P. Fang, Wei Kessler, Jan Poltavsky, Igor Vandenbrande, Steven Wieme, Jelle Corminboeuf, Clemence Kühne, Thomas D. Manolopoulos, David E. Markland, Thomas E. Richardson, Jeremy O. Tkatchenko, Alexandre Tribello, Gareth A. van Speybroeck, Veronique Ceriotti, Michele Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Fritz Haber Institute of the Max Planck Society Theory Department Faradayweg 4-6 Berlin14195 Germany Physics and Materials Science Research Unit University of Luxembourg L-1511 Luxembourg Department of Chemistry Stanford University StanfordCA94305 United States Atomistic Simulation Centre School of Mathematics and Physics Queen’s University Belfast BelfastBT7 1NN United Kingdom Department of Chemistry and Center for Sustainable Systems Design University of Paderborn Warburger Str. 100 PaderbornD-33098 Germany Laboratory of Physical Chemistry ETH Zurich Zurich8093 Switzerland Center for Molecular Modeling Ghent University Zwijnaarde9052 Belgium Physical and Theoretical Chemistry Laboratory South Parks Road OxfordOX1 3QZ United Kingdom Laboratory for Computational Molecular Design Institute of Chemical Sciences and Engineering École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Charles University Faculty of Mathematics and Physics Ke Karlovu 3 Prague 2121 16 Czech Republic

Progress in the atomic-scale modelling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explicitly, or by computing accurate approximations of the solution and by the development of techniques that use the Born-Oppenheimer (BO) forces to move the atoms on the BO potential energy surface. As a consequence of these developments it is now possible to identify stable or metastable states, to sample configurations consistent with the appropriate thermodynamic ensemble, and to estimate the kinetics of reactions and phase transitions. All too often, however, progress is slowed down by the bottleneck associated with implementing new optimization algorithms and/or sampling techniques into the many existing electronic-structure and empirical-potential codes. To address this problem, we are thus releasing a new version of the i-PI software. This piece of software is an easily extensible framework for implementing advanced atomistic simulation techniques using interatomic potentials and forces calculated by an external driver code. While the original version of the code[1] was developed with a focus on path integral molecular dynamics techniques, this second release of i-PI not only includes several new advanced path integral methods, but also offers other classes of algorithms. In other words, i-PI is moving towards becoming a universal force engine that is both modular and tightly coupled to the driver codes that evaluate the potential energy surface and its derivatives. Copyright © 2018, The Authors. All rights reserved.

关键词： molecular dynamics

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Antimalarial artemisinins derivatives study: molecular modeling and multivariate analysis (PCA, HCA, KNN, SIMCA and SDA)

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3443-3458页

作者： Macdo, Williams Jorge C. Braga, Francinaldo Sarges Santos, César Freitas Da Silva Costa, Josivan De Melo, Geraldo Souza De Mello, Marcello Neiva Sousa, Daniele Salgado Carvalho, José Carlos T. Do Socorro Barros Brasil, Davi Dos Santos, Cleydson Breno R. Laboratory of Molecular Modeling and Simulation System Federal Rural University of Amaznia Campus Capanema-Centro Rua João Pessoa 121 Capanema Pará Brazil Laboratory of Modeling and Computational Chemistry Federal University of Amapá Macapá Amapá Brazil Postgraduate Program in Pharmaceutical Sciences Federal University of Amapá Macapá Amapá Brazil Laboratory of Drug Research School of Pharmaceutical Sciences Federal University of Amapá Macapá Amapá Brazil Institute of Technology Federal University of Pará Belém-Pará-Amazon Brazil

A set of 20 artemisinins compounds with antimalarial activity against clone D-6 strains of Plasmodium falciparum, mefloquine resistant but chloroquine sensitive, were studied through quantum chemistry and multivariate analysis. The geometry optimization of structures was done with the Hartree-Fock (HF) theory and 6-31G∗basis set. Maps of molecular electrostatic potential (MEP) and molecular docking were used to investigate interaction between ligands and receptor (heme). The chemometrics methods employed was Principal Component Analysis (PCA), Hierarquical Cluster Analysis (HCA), K-Nearest Neighbor (KNN), Soft Independent modeling of Class Analogy (SIMCA) and Stepwise Discriminant Analisis (SDA) were employed to select most important descriptors, related to obtain possible relationships for two compounds classes with activity antimalarial. A predictive model was done with a set of 20 compounds artemisinin derivatives with known activity experimental by PCA, HCA, KNN, SIMCA and SDA classification methods. Four descriptors were responsible for separation between origin two class inactives and actives compounds: HOMO (highest occupied molecular orbital), QC3 (charge on atom carbon 3), logP (logarithm of the partition coefficient) and HATS7v (leverage-weighted autocorrelation of lag7/weighted by atomic Van der Waals Volume). The model proposed may follow the results of the MEP maps and docking molecular. Copyright © 2015 American Scientific Publishers.

关键词： Principal component analysis

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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ENISI Visual, an agent-based simulator for modeling gut immunity

ENISI Visual, an agent-based simulator for modeling gut immu...

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2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012

作者： Mei, Yongguo Hontecillas, Raquel Zhang, Xiaoying Bisset, Keith Eubank, Stephen Hoops, Stefan Marathe, Madhav Bassaganya-Riera, Josep Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute Virginia Tech. Blacksburg VA 24061 United States Nutritional Immunology and Molecular Nutrition Laboratory Virginia Bioinformatics Institute Virginia Tech. Blacksburg VA 24061 United States Network Dynamics and Simulation Science Laboratory Virginia Bioinformatics Institute Virginia Tech. Blacksburg VA 24061 United States

ISBN: (纸本)9781467325585

This paper presents ENISI Visual, an agent-based simulator for modeling gut immunity to enteric pathogens. Gastrointestinal systems are important for in-taking food and other nutritions and gut immunity is an important part of human immune system. ENISI Visual provides quality visualizations and users can control initial cell concentrations and the simulation speed, take snapshots, and record videos. The cells are represented with different icons and the icons change colors as their states change. Users can observe real-time immune responses, including cell recruitment, cytokine and chemokine secretion and dissipation, random or chemotactic movement, cell-cell interactions, and state changes. The case study clearly shows that users can use ENISI Visual to develop models and run novel and insightful in silico experiments. © 2012 IEEE.

关键词： Cytology

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ENISI Visual, an agent-based simulator for modeling gut immunity

ENISI Visual, an agent-based simulator for modeling gut immu...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yongguo Mei Raquel Hontecillas Xiaoying Zhang Keith Bisset Stephen Eubank Stefan Hoops Madhav Marathe Josep Bassaganya-Riera The Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute Nutritional Immunology and Molecular Nutrition Laboratory Virginia Tech Blacksburg VA USA The Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute Network Dynamics and Simulation Science Laboratory Virginia Tech Blacksburg VA USA

关键词： Immune system Visualization Computational modeling Microorganisms Pathogens Biological system modeling Mathematical model

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ENteric Immunity SImulator: A Tool for in silico Study of Gut Immunopathologies

ENteric Immunity SImulator: A Tool for in silico Study of Gu...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Katherine V. Wendeldorf Josep Bassaganya-Riera Keith Bisset Stephen Eubank Raquel Hontecillas Madhav Marathe Network Dynamics and Simulation Science Laboratory Center of Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute Virginia Polytechnic Institute and University Blacksburg VA USA Nutritional Immunology and Molecular Medicine Laboratory Center of Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute Virginia Polytechnic Institute and University Blacksburg VA USA Department of Computer Science Center of Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute Virginia Polytechnic Institute and University Blacksburg VA USA

Clinical symptoms of gastrointestinal (GI) infections are often caused by the inflammatory response elicited to eliminate the invading microbe. Here we present ENISI, a simulator of GI immune mechanisms in response to resident commensal bacteria as well as invading pathogens and the effect on host clinical symptoms. ENISI is a tool for identifying treatment strategies that reduce inflammation-induced damage and, at the same time, ensure pathogen removal by allowing one to test plausibility of in vitro observed behavior as explanations for observations in vivo, propose behaviors not yet tested in vitro that could explain these tissue-level observations, and conduct low-cost, preliminary experiments of proposed interventions/ treatments. An example of such application is shown in which we simulate dysentery resulting from B. hyodysenteriae infection and identify aspects of the host immune pathways that lead to continued inflammation-induced tissue damage even after pathogen elimination.

关键词： Immune system Microorganisms Automata Pathogens Blood Tissue damage Computational modeling

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Inside Back Cover: The Reaction Coordinate of a Bacterial GH47 α-Mannosidase: A Combined Quantum Mechanical and Structural Approach (Angew. Chem. Int. Ed. 44/2012)

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Angewandte Chemie International Edition 2012年第44期51卷

作者： Andrew J. Thompson Dr. Jerome Dabin Javier Iglesias-Fernández Dr. Albert Ardèvol Dr. Zoran Dinev Assoc. Prof. Spencer J. Williams Dr. Omprakash Bande Dr. Aloysius Siriwardena Carl Moreland Dr. Ting-Chou Hu David K. Smith Prof. Harry J. Gilbert Prof. Carme Rovira Prof. Gideon J. Davies Department of Chemistry University of York Heslington York YO10 5DD (UK) Computer Simulation & Modeling Laboratory Parc Científic de Barcelona Baldiri Reixac 4 08028 Barcelona (Spain) Institut de Química Teòrica i Computacional (IQTCUB) (Spain) Present address: Departament de Química Orgànica Universitat de Barcelona Martí i Franquès 1 08028 Barcelona (Spain) Present address: Department of Chemistry and Applied Biosciences ETH Zurich USI Campus Via Giuseppe Buffi 13 CH-6900 Lugano (Switzerland) School of Chemistry and Bio21 Molecular Science and Biotechnology Institute University of Melbourne Parkville (Australia) Université de Picardie Jules Vernes Laboratoire des Glucides (CNRS-FRE 3617) 33 Rue Saint Leu 80039 Amiens (France) Institute for Cell and Molecular Biosciences The Medical School Newcastle University Framlington Place Newcastle upon Tyne NE2 4HH (UK) Institució Catalana de Recerca i Estudis Avançats (ICREA) Passeig Lluís Companys 23 08020 Barcelona (Spain) Carme Rovira Computer Simulation & Modeling Laboratory Parc Científic de Barcelona Baldiri Reixac 4 08028 Barcelona (Spain) Gideon J. Davies Department of Chemistry University of York Heslington York YO10 5DD (UK)

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The Reaction Coordinate of a Bacterial GH47 α‐Mannosidase: A Combined Quantum Mechanical and Structural Approach†

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Angewandte Chemie 2012年第44期124卷

作者： Andrew J. Thompson Jerome Dabin Javier Iglesias‐Fernández Albert Ardèvol Zoran Dinev Spencer J. Williams Omprakash Bande Aloysius Siriwardena Carl Moreland Ting‐Chou Hu David K. Smith Harry J. Gilbert Carme Rovira Gideon J. Davies Department of Chemistry University of York Heslington York YO10 5DD (UK) Computer Simulation & Modeling Laboratory Parc Científic de Barcelona Baldiri Reixac 4 08028 Barcelona (Spain) Institut de Química Teòrica i Computacional (IQTCUB) (Spain) Present address: Departament de Química Orgànica Universitat de Barcelona Martí i Franquès 1 08028 Barcelona (Spain) Present address: Department of Chemistry and Applied Biosciences ETH Zurich USI Campus Via Giuseppe Buffi 13 CH‐6900 Lugano (Switzerland) School of Chemistry and Bio21 Molecular Science and Biotechnology Institute University of Melbourne Parkville (Australia) Université de Picardie Jules Vernes Laboratoire des Glucides (CNRS‐FRE 3617) 33 Rue Saint Leu 80039 Amiens (France) Institute for Cell and Molecular Biosciences The Medical School Newcastle University Framlington Place Newcastle upon Tyne NE2 4HH (UK) Institució Catalana de Recerca i Estudis Avançats (ICREA) Passeig Lluís Companys 23 08020 Barcelona (Spain)

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Innenrücktitelbild: The Reaction Coordinate of a Bacterial GH47 α‐Mannosidase: A Combined Quantum Mechanical and Structural Approach (Angew. Chem. 44/2012)

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Angewandte Chemie 2012年第44期124卷

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