Atomistic Molecular Dynamics Simulation of Graphene- Isoprene Nanocomposites
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Spoken Tutorial Project, IIT Bombay Brochure for Chemistry Department
Spoken Tutorial Project, IIT Bombay Brochure for Chemistry Department Name of FOSS Applications Employability GChemPaint GChemPaint is an editor for 2Dchem- GChemPaint is currently being developed ical structures with a multiple docu- as part of The Chemistry Development ment interface. Kit, and a Standard Widget Tool kit- based GChemPaint application is being developed, as part of Bioclipse. Jmol Jmol applet is used to explore the Jmol is a free, open source molecule viewer structure of molecules. Jmol applet is for students, educators, and researchers used to depict X-ray structures in chemistry and biochemistry. It is cross- platform, running on Windows, Mac OS X, and Linux/Unix systems. For PG Students LaTeX Document markup language and Value addition to academic Skills set. preparation system for Tex typesetting Essential for International paper presentation and scientific journals. For PG student for their project work Scilab Scientific Computation package for Value addition in technical problem numerical computations solving via use of computational methods for engineering problems, Applicable in Chemical, ECE, Electrical, Electronics, Civil, Mechanical, Mathematics etc. For PG student who are taking Physical Chemistry Avogadro Avogadro is a free and open source, Research and Development in Chemistry, advanced molecule editor and Pharmacist and University lecturers. visualizer designed for cross-platform use in computational chemistry, molecular modeling, material science, bioinformatics, etc. Spoken Tutorial Project, IIT Bombay Brochure for Commerce and Commerce IT Name of FOSS Applications / Employability LibreOffice – Writer, Calc, Writing letters, documents, creating spreadsheets, tables, Impress making presentations, desktop publishing LibreOffice – Base, Draw, Managing databases, Drawing, doing simple Mathematical Math operations For Commerce IT Students Drupal Drupal is a free and open source content management system (CMS). -
Pymol Modelling Workshop
PyMOL Modelling Workshop My website: http://pldserver1.biochem.queensu.ca/~rlc/work/teaching/BCHM442/ There you will find links to download the latest educational version of PyMOL as well as a link to my “Introduction to PyMOL”, which in turn has links to other people's PyMOL tutorials. Note also the PyMOL Wiki: http://pymolwiki.org. Structure files can be found by searching the Protein Data Bank (PDB) for structure: easy to remember website http://www.pdb.org. There is also the PDBe (PDB Europe, http://www.pdbe.org) that contains the same databank of structures, but with a different web interface for searching for structures and a different set of tools for analyzing structures. What is in a PDB file? Lots of information in the “header” (the section of the file preceding the actual atomic coordinates) as well as the coordinates for the atoms. When assessing a structure, one needs to take account of the resolution and R-factor, error estimates and missing residues. There is information about the sequence that was used to determine the structure with a sequence database reference. There is also information about the biological unit. In the case of crystal structures the biological unit may need to be generated by applying crystallographic symmetry operators, although there are web sites that also try to provide that information. (e.g. http://www.ebi.ac.uk/msd-srv/pisa/). Warning: One cannot blindly trust a crystal structure to be providing you with a completely accurate picture of reality. Reading the paper that describes the structure is a good start! Outline of PyMOL usage PyMOL is a very powerful, scriptable (customizable) tool for making publication-quality figures and performing analyses on structures. -
Dmol Guide to Select a Dmol3 Task 1
DMOL3 GUIDE MATERIALS STUDIO 8.0 Copyright Notice ©2014 Dassault Systèmes. All rights reserved. 3DEXPERIENCE, the Compass icon and the 3DS logo, CATIA, SOLIDWORKS, ENOVIA, DELMIA, SIMULIA, GEOVIA, EXALEAD, 3D VIA, BIOVIA and NETVIBES are commercial trademarks or registered trademarks of Dassault Systèmes or its subsidiaries in the U.S. and/or other countries. All other trademarks are owned by their respective owners. Use of any Dassault Systèmes or its subsidiaries trademarks is subject to their express written approval. Acknowledgments and References To print photographs or files of computational results (figures and/or data) obtained using BIOVIA software, acknowledge the source in an appropriate format. For example: "Computational results obtained using software programs from Dassault Systèmes Biovia Corp.. The ab initio calculations were performed with the DMol3 program, and graphical displays generated with Materials Studio." BIOVIA may grant permission to republish or reprint its copyrighted materials. Requests should be submitted to BIOVIA Support, either through electronic mail to [email protected], or in writing to: BIOVIA Support 5005 Wateridge Vista Drive, San Diego, CA 92121 USA Contents DMol3 1 Setting up a molecular dynamics calculation20 Introduction 1 Choosing an ensemble 21 Further Information 1 Defining the time step 21 Tasks in DMol3 2 Defining the thermostat control 21 Energy 3 Constraints during dynamics 21 Setting up the calculation 3 Setting up a transition state calculation 22 Dynamics 4 Which method to use? -
Computational Chemistry
Computational Chemistry as a Teaching Aid Melissa Boule Aaron Harshman Rexford Hoadley An Interactive Qualifying Project Report Submitted to the Faculty of the Worcester Polytechnic Institute In partial fulfillment of the requirements for the Bachelor of Science Degree Approved by: Professor N. Aaron Deskins 1i Abstract Molecular modeling software has transformed the capabilities of researchers. Molecular modeling software has the potential to be a helpful teaching tool, though as of yet its efficacy as a teaching technique has yet to be proven. This project focused on determining the effectiveness of a particular molecular modeling software in high school classrooms. Our team researched what topics students struggled with, surveyed current high school chemistry teachers, chose a modeling software, and then developed a lesson plan around these topics. Lastly, we implemented the lesson in two separate high school classrooms. We concluded that these programs show promise for the future, but with the current limitations of high school technology, these tools may not be as impactful. 2ii Acknowledgements This project would not have been possible without the help of many great educators. Our advisor Professor N. Aaron Deskins provided driving force to ensure the research ran smoothly and efficiently. Mrs. Laurie Hanlan and Professor Drew Brodeur provided insight and guidance early in the development of our topic. Mr. Mark Taylor set-up our WebMO server and all our other technology needs. Lastly, Mrs. Pamela Graves and Mr. Eric Van Inwegen were instrumental by allowing us time in their classrooms to implement our lesson plans. Without the support of this diverse group of people this project would never have been possible. -
Bringing Open Source to Drug Discovery
Bringing Open Source to Drug Discovery Chris Swain Cambridge MedChem Consulting Standing on the shoulders of giants • There are a huge number of people involved in writing open source software • It is impossible to acknowledge them all individually • The slide deck will be available for download and includes 25 slides of details and download links – Copy on my website www.cambridgemedchemconsulting.com Why us Open Source software? • Allows access to source code – You can customise the code to suit your needs – If developer ceases trading the code can continue to be developed – Outside scrutiny improves stability and security What Resources are available • Toolkits • Databases • Web Services • Workflows • Applications • Scripts Toolkits • OpenBabel (htttp://openbabel.org) is a chemical toolbox – Ready-to-use programs, and complete programmer's toolkit – Read, write and convert over 110 chemical file formats – Filter and search molecular files using SMARTS and other methods, KNIME add-on – Supports molecular modeling, cheminformatics, bioinformatics – Organic chemistry, inorganic chemistry, solid-state materials, nuclear chemistry – Written in C++ but accessible from Python, Ruby, Perl, Shell scripts… Toolkits • OpenBabel • R • CDK • OpenCL • RDkit • SciPy • Indigo • NumPy • ChemmineR • Pandas • Helium • Flot • FROWNS • GNU Octave • Perlmol • OpenMPI Toolkits • RDKit (http://www.rdkit.org) – A collection of cheminformatics and machine-learning software written in C++ and Python. – Knime nodes – The core algorithms and data structures are written in C ++. Wrappers are provided to use the toolkit from either Python or Java. – Additionally, the RDKit distribution includes a PostgreSQL-based cartridge that allows molecules to be stored in relational database and retrieved via substructure and similarity searches. -
Manual-2018.Pdf
GROMACS Groningen Machine for Chemical Simulations Reference Manual Version 2018 GROMACS Reference Manual Version 2018 Contributions from Emile Apol, Rossen Apostolov, Herman J.C. Berendsen, Aldert van Buuren, Pär Bjelkmar, Rudi van Drunen, Anton Feenstra, Sebastian Fritsch, Gerrit Groenhof, Christoph Junghans, Jochen Hub, Peter Kasson, Carsten Kutzner, Brad Lambeth, Per Larsson, Justin A. Lemkul, Viveca Lindahl, Magnus Lundborg, Erik Marklund, Pieter Meulenhoff, Teemu Murtola, Szilárd Páll, Sander Pronk, Roland Schulz, Michael Shirts, Alfons Sijbers, Peter Tieleman, Christian Wennberg and Maarten Wolf. Mark Abraham, Berk Hess, David van der Spoel, and Erik Lindahl. c 1991–2000: Department of Biophysical Chemistry, University of Groningen. Nijenborgh 4, 9747 AG Groningen, The Netherlands. c 2001–2018: The GROMACS development teams at the Royal Institute of Technology and Uppsala University, Sweden. More information can be found on our website: www.gromacs.org. iv Preface & Disclaimer This manual is not complete and has no pretention to be so due to lack of time of the contributors – our first priority is to improve the software. It is worked on continuously, which in some cases might mean the information is not entirely correct. Comments on form and content are welcome, please send them to one of the mailing lists (see www.gromacs.org), or open an issue at redmine.gromacs.org. Corrections can also be made in the GROMACS git source repository and uploaded to gerrit.gromacs.org. We release an updated version of the manual whenever we release a new version of the software, so in general it is a good idea to use a manual with the same major and minor release number as your GROMACS installation. -
Open Source Molecular Modeling
Accepted Manuscript Title: Open Source Molecular Modeling Author: Somayeh Pirhadi Jocelyn Sunseri David Ryan Koes PII: S1093-3263(16)30118-8 DOI: http://dx.doi.org/doi:10.1016/j.jmgm.2016.07.008 Reference: JMG 6730 To appear in: Journal of Molecular Graphics and Modelling Received date: 4-5-2016 Accepted date: 25-7-2016 Please cite this article as: Somayeh Pirhadi, Jocelyn Sunseri, David Ryan Koes, Open Source Molecular Modeling, <![CDATA[Journal of Molecular Graphics and Modelling]]> (2016), http://dx.doi.org/10.1016/j.jmgm.2016.07.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Open Source Molecular Modeling Somayeh Pirhadia, Jocelyn Sunseria, David Ryan Koesa,∗ aDepartment of Computational and Systems Biology, University of Pittsburgh Abstract The success of molecular modeling and computational chemistry efforts are, by definition, de- pendent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. 1. Introduction What is Open Source? Free and open source software (FOSS) is software that is both considered \free software," as defined by the Free Software Foundation (http://fsf.org) and \open source," as defined by the Open Source Initiative (http://opensource.org). -
Tutorial Plimpton.Pdf
A Quick Tour of LAMMPS Steve Plimpton Sandia National Labs [email protected] 4th LAMMPS Workshop August 2015 - Albuquerque, NM Follow along with my slides at: http://lammps.sandia.gov/workshops/Aug15/agenda tutorial.html Resources for learning LAMMPS All on web site, most in distro tarball: Web page links: Workshops (beginners sessions), Tutorials Features list: http://lammps.sandia.gov/features.html Manual: doc/Manual.html Intro, Commands, Packages, Accelerating, Howto, Modifying, Errors sections New format has index, allows searching Alphabetized command list: one doc page per command doc/Section commands.html#cmd 5 Papers: find a paper similar to what you want to model Mail list: search archives, post Qs to it http://lammps.sandia.gov/mail.html Examples: about 45 sub-dirs under examples in distro lower-case = simple, upper-case = more complex many have movies: http://lammps.sandia.gov/movies.html Structure of typical input scripts 1 Units and atom style 2 Create simulation box and atoms region, create box, create atoms, region commands lattice command vs box units read data command data file is a text file look at examples/micelle/data.micelle see read data doc page for full syntax 3 Define groups 4 Attributes of atoms: mass, velocity 5 Pair style for atom interactions 6 Fixes for time integration and constraints 7 Computes for diagnostics 8 Output: thermo, dump, restart 9 Run or minimize 10 Rinse and repeat (script executed one command at a time) Obstacle example input script = examples/obstacle/in.obstacle Obstacle input script 1st -
Open Babel Access and Interconvert Chemical Information
Open Babel Access and interconvert chemical information Noel M. O’Boyle Open Babel development team and NextMove Software, Cambridge, UK Dec 2013 EMBL-EBI/Wellcome Trust Course: Resources for Computational Drug Discovery Image credit: AJ Cann (AJC1 on Flickr) Image credit: Jon Osborne (jonno101101 on Flickr) • Volunteer effort, an open source success story – Originally a fork from OpenEye’s OELib in 2001 – Lead is Geoff Hutchison (Uni of Pittsburgh) – 4 or 5 active developers – I got involved in late 2005 • http://openbabel.org • Associated paper: (Open Access) – Open Babel: An open chemical toolbox, J. Cheminf., 2011, 3, 33. 5 Does anyone else use Open Babel? • 40K downloads (from SF) in last 12 months – 1.4K downloads of Windows Python bindings • Paper #1 most accessed in last year – Cited 60 times in 1 year • In short, very widely-used Features • Multiple chemical file formats (+ options) and utility formats • 2D coordinate generation and depiction (PNG and SVG) • 3D coordinate generation, forcefield minimisation, conformer generation • Binary fingerprints (path-based, substructure- based) and associated “fast search” database • Bond perception, aromaticity detection and atom- typing • Canonical labelling, automorphisms, alignment • Plugin architecture • Several command-line applications, but also a software library • Written in C++ but bindings in several languages obabel and file conversion • Basic usage: obabel infile.extn –O outfile.extn • Can also read from stdin, write to stdout, read from a SMILES string, specify the input and -
Downloaded from the PDB
bioRxiv preprint doi: https://doi.org/10.1101/077248; this version posted September 25, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset Michael R. Shirts Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, Colorado, USA Christoph Klein Department of Chemical Engineering, Vanderbilt University, Nashville, TN, USA Jason M. Swails Department of Chemistry and Chemical Biology, Rutgers University, Rutgers, NJ, USA Jian Yin Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA Michael K. Gilson Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA David L. Mobley Departments of Pharmaceutical Sciences and Chemistry, University of California, Irvine, Irvine, CA, USA David A. Case Department of Chemistry and Chemical Biology, Rutgers University, Rutgers, NJ, USA Ellen D. Zhong Department of Chemical Engineering, University of Virginia, Charlottesville, VA, USA∗ We describe our efforts to prepare common starting structures and models for the SAMPL5 blind prediction challenge. We generated the starting input files and single configuration potential energies for the host-guest in the SAMPL5 blind prediction challenge for the GROMACS, AMBER, LAMMPS, DESMOND and CHARMM molecular simulation programs. All conversions were fully automated from the originally prepared AMBER input files using a combination of the ParmEd and InterMol conversion programs. We find that the energy calculations for all molecular dynamics engines for this molecular set agree to a better than 0.1% relative absolute energy for all energy components, and in most cases an order of magnitude better, when reasonable choices are made for different cutoff parameters. -
Open Babel Documentation
Open Babel Documentation Geoffrey R Hutchison Chris Morley Craig James Chris Swain Hans De Winter Tim Vandermeersch Noel M O’Boyle (Ed.) Mar 26, 2021 Contents 1 Introduction 3 1.1 Goals of the Open Babel project.....................................3 1.2 Frequently Asked Questions.......................................4 1.3 Thanks..................................................7 2 Install Open Babel 11 2.1 Install a binary package......................................... 11 2.2 Compiling Open Babel.......................................... 11 3 obabel - Convert, Filter and Manipulate Chemical Data 19 3.1 Synopsis................................................. 19 3.2 Options.................................................. 19 3.3 Examples................................................. 22 3.4 Format Options.............................................. 24 3.5 Append property values to the title.................................... 24 3.6 Generating conformers for structures.................................. 24 3.7 Filtering molecules from a multimolecule file.............................. 25 3.8 Substructure and similarity searching.................................. 28 3.9 Sorting molecules............................................ 28 3.10 Remove duplicate molecules....................................... 28 3.11 Aliases for chemical groups....................................... 29 3.12 Forcefield energy and minimization................................... 30 3.13 Aligning molecules or substructures.................................. -
List of Symbols
Appendix A List of Symbols For convenience, many symbols frequently used in the text are listed below alphabetically. Some of the symbols may play a dual role, in which case the meaning should be obvious from the context. A number in parentheses refers to an Eq. number (or the text or footnote near that Eq. number) in which the symbol is defined or appears for the first time; in a few cases a page number, Table number, Sect. number, footnote (fn.) number, or Fig. number is given instead. Quantum number is abbreviated as q. n. Quantum numbers (atomic): Symbol Description Eq. No. j D l ˙ s Inner q. n. of an electron (3.13) J D L C S Inner (total angular momentum) q. n. of a state (5.51b) l P Azimuthal (orbital) q. n. of an electron (3.1) and (3.2) L D l Azimuthal (orbital) q. n. of a state (5.51c) ml Magnetic orbital q. n. of an electron (3.1) ms Magnetic spin q. n. of an electron (3.1) M Total magnetic q. n. (5.51d) n Principal q. n. of an electron (3.1) s P Spin q. n. of an electron (3.13) S D s Spin q. n. of a state (5.51e) Relativistic azimuthal q. n. of an electron (3.15a) and (3.15b) Relativistic magnetic q. n. of an electron (3.18a) and (3.18b) W.F. Huebner and W.D. Barfield, Opacity, Astrophysics and Space Science Library 402, 457 DOI 10.1007/978-1-4614-8797-5, © Springer Science+Business Media New York 2014 458 Appendix A: List of Symbols Quantum numbers (molecular)1: Symbol Description Eq.