Software Extensions to UCSF Chimera for Interactive Visualization of Large Molecular Assemblies

Total Page:16

File Type:pdf, Size:1020Kb

Software Extensions to UCSF Chimera for Interactive Visualization of Large Molecular Assemblies View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Structure, Vol. 13, 473–482, March, 2005, ©2005 Elsevier Ltd All rights reserved. DOI 10.1016/j.str.2005.01.006 Software Extensions to UCSF Chimera for Interactive Visualization of Large Molecular Assemblies Thomas D. Goddard, Conrad C. Huang, semblies (Figure 1). The icosahedral capsid contains 3 and Thomas E. Ferrin1,* million atoms and cannot be opened in existing desk- Department of Pharmaceutical Chemistry top analysis software due to insufficient memory. The University of California, San Francisco capsid can be described by using only 50,000 atom po- San Francisco, California 94143 sitions and the 60-fold icosahedral symmetry, but most existing software is not able to read and use these sym- metry matrices. Current low-resolution display styles such as ribbons and molecular surfaces are too de- Summary tailed for making an informative display of this large system, and the excessive detail prevents smooth in- Many structures of large molecular assemblies such teractive rotation of the model because of insufficient as virus capsids and ribosomes have been experi- graphics rendering speed. The atomic contacts of viral mentally determined to atomic resolution. We con- RNA with the capsid are of interest for this system. The sider four software problems that arise in interactive simplest algorithm for finding these contacts, calculat- visualization and analysis of large assemblies: how to ing distances between all pairs of atoms, requires sev- represent multimers efficiently, how to make cartoon eral minutes of computation and thus is not fast enough representations, how to calculate contacts efficiently, for interactive exploration of the contacts. In summary, and how to select subassemblies. We describe tech- analysis of this large system runs into problems of lim- niques and algorithms we have developed and give ited computer resources that require better data repre- examples of their use. Existing molecular visualiza- sentations and algorithms and new features such as low-resolution display styles. tion programs work well for single protein and nucleic Virus capsids are the largest structures in the PDB. acid molecules and for small complexes. The meth- All other PDB structures of cellular machinery are sig- ods presented here are proposed as features to add nificantly smaller in number of atoms, and they can be to existing programs or include in next-generation opened in current-generation molecular analysis pro- visualization software to allow easy exploration of as- grams. Yet, software designed for small complexes is semblies containing tens to thousands of macromole- cumbersome to use on these larger systems. An exam- cules. Our approach is pragmatic, emphasizing sim- ple is provided by a recent paper describing the in- plicity of code, reliability, and speed. The methods teractions of 27 ribosomal proteins with the 23S ribo- described have been distributed as the Multiscale somal RNA (Klein et al., 2004)(Figure 2). Each of the extension of the UCSF Chimera (www.cgl.ucsf.edu/ intermolecular interfaces between the 27 proteins and chimera) molecular graphics program. the 101 helices of the 23S RNA are individually ana- lyzed and illustrated in that work, and differences be- tween two different organisms are noted. Interactively Introduction exploring this large set of interfaces would benefit from the ability to switch views from the full assembly to indi- Advances in electron cryomicroscopy and X-ray crys- vidual proteins and neighboring helices with minimum tallography have enabled structures of many cellular effort. Low-resolution depiction of the whole assembly machines to be determined. Structures such as ribo- and methods of treating the 101 helices comprising the somes, virus capsids, molecular motors, cytoskeletal ribosomal RNA as natural structural units are useful ca- filaments, proteasomes, nucleosomes, chaperonins, pabilities for facile navigation of this assembly. transmembrane channels, and pumps, composed of The virus and ribosome studies described above tens to thousands of macromolecules, have been de- were carried out without the benefit of interactive analysis termined to atomic resolution. The inventory of large software designed for handling these large complexes. Such studies can be done laboriously with software de- molecular assemblies is growing rapidly. At the start of signed for small complexes, as well as with nonin- 2000, the Protein Data Bank (PDB) (Berman et al., 2000) teractive software and custom-written analysis pro- contained 137 structures with 10 or more chains, while grams. For virus capsids, files containing small pieces at the start of 2004, there were 517 such structures. with just the needed asymmetric units can be created Existing software to interactively display and analyze with specialized programs and then explored inter- macromolecules is difficult to use on these large as- actively. For the helices of the 23S rRNA, many exact semblies. residue sequence ranges can be entered by hand to A published study of viral RNA bound to the outside specify regions of interest during interactive analysis. of bluetongue virus capsid (Diprose et al., 2002) il- Software that provides more efficient ways of exploring lustrates several limitations with existing interactive large assemblies will speed up the elucidation of the molecular analysis programs when applied to large as- functions of these systems. Past efforts to develop analysis software for large as- semblies have addressed some of the limitations. A *Correspondence: [email protected] study done 6 years ago (Macke et al., 1998), when 1Lab address: http://www.cgl.ucsf.edu many fewer experimental structures were available, fo- Structure 474 Figure 1. Bluetongue Virus Capsid with Bound Viral RNA (A) Two protein layers of bluetongue virus capsid with viral RNA bound to the surface (PDB models 2btv and 1h1k). Each molecule is displayed by using a low-resolution sur- face. RNA contacts seven protein monomers (shown in blue) on the surface. The model contains approximately 3 million atoms (no hydrogens) and 900 molecular components. (B) Atomic contacts between RNA and cap- sid proteins within a 5 Å range shown in black. cused on building molecular assemblies by using sym- (Humphrey et al., 1996) provide many of these capabili- metry operations and displaying them with variable res- ties. Analysis of large assemblies requires the same olution surfaces using spherical harmonics (Duncan tools to study many local regions in atomic detail. On and Olson, 1995). Other work (Bajaj et al., 2004) has top of these, better facilities to navigate to small re- explored computer graphics techniques to efficiently gions of interest, restrict attention to them, and show display molecular properties at various resolutions by them in the context of the larger assembly are needed. using texture maps on surfaces and volumetric render- The main virtue of the tools we have developed and ing. Another group has developed a web service to ap- describe here is that they interoperate within a program ply symmetry matrices to generate atomic coordinates that provides the rich set of analysis capabilities al- of crystal packings and visualize them (Hussain et al., ready created for studying smaller systems. To suc- 2003). Most macromolecular structures are determined cessfully augment an already complex software pack- by crystallography, so this type of large molecular as- age, we have favored simple code, reliable algorithms, sembly is common. and speed. Our aim is to develop the breadth of capa- The distinctive feature of the work presented here is bilities necessary for effective analysis of large assem- our focus on software system integration. Many meth- blies, rather than maximal performance of any one soft- ods exist for analyzing single molecules and small com- ware component. plexes, for example, structure and sequence align- The following sections address the most essential ments, molecular dynamics, binding site prediction, software capabilities needed for exploring large assem- electrostatics calculations, hydrogen bond identifica- blies. We describe how to efficiently represent multi- tion, superimposing homologous or mutant structures, meric molecular complexes in computer memory, an testing conformational changes, and fitting experimen- algorithm for creating low-resolution surfaces to repre- tal density maps. Programs such as UCSF Chimera sent molecules, an algorithm for finding atomic con- (Pettersen et al., 2004), PyMol (DeLano, 2002), and VMD tacts between large sets of atoms, and a hierarchical Figure 2. Protein-RNA Contacts in Large Ri- bosomal Subunit (A) Arrangement of 27 ribosomal proteins contacting 23S ribosomal RNA (gray) and 5S ribosomal RNA (black) (PDB model 1s72). Each protein and RNA is represented by a low-resolution surface. This coarse view is used to select and focus on individual pro- tein-RNA interactions. (B) Displaying atoms as spheres creates a pebbly surface that reduces the effec- tiveness of the three-dimensional cues pro- vided by object illumination techniques. (C) Ribbon display style permits seeing through the structure. Clear display of pro- tein-RNA interactions requires restricting the view to small pieces of the assembly. Extensions to UCSF Chimera 475 representation of quaternary structure useful for select- column. Most molecular visualization software is un- ing pieces of a large assembly.
Recommended publications
  • Latest Stable Copy and Install It With: Chmod+X Chimera- *.Bin&&./Chimera- *.Bin
    Tangram Suite Documentation Release 0.0.8 InsiliChem Mar 26, 2019 General instructions 1 What is Tangram Suite 3 2 How to install Tangram Suite5 3 General usage 7 4 FAQ & Known issues 9 5 List of Tans 11 6 Tangram BondOrder 13 7 Tangram QMSetup 15 8 Tangram DummyAtoms 17 9 Tangram GAUDIView 19 10 Tangram MMSetup 21 11 Tangram NCIPlot 23 12 Tangram NormalModes 25 13 Tangram OrbiTraj 27 14 Tangram PLIP 29 15 Tangram PoPMuSiCGUI 31 16 Tangram PropKaGUI 33 17 Tangram ReVina 35 18 Tangram SubAlign 37 19 Tangram TalaDraw 39 i ii Tangram Suite Documentation, Release 0.0.8 It’s composed of several independent graphical interfaces and commands for UCSF Chimera. General instructions 1 Tangram Suite Documentation, Release 0.0.8 2 General instructions CHAPTER 1 What is Tangram Suite In progress 3 Tangram Suite Documentation, Release 0.0.8 4 Chapter 1. What is Tangram Suite CHAPTER 2 How to install Tangram Suite 2.1 Install the full Tangram Suite (recommended) 1 - If you don’t have UCSF Chimera installed, download the latest stable copy and install it with: chmod+x chimera- *.bin&&./chimera- *.bin 2 - Download the latest installer from the releases page (Linux and MacOS only) and run it with: bash tangram-*.sh 2.2 Using the conda meta-package Instead of using the Bash installer, you can use conda (if you are already using it) to create a new environment with the tangram metapackage, which will handle all the dependencies. While in alpha, both insilichem channels are needed (the main one and also the dev label): conda create-n tangram-c insilichem/label/dev-c insilichem-c omnia-c rdkit-c ,!conda-forge tangram 2.3 Updating extensions Each extension will check if there’s a new release available every time you launch it.
    [Show full text]
  • UCSF Chimera Was Developed by the Computer Graphics Laboratory at the University of California, San Francisco, Under Support of NIH Grant P41-RR01081
    matrixcopy apply the transformation matrix of one model to another tcolor color using texture map colors UCSF Chimera matrixget write the current transformation matrices to a ®le texture de®ne texture maps and associated colors QUICK REFERENCE GUIDE June 2007 matrixset read and apply transformation matrices from a ®le thickness move the clipping planes in opposite directions minimize energy-minimize structures turn rotate about the X, Y, or Z axis mmaker (matchmaker) align models in sequence, then in 3D vdw* display van der Waals (VDW) surface modelcolor set color at the model level vdwde®ne* set VDW radii Commands modeldisplay* set display at the model level vdwdensity set VDW surface dot density *reverse function Äcommand available move translate along the X, Y, or Z axis version show copyright information and Chimera version movie capture image frames and assemble them into a movie viewdock start ViewDock and load docking results 2dlabels create arbitrary text labels and place them in 2D namesel name and save the current selection wait suspend command processing until motion has stopped ac enable accelerators (keyboard shortcuts) neon create a shadowed stick/tube image (not on Windows) window adjust the view to contain the speci®ed atoms addaa add an amino acid to a peptide C-terminus objdisplay* display graphical objects windowsize adjust the dimensions of the graphics window addcharge assign partial charges to atoms open* read structures and data, execute command ®les write save a molecule model as a PDB ®le addh add hydrogens pdbrun
    [Show full text]
  • 3D-Printing Models for Chemistry
    3D-Printing Models for Chemistry: A Step-by-Step Open-Source Guide for Hobbyists, Corporate ProfessionAls, and Educators and Student in K-12 and Higher Education Poster Elisabeth Grace Billman-Benveniste+, Jacob Franz++, Loredana Valenzano-Slough+* +Department of Chemistry, Michigan Technological University, ++Department of Mechanical Engineering, Michigan Technological University *Corresponding Author References 1. “LulzBot TAZ 5.” LulzBot, 14 Aug. 2018, www.lulzbot.com/store/printers/lulzbot-taz-5 2. Gaussian 16, Revision B.01, Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; Li, X.; Caricato, M.; Marenich, A. V.; Bloino, J.; Janesko, B. G.; Gomperts, R.; Mennucci, B.; Hratchian, H. P.; Ortiz, J. V.; Izmaylov, A. F.; Sonnenberg, J. L.; Williams-Young, D.; Ding, F.; Lipparini, F.; Egidi, F.; Goings, J.; Peng, B.; Petrone, A.; Henderson, T.; Ranasinghe, D.; ZakrzeWski, V. G.; Gao, J.; Rega, N.; Zheng, G.; Liang, W.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; HasegaWa, J.; Ishida, M.; NakaJima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Throssell, K.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M. J.; Heyd, J. J.; Brothers, E. N.; Kudin, K. N.; Staroverov, V. N.; Keith, T. A.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A. P.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Millam, J. M.; Klene, M.; Adamo, C.; Cammi, R.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Farkas, O.; Foresman, J. B.; Fox, D. J. Gaussian, Inc., Wallingford CT, 2016. 3.
    [Show full text]
  • Development and Application of a Computational Platform for Complex Molecular Design Jaime Rodríguez-Guerra Pedregal
    ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en Development and Application of a Computational Platform for Complex Molecular Design a dissertation submitted by Jaime Rodríguez-Guerra Pedregal & directed by Prof. Dr. Jean-Didier Maréchal in fulfillment of the requirements for the degree of Doctor of Biotechnology Tutor: Prof. Dr. Jordi Joan Cairó Badillo Department of Chemical, Biological and Environmental Engineering Universitat Autònoma de Barcelona July 2018 Development and Application of a Computational Platform for Complex Molecular Design a dissertation submitted by & recommended for acceptance by advisor Jaime Rodríguez-Guerra Pedregal Prof. Dr. Jean-Didier Maréchal Tutor: Prof. Dr. Jordi Joan Cairó Badillo Department of Chemical, Biological and Environmental Engineering Universitat Autònoma de Barcelona July 2018 ©2018 – Jaime Rodríguez-Guerra Pedregal Licensed as Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs In the beginning, there was nothing. And God said «Let there be light». And there was light. There was still nothing, but you could see it a lot better. —WoodyAllen. Development and Application of a Computational Platform for Complex Molecular Design by Jaime Rodríguez-Guerra Pedregal Abstract In this dissertation, a series of novel computational modeling tools is reported.
    [Show full text]
  • Hands-On Tutorials of Autodock 4 and Autodock Vina
    Hands-on tutorials of AutoDock 4 and AutoDock Vina Pei-Ying Chu (朱珮瑩) Supervisor: Jung-Hsin Lin (林榮信) Research Center for Applied Sciences, Academia Sinica 2018 Frontiers in Computational Drug Design, Academia Sinica, March 16-20, 2018 AutoDock http://autodock.scripps.edu AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. AutoDock 4 is free and is available under the GNU General Public License. 2 AutoDock Vina http://vina.scripps.edu/ Because the scoring functions used by AutoDock 4 and AutoDock Vina are different and inexact, on any given problem, either program may provide a better result. AutoDock Vina is available under the Apache license, allowing commercial and 3 non-commercial use and redistribution. http://autodock.scripps.edu/downloads These programs were installed on VM. 4 http://mgltools.scripps.edu/ AutoDockTools (ADT) is developed to help set up the docking. ADT is included in MGLTools packages. 5 In general, each docking (AutoDock 4 and/or AutoDock Vina) requires: 1. structure of the receptor (protein), in pdbqt format 2. structure of the ligand (small molecule, drug, etc.) in pdbqt format 3. docking and grid parameters (search space) PDBQT format is very similar to PDB format but it includes partial charges ('Q') and AutoDock 4 (AD4) atom types ('T'). • Preparing the ligand involves ensuring that its atoms are assigned the correct AutoDock4 atom types, adding Gasteiger charges if necessary, merging non-polar hydrogens, detecting aromatic carbons if any, and setting up the 'torsion tree'.
    [Show full text]
  • Mai Muuttunut Pilit Muut Aidi Mini
    MAIMUUTTUNUT US009963689B2 PILIT MUUT AIDI MINI (12 ) United States Patent ( 10 ) Patent No. : US 9 ,963 , 689 B2 Doudna et al. ( 45) Date of Patent: May 8 , 2018 ( 54 ) CASI CRYSTALS AND METHODS OF USE FOREIGN PATENT DOCUMENTS THEREOF WO WO 2013 / 126794 AL 8 / 2013 ( 71 ) Applicant: The Regents of the University of wo WO 2013 / 142578 A19 / 2013 California , Oakland , CA (US ) WO WO 2013 / 176772 A1 11/ 2013 ( 72 ) Inventors : Jennifer A . Doudna , Oakland , CA OTHER PUBLICATIONS (US ) ; Samuel H . Sternberg , Oakland , McPherson , A . Current Approaches to Macromolecular Crystalli CA (US ) ; Martin Jinek , Oakland , CA zation . European Journal of Biochemistry . 1990 . vol . 189 , pp . (US ) ; Fuguo Jiang , Oakland , CA (US ); 1 - 23 . * Emine Kaya , Oakland , CA (US ) ; Kundrot, C . E . Which Strategy for a Protein Crystallization Project ? Cellular Molecular Life Science . 2004 . vol . 61, pp . 525 - 536 . * David W . Taylor, Jr. , Oakland , CA Benevenuti et al. , Crystallization of Soluble Proteins in Vapor (US ) Diffusion for X - ray Crystallography , Nature Protocols , published on - line Jun . 28 , 2007 , 2 ( 7 ) : 1633 - 1651. * ( 73 ) Assignee : THE REGENTS OF THE Cudney R . Protein Crystallization and Dumb Luck . The Rigaku UNIVERSITY OF CALIFORNIA , Journal. 1999 . vol. 16 , No . 1 , pp . 1 - 7 . * Drenth , “ Principles of Protein X - Ray Crystallography ” , 2nd Edi Oakland , CA (US ) tion , 1999 Springer - Verlag New York Inc ., Chapter 1 , p . 1 - 21. * Moon et al . , “ A synergistic approach to protein crystallization : ( * ) Notice : Subject to any disclaimer , the term of this Combination of a fixed -arm carrier with surface entropy reduction ” , patent is extended or adjusted under 35 Protein Science , 2010 , 19 : 901 -913 .
    [Show full text]
  • UCSF Chimera[Mdash]A Visualization System for Exploratory Research And
    UCSF Chimera—A Visualization System for Exploratory Research and Analysis ERIC F. PETTERSEN, THOMAS D. GODDARD, CONRAD C. HUANG, GREGORY S. COUCH, DANIEL M. GREENBLATT, ELAINE C. MENG, THOMAS E. FERRIN Computer Graphics Laboratory, Department of Pharmaceutical Chemistry, University of California, 600 16th Street, San Francisco, California 94143-2240 Received 24 February 2004; Accepted 6 May 2004 DOI 10.1002/jcc.20084 Published online in Wiley InterScience (www.interscience.wiley.com). Abstract: The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1605–1612, 2004 Key words: molecular graphics; extensibility; visualization; multiscale modeling; sequence alignment Introduction had not anticipated.
    [Show full text]
  • Functional Behavior of Molecular Baskets and Structure-Activity Studies on Trapping Organophosphorus Nerve Agents in Water
    Functional Behavior of Molecular Baskets and Structure-Activity Studies on Trapping Organophosphorus Nerve Agents in Water DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Yian Ruan Graduate Program in Chemistry The Ohio State University 2014 Dissertation Committee: Jovica D. Badjic, Advisor Christopher M. Hadad Jon R. Parquette Copyright by Yian Ruan 2014 Abstract Molecular recognition is exploited by nature to carry out delicately regulated reactions and form precisely organized structures in living organisms. Enzymes promote reactions by preorganizing substrates and stabilizing transition states in an active site via covalent and non-covalent interactions. Receptor proteins and antibodies can respond selectively to stimuli and trigger subsequent activities. These protein-substrate interactions have been great inspirations for chemists in the design of synthetic receptors as hosts and the study of their molecular recognition properties. Investigation of recognition behaviors can help decipher sub-cellular processes. Moreover, some artificial host-guest complexes have found applications in catalysis, sensing, imaging and drug delivery systems. The Badjic group has developed a family of host molecules called molecular baskets to study the effect of gating on molecular recognition. These baskets possess a cavity formed by a benzene base and phthalimide side walls. Pyridine-based gates close the basket via hydrogen bonds or metal chelation. Tuning the electronic and steric characteristics of gates affects the rate of guests entering and departing the basket. ii With all the knowledge about molecular gating, questions arise as to whether these gates can be applied to other platforms and how the mechanism of gating will be affected.
    [Show full text]
  • Molecular Dynamics (MD) for Cancer Control Protocol
    Molecular Dynamics (MD) for Cancer control Protocol Claudio Nicolini ( [email protected] ) Claudio Ando Nicolini's Lab, NanoWorld, USA; HC Professor Nanobiotechnology, Lomonosov Moscow State University, Russia; Foreign Member Russian Academy of Sciences; President NWI Fondazione EL.B.A. Nicolini; Editor-in-Chief NWJ, Santa Clara, USA Marine Bozdaganyan Claudio Ando Nicolini's Lab, NanoWorld, USA; Lomonosov Moscow State University (MSU), Moscow, Russia; Fondazione EL.B.A. Nicolini Nicola Luigi Bragazzi Claudio Ando Nicolini's Lab, NanoWorld, USA Philippe Orekhov Claudio Ando Nicolini's Lab, NanoWorld, USA Eugenia Pechkova Claudio Ando Nicolini's Lab, NanoWorld, USA Method Article Keywords: Langmuir-Blodgett (LB)-based crystallography Posted Date: March 15th, 2016 DOI: https://doi.org/10.1038/protex.2016.016 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/13 Abstract In the present protocol, we describe how molecular dynamics \(MD) can be applied for studying Langmuir-Blodgett \(LB)-based crystal proteins. MD can therefore play a major role in nanomedicine, as well as in personalized medicine. Introduction The computer simulation of dynamics in molecular systems is widely used in molecular physics, biotechnology, medicine, chemistry and material sciences to predict physical and mechanical properties of new samples of matter. In the molecular dynamics method there is a polyatomic molecular system in which all atoms are interacting like material points, and behavior of the atoms is described by the equations of classical mechanics. This method allows doing simulations of the system of the order of 106 atoms in the time range up to 1 microsecond.
    [Show full text]
  • Eduardo's Guide for 3D Printing Proteins Using Chimera for 3D Printing
    Eduardo’s Guide for 3D Printing Proteins Eduardo da Veiga Beltrame – [email protected] - www.munfred.com ​ ​ ​ Using Chimera for 3D Printing UCSF Chimera is a free and open source molecular visualizer. In this tutorial we’ll show how Chimera can be used to generate 3D printable molecular models for FDM/FFF desktop 3D printers. You can download Chimera at https://www.cgl.ucsf.edu/chimera/. ​ ​ Finding PDB Files First, you need the coordinate file of the molecule you want to print. The files containing the atoms coordinates for a molecule are called .pdb files (for protein data bank). These structures are determined using an array of techniques such as x-ray crystallography and nuclear magnetic resonance, and when they are published they are also deposited in databases and become freely available for download. The biggest such database is the Protein Data Bank, and if you are interested it's worth a visit: www.rcsb.org ​ If you’re looking for cool structures and some explanations, the molecule of the month PDB articles at http://pdb101.rcsb.org/ are a good way to start browsing. They are ​ ​ written by David Goodsell, who is awesome. If you can't find your molecule, if it's not on the PDB it's probably because nobody knows it's structure yet. If what you want is some small molecule, you can try searching for the structure online, or can draw it using Avogadro, a free and open source molecule editor you can get at www.avogadro.cc. ​ ​ Visualizing and Exporting Models Once you have your PDB file, you can render it on a molecular visualizer.
    [Show full text]
  • Visualizing Protein Structures-Tools and Trends
    Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 12 January 2020 Visualizing protein structures - tools and trends 1,2 3 1,2 X. Martinez ,​ M. Chavent ,​ M. Baaden ​ ​ ​ 1) CNRS, Université de Paris, UPR 9080, Laboratoire de Biochimie Théorique, 13 rue Pierre et Marie Curie, F-75005, Paris, France 2) Institut de Biologie Physico-Chimique-Fondation Edmond de Rotschild, PSL Research University, Paris, France 3) Institut de Pharmacologie et de Biologie Structurale IPBS, Université de Toulouse, CNRS, UPS, Toulouse, France Abstract Molecular visualisation is fundamental in the current scientific literature, textbooks and dissemination materials, forming an essential support for presenting results, reasoning on and formulating hypotheses related to molecular structure. Visual exploration has become easily accessible on a broad variety of platforms thanks to advanced software tools that render a great service to the scientific community. These tools are often developed across disciplines bridging computer science, biology and chemistry. Here we first describe a few Swiss Army knives geared towards protein visualisation for everyday use with an existing large user base, then focus on more specialised tools for peculiar needs that are not yet as broadly known. Our selection is by no means exhaustive, but reflects a diverse snapshot of scenarios that we consider informative for the reader. We end with an account of future trends and perspectives. Keywords Molecular Graphics, Protein visualization, Software tools, Virtual reality Introduction Many parts of science rely on a visualization-driven cycle of experimentation, reasoning, conjecture and validation, even more so in relation with structural biology and biophysics. Molecular visualization (1) in particular is now broadly used in many contexts, with the purpose of illustration in the scientific literature or the aim to gain insight about primary research data.
    [Show full text]
  • Software and Techniques for Bio-Molecular Modelling
    Software and Techniques for Bio-Molecular Modelling Azat Mukhametov Published by Austin Publications LLC Published Date: December 01, 2016 Online Edition available at http://austinpublishinggroup.com/ebooks For reprints, please contact us at [email protected] All book chapters are Open Access distributed under the Creative Commons Attribution 4.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of the publication. Upon publication of the eBook, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work, identifying the original source. Statements and opinions expressed in the book are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Software and Techniques for Bio-Molecular Modelling | www.austinpublishinggroup.com/ebooks 1 Copyright Mukhametov A.This book chapter is open access distributed under the Creative Commons Attribution 4.0 International License, which allows users to download, copy and build upon published articles even for com- mercial purposes, as long as the author and publisher are properly credited. We consider to publish more books on the topics of drug design, molecular modelling, and structure-activity relationships.
    [Show full text]