Application of Molecular Dynamics Simulation to Small Systems
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MODELLER 10.1 Manual
MODELLER A Program for Protein Structure Modeling Release 10.1, r12156 Andrej Saliˇ with help from Ben Webb, M.S. Madhusudhan, Min-Yi Shen, Guangqiang Dong, Marc A. Martı-Renom, Narayanan Eswar, Frank Alber, Maya Topf, Baldomero Oliva, Andr´as Fiser, Roberto S´anchez, Bozidar Yerkovich, Azat Badretdinov, Francisco Melo, John P. Overington, and Eric Feyfant email: modeller-care AT salilab.org URL https://salilab.org/modeller/ 2021/03/12 ii Contents Copyright notice xxi Acknowledgments xxv 1 Introduction 1 1.1 What is Modeller?............................................. 1 1.2 Modeller bibliography....................................... .... 2 1.3 Obtainingandinstallingtheprogram. .................... 3 1.4 Bugreports...................................... ............ 4 1.5 Method for comparative protein structure modeling by Modeller ................... 5 1.6 Using Modeller forcomparativemodeling. ... 8 1.6.1 Preparinginputfiles . ............. 8 1.6.2 Running Modeller ......................................... 9 2 Automated comparative modeling with AutoModel 11 2.1 Simpleusage ..................................... ............ 11 2.2 Moreadvancedusage............................... .............. 12 2.2.1 Including water molecules, HETATM residues, and hydrogenatoms .............. 12 2.2.2 Changing the default optimization and refinement protocol ................... 14 2.2.3 Getting a very fast and approximate model . ................. 14 2.2.4 Building a model from multiple templates . .................. 15 2.2.5 Buildinganallhydrogenmodel -
User Guide of Computational Facilities
Physical Chemistry Unit Departament de Quimica User Guide of Computational Facilities Beta Version System Manager: Marc Noguera i Julian January 20, 2009 Contents 1 Introduction 1 2 Computer resources 2 3 Some Linux tools 2 4 The Cluster 2 4.1 Frontend servers . 2 4.2 Filesystems . 3 4.3 Computational nodes . 3 4.4 User’s environment . 4 4.5 Disk space quota . 4 4.6 Data Backup . 4 4.7 Generation of SSH keys for automatic SSH login . 4 4.8 Submitting jobs to the cluster . 5 4.8.1 Typical queue system commands . 6 4.8.2 HomeMade scripts . 6 4.8.3 Create your own submit script . 6 4.8.4 Submitting Parallel Calculations . 7 5 Available Software 9 5.1 Chemisty software . 9 5.2 Development Software . 10 5.3 How to use the software . 11 5.4 Non-default environments . 11 6 Your Linux Workstation 11 6.1 Disk space on your workstation . 12 6.2 Workstation Data Backup . 12 6.3 Running virtual Windows XP . 13 6.3.1 The Windows XP Environment . 13 6.4 Submitting calculations to your dekstop . 13 6.5 Network dependent structure . 14 7 Your WindowsXP Workstation 14 7.1 Workstation Data Backup . 14 8 Frequently asked questions 14 1 Introduction This User Guide is aimed to the standard user of the computer facilities in the ”Unitat de Quimica Fisica” in the Universitat Autnoma de Barcelona. It is not assumed that you have a knowledge of UNIX/Linux. However, you are 1 encouraged to take a close look to the linux guides that will be pointed out. -
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
processes Review Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development Outi M. H. Salo-Ahen 1,2,* , Ida Alanko 1,2, Rajendra Bhadane 1,2 , Alexandre M. J. J. Bonvin 3,* , Rodrigo Vargas Honorato 3, Shakhawath Hossain 4 , André H. Juffer 5 , Aleksei Kabedev 4, Maija Lahtela-Kakkonen 6, Anders Støttrup Larsen 7, Eveline Lescrinier 8 , Parthiban Marimuthu 1,2 , Muhammad Usman Mirza 8 , Ghulam Mustafa 9, Ariane Nunes-Alves 10,11,* , Tatu Pantsar 6,12, Atefeh Saadabadi 1,2 , Kalaimathy Singaravelu 13 and Michiel Vanmeert 8 1 Pharmaceutical Sciences Laboratory (Pharmacy), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland; ida.alanko@abo.fi (I.A.); rajendra.bhadane@abo.fi (R.B.); parthiban.marimuthu@abo.fi (P.M.); atefeh.saadabadi@abo.fi (A.S.) 2 Structural Bioinformatics Laboratory (Biochemistry), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland 3 Faculty of Science-Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, 3584 CH Utrecht, The Netherlands; [email protected] 4 Swedish Drug Delivery Forum (SDDF), Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden; [email protected] (S.H.); [email protected] (A.K.) 5 Biocenter Oulu & Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7 A, FI-90014 Oulu, Finland; andre.juffer@oulu.fi 6 School of Pharmacy, University of Eastern Finland, FI-70210 Kuopio, Finland; maija.lahtela-kakkonen@uef.fi (M.L.-K.); tatu.pantsar@uef.fi -
Parameterizing a Novel Residue
University of Illinois at Urbana-Champaign Luthey-Schulten Group, Department of Chemistry Theoretical and Computational Biophysics Group Computational Biophysics Workshop Parameterizing a Novel Residue Rommie Amaro Brijeet Dhaliwal Zaida Luthey-Schulten Current Editors: Christopher Mayne Po-Chao Wen February 2012 CONTENTS 2 Contents 1 Biological Background and Chemical Mechanism 4 2 HisH System Setup 7 3 Testing out your new residue 9 4 The CHARMM Force Field 12 5 Developing Topology and Parameter Files 13 5.1 An Introduction to a CHARMM Topology File . 13 5.2 An Introduction to a CHARMM Parameter File . 16 5.3 Assigning Initial Values for Unknown Parameters . 18 5.4 A Closer Look at Dihedral Parameters . 18 6 Parameter generation using SPARTAN (Optional) 20 7 Minimization with new parameters 32 CONTENTS 3 Introduction Molecular dynamics (MD) simulations are a powerful scientific tool used to study a wide variety of systems in atomic detail. From a standard protein simulation, to the use of steered molecular dynamics (SMD), to modelling DNA-protein interactions, there are many useful applications. With the advent of massively parallel simulation programs such as NAMD2, the limits of computational anal- ysis are being pushed even further. Inevitably there comes a time in any molecular modelling scientist’s career when the need to simulate an entirely new molecule or ligand arises. The tech- nique of determining new force field parameters to describe these novel system components therefore becomes an invaluable skill. Determining the correct sys- tem parameters to use in conjunction with the chosen force field is only one important aspect of the process. -
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. -
Computational Chemistry (F14CCH)
Computational Chemistry (F14CCH) Connecting to Remote Machines Using CCP1GUI CONDOR is a queuing system that can be accessed from the Linux Left Mouse Button: Turn machines of the theoretical research groups and distributes the Hold right + up or down: Zoom submitted jobs to free compute nodes. Since the machines are protected Hold wheel + move: Move by firewalls you have to connect to a specific node, Porthos, on which you were given an account. Click Atom => Select Fragment => Add Assign all elements, also the hydrogens, before creating the GAMESS Use PuTTY to connect to remote machines, porthos in this case. Open input file (click on “All X => H” in the tool panel). If you cannot see one of putty.exe, enter the hostname as porthos.chem.nott.ac.uk. The login the windows of CCP1GUI, it might be hiding outside the desktop area. is your university username and the default password is Right click on the taskbar icon => Move => hold cursor keys to the left ChangeMeSoon. When you first log in on CONDOR you must change until the window appears. your password using kpasswd! It must be strong, including mixed case letters and numbers. Creating a GAMESS Input File / Running a Local Job Compute => GAMESS-UK Copying Files from/to Porthos To exchange files with porthos in order to submit files to CONDOR for Molecule: Options => Title calculation or copy results back, you first have to copy them from the Task => select requested task Windows machine to porthos via the SSHClient. It cannot be installed in Theory: Select SCF Method (and post SCF Method, if required) the CAL but can be accessed at NAL => Accessing the Internet => Optimisation: Runtype => Opt. -
Molecular Simulation and Structure Prediction Using CHARMM and the MMTSB Tool Set Introduction
Molecular simulation and structure prediction using CHARMM and the MMTSB Tool Set Introduction Charles L. Brooks III MMTSB/CTBP 2006 Summer Workshop MMTSB/CTBP Summer Workshop © Charles L. Brooks III, 2006. CTBP and MMTSB: Who are we? • The CTBP is the Center for Theoretical Biological Physics – Funded by the NSF as a Physics Frontiers Center – Partnership between UCSD, Scripps and Salk, lead by UCSD • The CTBP encompasses a broad spectrum of research and training activities at the forefront of the biology- physics interface. – Principal scientists include • José Onuchic, Herbie Levine, Henry Abarbanel, Charles Brooks, David Case, Mike Holst, Terry Hwa, David Kleinfeld, Andy McCammon, Wouter Rappel, Terry Sejnowski, Wei Wang, Peter Wolynes MMTSB/CTBP Summer Workshop © Charles L. Brooks III, 2006. CTBP and MMTSB: Who are we? MMTSB/CTBP Summer Workshop http://ctbp.ucsd.edu © Charles L. Brooks III, 2006. CTBP and MMTSB: Who are we? • The MMTSB is the Center for Multi-scale Modeling Tools for Structural Biology – Funded by the NIH as a National Research Resource Center – Partnership between Scripps and Georgia Tech, lead by Scripps • The MMTSB aims to develop new tools and theoretical models to aid molecular and structural biologists in interpreting their biological data. – Principal scientists include • Charles Brooks, David Case, Steve Harvey, Jack Johnson, Vijay Reddy, Jeff Skolnick MMTSB/CTBP Summer Workshop © Charles L. Brooks III, 2006. CTBP and MMTSB: Who are we? http://mmtsb.scripps.edu MMTSB/CTBP Summer Workshop © Charles L. Brooks III, 2006. CTBP and MMTSB: Who are we? • Activities – Fundamental research across a broad spectrum – Software and methods development and distribution • MMTSB distributes multiple software packages as well as hosts a variety of web services and databases – Training and research workshops and educational outreach • Both centers have extensive workshop programs – Visitors • Both centers host visitors and collaborators for short and longer term (sabbatical) visits MMTSB/CTBP Summer Workshop © Charles L. -
Trends in Atomistic Simulation Software Usage [1.3]
A LiveCoMS Perpetual Review Trends in atomistic simulation software usage [1.3] Leopold Talirz1,2,3*, Luca M. Ghiringhelli4, Berend Smit1,3 1Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingenierie Chimiques, Valais, École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland; 2Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 3National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 4The NOMAD Laboratory at the Fritz Haber Institute of the Max Planck Society and Humboldt University, Berlin, Germany This LiveCoMS document is Abstract Driven by the unprecedented computational power available to scientific research, the maintained online on GitHub at https: use of computers in solid-state physics, chemistry and materials science has been on a continuous //github.com/ltalirz/ rise. This review focuses on the software used for the simulation of matter at the atomic scale. We livecoms-atomistic-software; provide a comprehensive overview of major codes in the field, and analyze how citations to these to provide feedback, suggestions, or help codes in the academic literature have evolved since 2010. An interactive version of the underlying improve it, please visit the data set is available at https://atomistic.software. GitHub repository and participate via the issue tracker. This version dated August *For correspondence: 30, 2021 [email protected] (LT) 1 Introduction Gaussian [2], were already released in the 1970s, followed Scientists today have unprecedented access to computa- by force-field codes, such as GROMOS [3], and periodic tional power. -
Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens
International Journal of Molecular Sciences Review Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens Anna Helena Mazurek 1 , Łukasz Szeleszczuk 1,* , Thomas Simonson 2 and Dariusz Maciej Pisklak 1 1 Chair and Department of Physical Pharmacy and Bioanalysis, Department of Physical Chemistry, Medical Faculty of Pharmacy, University of Warsaw, Banacha 1 str., 02-093 Warsaw Poland; [email protected] (A.H.M.); [email protected] (D.M.P.) 2 Laboratoire de Biochimie (CNRS UMR7654), Ecole Polytechnique, 91-120 Palaiseau, France; [email protected] * Correspondence: [email protected]; Tel.: +48-501-255-121 Received: 21 July 2020; Accepted: 1 September 2020; Published: 3 September 2020 Abstract: In this review, applications of various molecular modelling methods in the study of estrogens and xenoestrogens are summarized. Selected biomolecules that are the most commonly chosen as molecular modelling objects in this field are presented. In most of the reviewed works, ligand docking using solely force field methods was performed, employing various molecular targets involved in metabolism and action of estrogens. Other molecular modelling methods such as molecular dynamics and combined quantum mechanics with molecular mechanics have also been successfully used to predict the properties of estrogens and xenoestrogens. Among published works, a great number also focused on the application of different types of quantitative structure–activity relationship (QSAR) analyses to examine estrogen’s structures and activities. Although the interactions between estrogens and xenoestrogens with various proteins are the most commonly studied, other aspects such as penetration of estrogens through lipid bilayers or their ability to adsorb on different materials are also explored using theoretical calculations. -
CHARMM WORKSHOP 1.0 1. Introduction 2. Help
CHARMM WORKSHOP 1.0 Arjan van der Vaart Department of Chemistry University of South Florida [email protected] 1. Introduction CHARMM (Chemistry at HARvard Macromolecular Mechanics) is a computer program for the simulation of biomolecular systems. Initial development of the program started in the early 1970's in the lab of Prof. Karplus at Harvard University, leading to the first molecular dynamics study of a protein (McCammon, Gelin, and Karplus, Nature 267, 585 (1977)). Today, more than 20 groups worldwide work on the maintenance and further development of the program. Important features of the program are: 1. It is largely self-contained The setup, actual calculations, and analysis are all done by the same program. 2. It is fairly complete Most simulation techniques, force fields, and analysis tools pertinent to biomolecules are part of the CHARMM program. 3. The CHARMM interface works like a programming language Commands resemble the Fortran programming language, various mathematical manipulations on a selected set of internal and external variables are possible, and commands can include loop structures. This workshop will provide a short introduction to the CHARMM program. After the workshop, participants should be able to setup, execute, and analyze standard simulation protocols. 2. Help In the 1970's the working name for the CHARMM program was HARMM (HARvard Macromolecular Mechanics). This name should serve as a warning that CHARMM may be daunting and/or frustrating for users. The program has many options and features; making it a powerful and flexible tool on the one hand, and a difficult program to use on the other. -
Autodock 3 User's Guide
User’s Guide AutoDock Automated Docking of Flexible Ligands to Receptors 3 Version 3.0.5 Garrett M. Morris David S. Goodsell Ruth Huey William E. Hart Scott Halliday Rik Belew Arthur J. Olson 2 Important AutoDock is distributed free of charge for academic and non-commercial use. There are some caveats, however. Firstly, since we do not receive funding to support the academic community of users, we cannot guarantee rapid (or even slow) response to queries on installation and use. While there is documentation, it may require at least some basic Unix abilities to install. If you need more support for the AutoDock code, a commercial version (with support) is available from Oxford Molecular (http://www.oxmol.com). If you can’t afford support, but still need help: (1) Ask your local system administrator or programming guru for help about compiling, using Unix/Linux, etc.. (2) Consult the AutoDock web site, where you will find a wealth of information and a FAQ (Frequently Asked Questions) page with answers on AutoDock: http://www.scripps.edu/pub/olson-web/doc/autodock/ (3) If you can’t find the answer to your problem, send your question to the Computational Chemistry List (CCL). There are many seasoned users of computational chemistry software and some AutoDock users who may already know the answer to your question. You can find out more about the CCL on the web, at: http://ccl.osc.edu/ccl/welcome.html (4) If you have tried (1), (2) and (3), and you still cannot find an answer, send email to [email protected] for questions about AutoGrid or AutoDock; or to [email protected], for questions about AutoTors. -
New LAMMPS Modules for the Simulation of Protein-Surface
New LAMMPS Modules for the Simulation of Prof. Robert A. Latour, Department of Bioengineering, Clemson University, Clemson, SC Group Members: T. Abramyan, J. Snyder, J. Yancey (Bioengr.), Prof. S.J. Stuart, D. Hyde-Volpe (Chemistry) Protein-Surface Interactions with CHARMM Collaborative Support: Dr. Chris Lorenz, Physics Dept., King’s College-London Introduction Objective Utility Files to Facilitate IFF Parameter Adjustment Development of these capabilities in LAMMPS: Text file to facilitate modification of default CHARMM parameters to Protein-surface interactions important for broad range . Modules to incorporate an interfacial force field including define new IFF parameters: of application in bioengineering and biotechnology. both L-J and partial charge parameter sets [1]. • Section I.A to modify L-J e and s for existing Atom Types Simulations of protein-surface interactions require: . New fix_cmap module for CHARMM CMAP parameters • Section I.B for creation of new Atom Types . Force fields for protein, surface, and interface . Modules for TIGER2 and TIGER2A advance sampling [3,4]. Advanced sampling for ensemble avg. properties • Section II to modify partial charges for Atoms The Latour group previously developed these • Section III providing list of all atoms and associations capabilities for use with the CHARMM simulation LAMMPS Modules: Perl script to update LAMMPS data files with IFF parameters program [1-4]. Modified LAMMPS data file format to include IFF partial Independent Force Fields for Each Phase of System charge in Atoms section. Perl scripts to convert CHARMM and LAMMPS regular data Interfacial force field files into IFF-formatted LAMMPS data files. (IFF) to separately represent protein- IFF-Formatted LAMMPS Data File with qiff Column surface interactions (both Lennard-Jones q X Y Z qiff (e, s) and partial charge (q) parameters [1].