DOCSLIB.ORG

CHARMM Force Fields, Parameterization Strategies and Future/Ongoing Force Field Developments

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
CHARMM Force Fields, Parameterization Strategies and Future/Ongoing Force Field Developments CHARMM force fields, parameterization strategies and future/ongoing force field developments Alexander D. MacKerell, Jr. University of Maryland, Baltimore School of Pharmacy MMTSB/CTBP 2006 Summer Workshop © Alexander D. MacKerell , 2006. Potential energy function (mathematical equations) Empirical force field equations and parameters relate chemical structure and conformation to energy © Alexander D. MacKerell , 2006. Common “additive” empirical force fields Class I CHARMM CHARMm (Accelrys) AMBER OPLS/AMBER/Schrödinger ECEPP (free energy force field) GROMOS Class II CFF95 (Accelrys) MM3 MMFF94 (CHARMM, Macromodel, MOE, elsewhere) UFF, DREIDING © Alexander D. MacKerell , 2006. State of the art additive force fields are typically all-atom models All atoms, including all hydrogens, explicitly represented in the model. Lone pairs included on hydrogen bond acceptors in some force fields. e.g., CHARMM22 and 27, AMBER94….03, OPLS/AA © Alexander D. MacKerell , 2006. Extended or united atom models (omit non-polar hydrogens) CHARMM PARAM19 (proteins) often used with implicit solvent models ACE, EEF, GB variants improper term to maintain chirality loss of cation - pi interactions OPLS AMBER GROMOS © Alexander D. MacKerell , 2006. Transition State Force Field Parameters Same approach as standard force field parameterization Require target data for transition state of interest: ab initio Metal Force Field Parameterization Only interaction parameters or include intramolecular terms Parameterization of QM atoms for QM/MM calculations © Alexander D. MacKerell , 2006. Polarizable “non-additive” force fields Include explicit term(s) in the potential energy function to treat induction/polarization of the charge distribution by the environment. Still under development. CHARMM Drude (MacKerell, Roux and coworkers) PIPF (Gao and coworkers) Cheq (Brooks and coworkers) AMBER Friesner/Berne et al. (Schrödinger Inc.) TINKER © Alexander D. MacKerell , 2006. Class I Additive Potential Energy Function Intramolecular (internal, bonded terms) 2 2 "Kb (b # bo ) + "K$ ($ #$o) + "K% (1+ cos(n% #&)) bonds angles torsions 2 2 + "K' (' #'o ) + "KUB (r1,3 # r1,3,o) impropers Urey#Bradley Intermolecular (external, nonbonded terms) ! 12 6 q q ,% R ( % R ( / i j + # .' min,ij * + 2' min,ij * 1 $ 4"Dr ij .' r * ' r * 1 nonbonded ij -& ij ) & ij ) 0 ! © Alexander D. MacKerell , 2006. Class II force fields (e.g. MM3, MMFF, UFF, CFF) 2 3 4 K b " b + K b " b + K b " b #[ b, 2( o) b, 3( o) b, 4( o) ] bonds 2 3 4 + K $ "$ + K $ "$ + K $ "$ #[ $ , 2( o) $ , 3( o) $ , 4( o) ] angles + #[K% ,1(1" cos%) + K% , 2(1" cos2%) + K% , 3(1" cos3%)] dihedrals 2 + #K & & impropers + # #K bb'(b " bo)(b'"bo ') + # #K$$ '($ "$ o)($ '"$ o ') bonds bonds' angles angles' + # #K b$ (b " bo)($ "$ o) bonds angles + # #(b " bo)[K% , b1 cos% + K% , b2 cos2% + K% , b3 cos3%] bonds dihedrals + # #(b'"bo ')[K% , b'1 cos% + K% , b'2 cos2% + K% , b'3 cos3%] bonds' dihedrals + # #($ "$ o)[K% ,$ 1 cos% + K% ,$ 2 cos2% + K% ,$ 3 cos3%] angles dihedrals + # # #($ "$ o)($ '"$ o ') cos% angles angles' dihedrals © Alexander D. MacKerell , 2006. ! Merck Molecular FF: Force field for drug-like molecules MMFF is a force field designed for pharmaceutical compounds as well as biological molecules. It may be considered one of the better general FFs, although its quality in treating proteins etc. is worse than CHARMM and other biological FFs. Therefore, MMFF is good for computing drug-receptor interactions but not for extensive minimizations etc. of proteins. The tutorial MMFF_Interaction gives an example of reading a drug molecule in Mol2 format, reading a protein structure and calculating the interaction energy. See mmff_inter_energy.inp © Alexander D. MacKerell , 2006. Intramolecular energy function and corresponding force field parameters 2 2 "Kb (b # bo ) + "K$ ($ #$o) + "K% (1+ cos(n% #&)) bonds angles torsions 2 2 + "K' (' #'o ) + "KUB (r1,3 # r1,3,o) + "VCMAP impropers Urey#Bradley %,( Equilibrium terms Force constants b : bonds o Kb: bonds θ : angles o Kθ: angles ! n: dihedral multiplicity Kφ: dihedral δ : dihedral phase o Kω: impropers ω : impropers o KUB: Urey-Bradley r1,3o: Urey-Bradley Aka. Internal or bonded terms © Alexander D. MacKerell , 2006. Diagram of intramolecular energy terms 2 Vbond = Kb (b " bo ) ! 1 2 Vdihedral = K" (1+ (cosn" #$)) 2 Vangle = K" (" #"o) ! 3 4 ! © Alexander D. MacKerell , 2006. 2 Vbond = Kb (b " bo ) Chemical type Kbond bo C-C 100 kcal/mole/Å2 1.5 Å C=C 200 kcal/mole/Å2 1.3 Å 2 ! C=-C 400 kcal/mole/Å 1.2 Å Bond Energy versus Bond length 400 300 Single Bond 200 Double Bond Triple Bond 100 Potential Energy, kcal/mol 0 0.5 1 1.5 2 2.5 Bond length, Å © Alexander D. MacKerell , 2006. Vdihedral = K" (1+ (cosn" #$)) Dihedral energy versus dihedral angle 20 ! 15 K=10, n=1 10 K=5, n=2 K=2.5, N=3 5 Potential Energy, kcal/mol 0 0 60 120 180 240 300 360 Dihedral Angle, degrees δ = 0˚ Note use of a Fourier series for a dihedral © Alexander D. MacKerell , 2006. 2 H Vimproper = K" (" #"o) H H! H 2 C VUrey"Bradley = KUB (r1,3 " r1,3o ) ! © Alexander D. MacKerell , 2006. 2D dihedral energy correction map to the CHARMM 22 φ,ψ backbone (CMAP) φ,ψ grid-based energy correction via bicubic interpolation i$1 j$1 4 4 & ) & ) " $ "L # $#L V CMAP = f (",#) = ,,cij ( + ( + i=1 j=1 ' %" * ' %# * Smooth first derivatives, continuous second derivatives Grid rectangle coefficients, c ! ij 1) Corner grid points H1 H8 O13 H14 " ! C4 N7 C12 C19 "f f H2 H15 " H3 C6 C9 N17 H16 2) First derivatives: , H10 O5 H20 C11 H18 "# "# 2 "f H21H22 3) Cross derivatives: "#"$ ! Use bicubic spline inte!rp olation to determine derivatives ! © Alexander D. MacKerell , 2006. Additive intermolecular energy function and corresponding parameters 12 6 q q ,% R ( % R ( / i j + # .' min,ij * + 2' min,ij * 1 $ 4"Dr ij .' r * ' r * 1 nonbonded ij -& ij ) & ij ) 0 qi: partial atomic charge D: dielectric constant ! ε: Lennard-Jones (LJ, vdW) well-depth Rmin: LJ radius (Rmin/2 in CHARMM) Combining rules (CHARMM, Amber) Rmin i,j = Rmin i + Rmin j εi,j = SQRT(εi * εj ) Aka. Nonbonded or external terms © Alexander D. MacKerell , 2006. Electrostatic energy 100 80 60 40 20 qi=1, qi=1 0 qi=1, qj=-1 0 2 4 6 8 10 -20 -40 -60 Interaction energy, kcal/mol -80 -100 Distance, Å © Alexander D. MacKerell , 2006. Treatment of hydrogen bonds??? Partial atomic charges -0.5 0.35 0.5 C O H N -0.45 © Alexander D. MacKerell , 2006. 12 6 *# R & # R & - " ,% min,ij ( ) 2% min,ij ( / ij ,% r ( % r ( / +$ ij ' $ ij ' . © Alexander D. MacKerell , 2006. ! Example of nonbond exclusions 1 2 3 4 nonbond (intermolecular) interactions between bonded atoms are treated with special rules 1,2 interactions: 0 1,3 interactions: 0 1,4 interactions: 1 or scaled > 1,4 interactions: 1 © Alexander D. MacKerell , 2006. Alternate intermolecular terms for the electrostatic (additive) or vdW interactions *$ '12 $ '10 - RHB,A# H RHB,A# H VHbond = "HB ,& ) #& ) / *cos(1A# H #D ) 0 r r Hbonds +,% A# H ( % A# H ( ./ 9 6 +$ R ' $ R ' . V = " -& min,ij ) *& min,ij ) 0 ! vdw # ij -& r ) & r ) 0 vdw ,% ij ( % ij ( / #aR 6 $ min,ij $ R ' ' & rij min,ij ) ! Vvdw = "ij e #& ) * & & r ) ) vdw % % ij ( ( © Alexander D. MacKerell , 2006. ! Limitation of additive force fields The use of Coulomb’s law with fixed atomic charges to treat the electrostatic interactions is a major simplification in current force fields. It is well known that the electron distribution of a molecule (and, thus, the atomic charges) changes as a function of the electrostatic field around the molecule. This is ignored in additive force fields. To compensate for this omission, the atomic charges are “enhanced” to mimic the polarization of molecules that occurs in a polar, condensed phase environment (e.g. aqueous solution, TIP3P water model dipole moment = 2.35 versus gas phase value of 1.85). This approximation has worked well in the current additive force fields; however, in many cases these models fail. To overcome this, next generation force fields are being developed that explicitly treat electronic polarization. © Alexander D. MacKerell , 2006. Methods to include electronic polarization in force fields Fluctuating charge (CHEQ) Induced dipoles (PIPF, Berne/Friesner, AMBER) Classical Drude Oscillator All methods require that the perturbation of the electronic distribution due to the surrounding electrostatic field be optimized in an iterative fashion. This is due to the change in the “charge distribution” of a system leading to a new electrostatic field which then requires additional re-adjustment of the charge distribution (SCF: self-consistent field calculation). Matrix diagonalization may also be used, but is frequently inaccessible due to the large number of atoms in biological systems. In the end the need to perform an SCF calculation leads to a large increase in computational demands. Special methods to minimize this limitation in MD simulations have been developed (see below). © Alexander D. MacKerell , 2006. Fluctuating Charge Model (CHEQ) Polarization is based on the movement of charge, q, between bonded atoms i and j in response to the surrounding electrostatic field. The extent of charge movement is based on the relative electronegativity, χ, and hardness, J, of the bonded atoms. The electrostatic energy is then obtained from the Coulombic interactions between the relaxed charges. 1 V(q ) = " q + J q2 ij ij ij 2 ij ij ' ' ' ' ' " ij = " i + " j Jij = Ji + J j + 2Jij Electrone!g ativity: attraction of an atom for electrons Hardness: work needed to transfer charge (resistance to charge movement) ! ! © Alexander D. MacKerell , 2006. Induced Dipole Model Each atom, i, carries a charge, qi, and a dipole moment, µi, such that electrostatic interactions between atoms i and j include: charge-charge interactions: 1/rij 2 charge-dipole interactions: 1/rij 3 dipole-dipole interactions: 1/rij Polarization included via relaxation of dipole moments in the electrostatic field, Ei, where αi is the polarizability of atom i % ( 0 induced 0 µi = " i (E i + E i ) = " i' E i + $Tijµ j * & i# j ) © Alexander D.
Load more

Recommended publications
  • BOSS, Version 4.6 Biochemical and Organic Simulation System User’S Manual for UNIX, Linux, and Windows
    BOSS, Version 4.6 Biochemical and Organic Simulation System User’s Manual for UNIX, Linux, and Windows William L. Jorgensen Department of Chemistry, Yale University P. O. Box 208107 New Haven, Connecticut 06520-8107 Phone: (203) 432-6278 Fax: (203) 432-6299 Internet: [email protected] January 2004 Contents Page Introduction 4 1 Can’t Wait to Start – Use the x Scripts 6 2 Statistical Mechanics Simulation – Theory 6 3 Energy and Free Energy Evaluation 7 4 New Features 9 5 Operating Systems 14 6 Installation 14 7 Files 14 8 Command or bat File Input 16 9 Parameter File Input 18 10 Z-matrix File Input 26 10.1 Atom Input 29 10.2 Geometry Variations 29 10.3 Bond Length Variations 29 10.4 Additional Bonds 30 10.5 Harmonic Restraints 30 10.6 Bond Angle Variations 30 10.7 Additional Bond Angles 31 10.8 Dihedral Angle Variations 31 10.9 Additional Dihedral Angles 33 10.10 Domain Definitions 34 10.11 Conformational Searching 34 10.12 Sample Z-matrix 34 10.13 Z-matrix Input for Custom Solvents 35 11 PDB Input 37 12 Coordinate Input in Mind Format and Reaction Path Following 38 13 Pure Liquid Simulations 39 14 Cluster Simulations 39 2 15 Solventless and Molecular Mechanics Calculations 40 15.1 Continuum Simulations 40 15.2 Energy Minimizations 41 15.3 Dihedral Angle Driving 42 15.4 Potential Surface Scanning 42 15.5 Normal Coordinate Analysis 43 15.6 Conformational Searching 45 16 Available Solvent Boxes 48 17 Ewald Summation for Long-Range Electrostatics 50 18 Test Jobs 51 19 Output 56 19.1 Some Variable Definitions 58 20 Contents of the Distribution Files 59 21 Appendix – No.
    [Show full text]
  • Macromodel Quick Start Guide
    MacroModel Quick Start Guide MacroModel 9.9 Quick Start Guide Schrödinger Press MacroModel Quick Start Guide Copyright © 2012 Schrödinger, LLC. All rights reserved. While care has been taken in the preparation of this publication, Schrödinger assumes no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein. BioLuminate, Canvas, CombiGlide, ConfGen, Epik, Glide, Impact, Jaguar, Liaison, LigPrep, Maestro, Phase, Prime, PrimeX, QikProp, QikFit, QikSim, QSite, SiteMap, Strike, and WaterMap are trademarks of Schrödinger, LLC. Schrödinger and MacroModel are registered trademarks of Schrödinger, LLC. MCPRO is a trademark of William L. Jorgensen. DESMOND is a trademark of D. E. Shaw Research, LLC. Desmond is used with the permission of D. E. Shaw Research. All rights reserved. This publication may contain the trademarks of other companies. Schrödinger software includes software and libraries provided by third parties. For details of the copyrights, and terms and conditions associated with such included third party software, see the Legal Notices, or use your browser to open $SCHRODINGER/docs/html/third_party_legal.html (Linux OS) or %SCHRODINGER%\docs\html\third_party_legal.html (Windows OS). This publication may refer to other third party software not included in or with Schrödinger software ("such other third party software"), and provide links to third party Web sites ("linked sites"). References to such other third party software or linked sites do not constitute an endorsement by Schrödinger, LLC or its affiliates. Use of such other third party software and linked sites may be subject to third party license agreements and fees. Schrödinger, LLC and its affiliates have no responsibility or liability, directly or indirectly, for such other third party software and linked sites, or for damage resulting from the use thereof.
    [Show full text]
  • CORINA Classic Program Manual
    CORINA Classic Generation of Three-Dimensional Molecular Models Version 4.4.0 Program Description Molecular Networks GmbH September 2021 www.mn-am.com Molecular Networks GmbH Altamira LLC Neumeyerstraße 28 470 W Broad St, Unit #5007 90411 Nuremberg Columbus, OH 43215 Germany USA mn-am.com This document is copyright © 1998-2021 by Molecular Networks GmbH Computerchemie and Altamira LLC. All rights reserved. Except as permitted under the terms of the Software Licensing Agreement of Molecular Networks GmbH Computerchemie, no part of this publication may be reproduced or distributed in any form or by any means or stored in a database retrieval system without the prior written permission of Molecular Networks GmbH or Altamira LLC. The software described in this document is furnished under a license and may be used and copied only in accordance with the terms of such license. (Document version: 4.4.0-2021-09-30) Content Content 1 Introducing CORINA Classic 1 1.1 Objective of CORINA Classic 1 1.2 CORINA Classic in Brief 1 2 Release Notes 3 2.1 CORINA (Full Version) 3 2.2 CORINA_F (Restricted FlexX Interface Version) 25 3 Getting Started with CORINA Classic 26 4 Using CORINA Classic 29 4.1 Synopsis 29 4.2 Options 29 5 Use Cases of CORINA Classic 60 6 Supported File Formats and Interfaces 64 6.1 V2000 Structure Data File (SD) and Reaction Data File (RD) 64 6.2 V3000 Structure Data File (SD) and Reaction Data File (RD) 67 6.3 SMILES Linear Notation 67 6.4 InChI file format 69 6.5 SYBYL File Formats 70 6.6 Brookhaven Protein Data Bank Format (PDB)
    [Show full text]
  • 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.
    [Show full text]
  • Chem3d 17.0 User Guide Chem3d 17.0
    Chem3D 17.0 User Guide Chem3D 17.0 Table of Contents Recent Additions viii Chapter 1: About Chem3D 1 Additional computational engines 1 Serial numbers and technical support 3 About Chem3D Tutorials 3 Chapter 2: Chem3D Basics 5 Getting around 5 User interface preferences 9 Background settings 10 Sample files 10 Saving to Dropbox 10 Chapter 3: Basic Model Building 12 Default settings 12 Selecting a display mode 12 Using bond tools 13 Using the ChemDraw panel 15 Using other 2D drawing packages 15 Building from text 16 Adding fragments 18 Selecting atoms and bonds 18 Atom charges 21 Object position 23 Substructures 24 Refining models 27 Copying and printing 29 Finding structures online 32 Chapter 4: Displaying Models 35 © Copyright 1998-2017 PerkinElmer Informatics Inc., All rights reserved. ii Chem3D 17.0 Display modes 35 Atom and bond size 37 Displaying dot surfaces 38 Serial numbers 38 Displaying atoms 39 Atom symbols 40 Rotating models 41 Atom and bond properties 44 Showing hydrogen bonds 45 Hydrogens and lone pairs 46 Translating models 47 Scaling models 47 Aligning models 47 Applying color 49 Model Explorer 52 Measuring molecules 59 Comparing models by overlay 62 Molecular surfaces 63 Using stereo pairs 72 Stereo enhancement 72 Setting view focus 73 Chapter 5: Building Advanced Models 74 Dummy bonds and dummy atoms 74 Substructures 75 Bonding by proximity 78 Setting measurements 78 Atom and building types 81 Stereochemistry 85 © Copyright 1998-2017 PerkinElmer Informatics Inc., All rights reserved. iii Chem3D 17.0 Building with Cartesian
    [Show full text]
  • Molecular Modeling: a Powerful Tool for Drug Design and Molecular Docking
    GENERAL I ARTICLE Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking Rama Rao Nadendla Molecular modeling has become a valuable and essential tool to medicinal chemists in the drug design process. Molecular modeling describes the generation, manipula­ tion or representation of three-dimensional structures of molecules and associated physico-chemical properties. It involves a range of computerized techniques based on theoretical chemistry methods and experimental data to predict molecular and biological properties. Depending on Rama Rao Nadendla has the context and the rigor, the subject is often referred to as been working in the 'molecular graphics', 'molecular visualizations', 'computa­ KVSR College of tional chemistry', or 'computational quantum chemistry'. Pharmaceutical Sciences, The molecular modeling techniques are derived from the Vijaywada as a Professor concepts of molecular orbitals of Huckel, Mullikan and of pharmaceutical chemistry. He is involved 'classical mechanical programs' of Westheimer, Wiberg in the synthesis of new and Boyd. biodynamic agents. He also has authored three 1. Why Modeling and Molecular Modeling? books on pharmaceutical organic chemistry and medicinal chemistry. Modeling is a tool for doing chemistry. Models are central for understanding of chemistry. Molecular modeling allows us to do and teach chemistry better by providing better tools for investi­ gating, interpreting, explaining and discovering new phenom­ ena. Like experimental chemistry, it is a skill-demanding sci­ ence and must be learnt by doing and not just reading. Molecular modeling is easy to perform with currently available software, but the difficulty lies in getting the right model and proper interpretation. 2. Molecular Modeling Tools Keywords Molecular modeling, molecu­ The tools of the trade have gradually evolved from physical lar docking, drug design, com­ putational chemistry, molecu­ models (Dreiding, CPK, etc.) and calculators, including the use lar visulatization.
    [Show full text]
  • “One Ring to Rule Them All”
    OpenMM library “One ring to rule them all” https://simtk.org/home/openmm CHARMM * Abalone Presto * ACEMD NAMD * ADUN * Ascalaph Gromacs AMBER * COSMOS ??? HOOMD * Desmond * Culgi * ESPResSo Tinker * GROMOS * GULP * Hippo LAMMPS * Kalypso MD * LPMD * MacroModel * MDynaMix * MOLDY * Materials Studio * MOSCITO * ProtoMol The OpenM(olecular)M(echanics) API * RedMD * YASARA * ORAC https://simtk.org/home/openmm * XMD Goals of OpenMM l Complete library l provide what is most needed l easy to learn and use l Fast, general, extensible l optimize for speed l hide hardware specifics l support new hardware l add new force fields, integration methods etc. l Available APIs in C++, Fortran95, Python l Advantages l Object oriented l Modular l Extensible l Disadvantages l Programs written in other languages need to invoke it through a layer of C++ code Features • Electrostatics: cut-off, Ewald, PME • Implicit solvent • Integrators: Verlet, Langevin, Brownian, custom • Thermostat: Andersen • Barostat: MonteCarlo • Others: energy minimization, virtual sites 5 The OpenMM Architecture Public Interface OpenMM Public API Platform Independent Code OpenMM Implementation Layer Platform Abstraction Layer OpenMM Low Level API Computational Kernels CUDA/OpenCL/Brook/MPI etc. Public API Classes (1) l System l A collection of interaction particles l Defines the mass of each particle (needed for integration) l Specifies distance restraints l Contains a list of Force objects that define the interactions l OpenMMContext l Contains all state information for a particular simulation − Positions, velocities, other parmeters Public API Classes (2) l Force l Anything that affects the system's behavior: forces, barostats, thermostats, etc. l A Force may: − Apply forces to particles − Contribute to the potential energy − Define adjustable parameters − Modify positions, velocities, and parameters at the start of each time step l Existing Force subclasses − HarmonicBond, HarmonicAngle, PeriodicTorsion, RBTorsion, Nonbonded, GBSAOBC, AndersenThermostat, CMMotionRemover..
    [Show full text]
  • Chemistry Packages at CHPC
    Chemistry Packages at CHPC Anita M. Orendt Center for High Performance Computing [email protected] Fall 2014 Purpose of Presentation • Identify the computational chemistry software and related tools currently available at CHPC • Present brief overview of these packages • Present how to access packages on CHPC • Information on usage of Gaussian09 http://www.chpc.utah.edu Ember Lonepeak /scratch/lonepeak/serial 141 nodes/1692 cores 16 nodes/256 cores Infiniband and GigE Large memory, GigE General 70 nodes/852 cores 12 GPU nodes (6 General) Kingspeak 199 nodes/4008 cores Ash cluster (417 nodes) Infiniband and GigE Switch General 44 nodes/832 cores Apex Arch Great Wall PFS Telluride cluster (93 nodes) /scratch/ibrix meteoXX/atmosXX nodes NFS Home NFS Administrative Directories & /scratch/kingspeak/serial Group Nodes Directories 10/1/14 http://www.chpc.utah.edu Slide 3 Brief Overview CHPC Resources • Computational Clusters – kingspeak, ember – general allocation and owner-guest on owner nodes – lonepeak – no allocation – ash and telluride – can run as smithp-guest and cheatham-guest, respectively • Home directory – NFS mounted on all clusters – /uufs/chpc.utah.edu/common/home/<uNID> – generally not backed up (there are exceptions) • Scratch systems – /scratch/ibrix/chpc_gen – kingspeak, ember, ash, telluride – 56TB – /scratch/kingspeak/serial – kingspeak, ember, ash – 175TB – /scratch/lonepeak/serial – lonepeak – 33 TB – /scratch/local on compute nodes • Applications – /uufs/chpc.utah.edu/sys/pkg (use for lonepeak, linux desktops if chpc
    [Show full text]
  • Organic & Biomolecular Chemistry
    Organic & Biomolecular Chemistry Accepted Manuscript This is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. Accepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available. You can find more information about Accepted Manuscripts in the Information for Authors. Please note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. www.rsc.org/obc Page 1 of 6 CREATED USING THE RSC ARTICLEOrganic TEMPLATE & Biomolecular (VER. 3.0 OOo) - SEE WWW.RSC.ORG/ELECTRONICFILESChemistry FOR DETAILS www.rsc.org/xxxxxx | XXXXXXXX Expanding DP4: Application to drug compounds and automation Kristaps Ermanis,a Kevin E. B. Parkes,b Tatiana Agbackb and Jonathan M. Goodman*c Received (in XXX, XXX) Xth XXXXXXXXX 200X, Accepted Xth XXXXXXXXX 200X First published on the web Xth XXXXXXXXX 200X DOI: 10.1039/b00000000x The DP4 parameter, which provides a confidence level for NMR assignment, has been widely used to help assign the structures of many stereochemically-rich molecules.
    [Show full text]
  • Firstdiscovery3.0
    FirstDiscovery 3.0 Quick Start Guide Copyright © 2004 Schrödinger, LLC. All rights reserved. Schrödinger, FirstDiscovery, Glide, Impact, Jaguar, Liaison, LigPrep, Maestro, Prime, QSite, and QikProp are trademarks of Schrödinger, LLC. MacroModel is a registered trademark of Schrödinger, LLC. To the maximum extent permitted by applicable law, this publication is provided “as is” without warranty of any kind. This publication may contain trademarks of other companies. Revision A, June 2004 Contents Chapter 1: Document Overview..........................................................................1 Chapter 2: The FirstDiscovery Suite ..................................................................3 Chapter 3: Introduction to Maestro ...................................................................5 3.1 General Interface Behavior ..................................................................................5 3.2 Starting Maestro...................................................................................................5 3.3 The Maestro Main Window .................................................................................6 3.3.1 The Menu Bar ..........................................................................................7 3.3.2 The Toolbar ..............................................................................................8 3.3.3 Mouse Functions in the Workspace .......................................................11 3.3.4 Shortcut Key Combinations ...................................................................11
    [Show full text]
  • Macromodel Faqs
    MacroModel FAQs 1. What is the MacroModel product suite and how will it help my research? 2. What is the structure of MacroModel? 3. What is Maestro? 4. What is the latest version of MacroModel? 5. Under what hardware platforms and operating systems can current version of MacroModel be used? 6. Can I use a Macintosh or Windows PC as a display for MacroModel? 7. What structure file formats can be used with the MacroModel package? 8. How do I find information about atomic charges used in MacroModel calculations? 9. MacroModel contains a variety of force fields. Which is best for my purpose? 10. How can I tell what force field parameters were used in a particular simulation? 11. I need to add parameters to MacroModel. How is this done? 12. When performing a conformational search, how do I judge whether the search has covered the complete conformation space? 13. How do I set up Jumping Between Wells (JBW) or Free Energy Perturbation (FEP) computa- tions with MacroModel? 14. What is XCluster and how can it help me in my research? MacroModel FAQs What is the MacroModel product suite and how will it help my research? MacroModel is a premier molecular mechanics and modeling software package that consists of the Maestro graphical user interface, the BatchMin molecular mechanical computational engine, and the XCluster and MINTA analysis modules. The Maestro interface provides easy-to-use tools for building and manipulating both simple and complex chemical structures, and the BatchMin computational engine contains powerful algorithms for performing conformational searches and free energy simulations.
    [Show full text]
  • EMERSON Centernewsletter
    EMERSON CENTER Newsletter A Publication of the Cherry L. Emerson Center for Scientific Computation, Emory University http://www.emerson.emory.edu Volume 8, September 15, 2001 COMPUTATIONAL CHEMIST JAMES KINDT Inside This Issue . JOINS EMERSON CENTER ✾ New Professor & User to EC (p. 1) ✾ The Emerson Center welcomes Dr. James Kindt, who has recently joined the Department New EC Equipment Purchase of Chemistry as an Assistant Professor and a new subscriber to the Emerson Center. His (p. 1) office and laboratory are located in the Emerson ✾ Emerson Center Fee Change (p. 1) Center on the 5th floor of the Cherry Logan ✾ ECEC Meeting Minutes (p. 1) Emerson Hall. Prof. Kindt’s specialty is ✾ computational chemistry, in particular, modeling EC Visiting Fellowship Announce- of biomolecular systems. He says that his primary ment & Letters from Fellows (p. 2) research goal will be to explore, by computer ✾ Research Reports from Emerson simulation and theory, how lipid composition and Ctr. (p. 3) molecular structure contribute to the organization ✾ Technical Specs on EC Hardware and structure of lipid bilayers. He will be using (p. 4) Emerson Center’s computational and graphic ✾ facilities extensively for his research. He recently Emerson Center Contact Info received a prestigious New Faculty Award from (p. 4) the Camille and Henry Dreyfus Foundation. Prof. Professor James T. Kindt Kindt received his PhD from Yale University and was a postdoctoral fellow at UCLA before joining Emory. Please refer to page 3 of this newsletter for one of Prof. Kindt’s research proposals using the Emerson Center facilities. New Biomolecular Modeling & Visualization Facility at EC In the News In response to popular demand from the biomolecular modeling community at Emory and with grant support from the National Science Foundation, the Emerson Center ◆ Emerson Center Fee recently established its new Biomolecular Modeling and Visualization Facility.
    [Show full text]