Ned H' Martin

1
Enhancing ComputationalCapabilities in Chemistry
(and Grid Computing) at UNCW

• Ned H. Martin
• Department of Chemistry and Biochemistry
• University of North Carolina Wilmington

Duke University, April 18, 2005
2
Outline, Part 1

• Culture of technology use in Chemistry at UNCW
• Grants that provided necessary infrastructure
• Phase I of Integrating Modeling into Curriculum
  Goals and Strategy
• Selective Integration of Modeling into most
  promising course / instructor combinations to
  enhance students 3D perceptions.
• Demonstration of benefits (to win support of
  faculty).
• Phase II of Integrating Modeling into Curriculum
• Expand to other courses in chemistry.
• Current Efforts / Results / Conclusions

3
Early Use of Technology at UNCW

• 1981 First student microcomputer lab at UNCW
  (Chemistry)
• Spreadsheets, statistics, graphing, word
  processing.
• ProStat statistical analysis/graphing software
  written by Dick Ward
• 1986 Chemical Applications of Microcomputers
  course
• Introduced students to word processing,
  spreadsheets, and interfacing computers with
  electronic equipment
• 1988 Molecular modeling software obtained
• PCModel on pcs,
• AMPAC on VAX (gift from Dewars group) initially
  used only in research.

4
Early Use of Technology at UNCW

• 1989 NHM attended NSF Workshop on Molecular
  Modeling
• Week-long workshop at Georgia State University.
• 1990 Computational Chemistry courses at NCSC
  online
• Provided necessary competence/confidence level
  for faculty to initiate teaching of computational
  chemistry methods.
• 1992 Introduced Computational Chemistry into
  Advanced
• Organic Chemistry (Physical Organic)
  course
• Used computations to illustrate concepts in text
  students did not do calculations
  themselves, just saw results

5
Grants for Infrastructure

• 1992 HyperChem grants in Chemistry and
  Biochemistry
• Software for curriculum development, research.
• 1993 NSF Grant for Integrating Molecular
  Modeling
• into the Chemistry Curriculum (Phase
  I)
• Provided SGI workstation, 8 fast pcs, and
  multiple copies of HyperChem modeling
  software for chemistry student computer lab and
  faculty.
• Impacted primarily upper level chemistry courses
  Organic Chemistry, Advanced (Physical) Organic,
  Physical Chemistry, Biochemistry, Independent
  Study.

6
Grants for Infrastructure

• 1994 NIDA Medication Development Database
• Pilot project contract provided Accord (3D
  structural database software), student training,
  led to QSAR projects
• 1996 ACS-PRF grant for Modeling NMR Shielding
  (1)
• Spartan and Gaussian94W software, student support
• 1997 NCSC Visualization grant (to NHM)
• SGI O2 workstation, AVS visualization software
• 1998 NCSC Visualization grant (to MM)
• SGI O2 workstation, AVS visualization software

7
Grants for Infrastructure

• 2000 ACS-PRF grant for Modeling NMR Shielding
  (2)
• Updated modeling software, student support
• 2000 Camille and Henry Dreyfus Grant to Enhance
• Computational Chemistry Capabilities
  (Phase II)
• Impacted courses omitted from 1992 NSF grant
  Introductory (General) Chemistry, Inorganic
  Chemistry, Medicinal Chemistry, and a new course
  in Computational Chemistry.
• Also addressed student research needs, NMR data
  processing.
• Provided SGI workstation, NMR analysis software,
  10 fast pcs, multiple copies of Titan.

8
Grants for Infrastructure

• 2001 Numina Grant for HP Jornadas
  
  
  
  and pocket HyperChem
• Allowed student use of computers fro molecular
  modeling in class also allowed for instant
  feedback on student perceptions
• 2002 ITSD grant for PocketPCs
• Improved in-class devices
• 2004 ACS-PRF grant for
• Modeling NMR Shielding (3)
• Updated software, student support

Modeling NMR Shielding (3)
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Goals and Strategy, Phase I

• Goal (Phase I) To enhance students perception
  of 3D concepts in chemistry
• Stereochemistry conformations of molecules, and
  relationship of energy to molecular conformation.
• Strategy 1 Selective integration of modeling
  into the most promising course / instructor
  combinations (most receptive)
• Acceptance by the instructor is key. This
  sometimes required some time for the value of
  computational chemistry to be recognized.
• Training is also needed for those not using
  modeling in research. This must be repeated each
  semester for new instructors and TAs.

10
Goals and Strategy, Phase I

• Strategy 2 Progressively integrate molecular
  modeling into the chemistry curriculum, starting
  in sophomore Organic Chemistry
• Include some modeling in several courses
  throughout the curriculum, so that students learn
  a variety of applications
• Verify modeling predictions with experimental
  results
• Teach increasing levels of theory as needed,
  rather than overloading students with theory to
  start
• Treat molecular modeling as a routine tool, like
  GC, HPLC, IR, or NMR
• Design experiments so that students can
  discover applications of molecular modeling as
  well as learn its
  limitations

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Specific Objectives, Phase I

• Develop computational exercises with
  experimentally verifiable results for selected
  courses.
• Predicting the major alkene isomer resulting from
  dehydration of an alcohol. (Organic Chemistry)
• Base pair H-bonding stabilizes DNA.
  (Biochemistry)
• Test students perception/knowledge level before
  and after modeling was introduced to determine
  the effect of the curriculum change.
• Provide adequate and ongoing instructional /
  tutorial support for students and faculty/TAs.
• Gain support and confidence of faculty.

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Intro. to Molecular Mechanics

• Organic Chemistry students learn the basics of
  molecular mechanics
• Create models of structures, perform energy
  minimizations
• Measure bond lengths, bond angles, and dihedral
  angles
• Construct model of axial methylcyclohexane using
  ideal bond lengths and bond angles measure
  these.
• Perform energy minimizations and observe how the
  molecule adjusts its structure to minimize its
  energy measure the same bond lengths and bond
  angles after energy minimization.

109.5
112.2
13
Organic Chemistry Experiment

• Compute the energies of the isomeric carbocations
  that arise from acid-catalyzed dehydration of an
  alcohol.

(2º carbocation)
methide shift
(3º carbocation)
Sayed, Y. Ahlmark, C. A. Martin, N. H. J.
Chem. Educ. 1989, 66, 174-175.
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Organic Chemistry Experiment

• Computation shows that the rearranged 3º
  carbocation is much lower in energy it can lose
  H to form either of two alkenes the one that
  predominates according to GLC analysis is the
  lower energy alkene, also shown by calculation.

major product lower energy
minor product higher energy
Martin, N. H. J. Chem. Educ. 1998, 75, 241-243.
15
Biochemistry Experiment

• Students model pairs of DNA bases (C-G, A-T, as
  well as others) using semi-empirical MO theory
  they determine the strength of the H-bonds C-G
  (top, which forms three H-bonds), has the
  greatest stabilization due to H-bonding A-T
  (bottom) forms only 2 H-bonds.

16
Biochemistry Experiment

• A plot of the mol C-G vs. the literature
  value of melting temperatures (temperature at
  which the helix unravels) of various DNA samples
  is linear.
• This demonstrates the effect of H-bonding on
  stabilizing the double helix.

Martin, N. H., Burgess, S. K., Connelly, T. L.,
Reynolds, W. R. Spiro, L. D. Biochemical
Education 1996, 24(4), 230-231.
17
Specific Objectives, Phase II

• Develop computational exercises with
  experimentally verifiable results for additional
  selected courses.
• Shapes of simple molecules VSEPR rule
  verification. (General Chemistry)
• Orbital shapes and energies transition metal
  complexes. (Inorganic Chemistry)
• Relating electrostatic energy to stability in
  carbocations. (Physical Organic Chemistry)
• Develop new Computational Chemistry course.
• Provide ongoing instructional / tutorial support
  for students and faculty/TAs.

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General Chemistry

• Hand-held Dell Axim PocketPCs (left) runing
  HyperChem provide students with in-class
  opportunity to view and rotate 3D structures,
  measure bond angles, and examine molecular shapes
  and resulting properties, such as polarity.

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Experimental group used HyperChem to rotate
molecules and measure bond angles
20
Control group used the PocketPCs to view
structures in color, but with no rotation
capability
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Sample Quiz Questions
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Test Results
Gas Law Question
VSEPR Questions
(control)
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Inorganic Chemistry

• HP Jornadas or PocketPCs and HyperChem are used
  in Inorganic (CHM 445) lecture to
  visualize molecular orbital splitting, see the
  shapes of molecular orbitals and their energy
  levels, and calculate bond stretching frequencies
  of CO before and after complexation with
  a metal.

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Inorganic Chemistry

• Students compute the energies of the
  molecular orbitals of BH3 (top) and then
  visualize them (bottom) to assess Lewis acid
  properties.

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Physical Organic Chemistry

• Students use Jornadas or PocketPCs and HyperChem
  during lecture to examine various topics as they
  are discussed, including
• MO calculations of molecular geometry, bond
  orders, atomic charges, and hybridization.
• Visualization of symmetry properties of
  molecules
• Calculation and visualization of steric effects
  in substituted cyclohexanes.
• Students also do computational projects outside
  of class using HyperChem on pcs in the computer
  lab.

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Computational Chemistry course
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Computational Chemistry

• New course in 2002, 2 lecture 2 computer lab
  hours/wk
• http//www.uncwil.edu/chem/molecularm
  odeling
• Covers the basic theoretical background of
  several computational methods molecular
  mechanics, quantum mechanics, density functional
  theory, molecular dynamics.
• Provides computer lab exercises in model
  building, energy minimization,conformation
  searching, transition state modeling, reaction
  pathway modeling, visualization of results and
  molecular property calculations (NMR).
• Introduces solvent effects, QSAR, modeling
  biomolecules, UNIX language, grid computing.

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Comp. Chem Syllabus

• Introduction to computational chemistry (overview
  of capabilities, relative cpu time, limitations
  and applications of various methods)
• Molecular mechanics (components of force fields,
  file types, atom types, successes and
  limitations caveats about minimum energy
  structure)
• LAB 1. Building and optimizing structures in
  Titan (model building, rendering modes,
  measurements)
• Molecular orbital theory, part 1 (history, levels
  of MO theory, SEMO methods, computational
  results)
• LAB 2. Manual conformation searching methods
  
• Molecular orbital theory, part 2 (ab initio MO
  theory, basis sets, correlated methods, effect of
  choice of method/basis set on cpu time)
• LAB 3. Automated conformation searching
• Calculating molecular properties (energy
  derivatives, UV-Vis, NMR, freq.)

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Comp. Chem Syllabus

• LAB 4. Ring strain in cycloalkanes
  isodesmic reactions
• Potential energy surfaces optimization methods
  reaction path following (gradient, stationary
  points, saddle point, minimization algorithms, TS
  modeling, frequency calculation, rxn. pathway
  calc.)
• LAB 5. Modeling a reaction pathway the
  pinacol rearrangement (locating a TS frequency
  calculation
• Computing charges on atoms (Mulliken, natural
  bond order, AIM, MK and CHELPG charges best fit
  to NMR data electrostatic effects on carbocation
  stabilization and conformation)
• LAB 6. Stability of alkenes and carbocations
• Solvation effects hybrid (QM/MM) methods
  (explicit, continuum and hybrid models ONIUM
  method hybrid MM/QM methods)
• LAB 7. Basicity of amines (electrostatic
  potential mapped on electron density isosurface
  modeling solvent effects)
• LAB 8. Modeling bromonium ion intermediates
  (LUMO)

30
Comp. Chem Syllabus

• Density functional theory (guest lecturer Lee
  Bartolotti, ECU)
• LAB 9. Endo/Exo Selectivity in Diels-Alder
  Cycloadditions (kinetic vs thermodynamic control)
• Grid Computing UNIX operating system Remote
  computing Gaussian 03 GridNexus NMR
  calculations of classical vs. non-classical
  carbocations
• LAB 10. Modeling the Relative Acidities of
  Substituted Phenols (npa charges, electrostatic
  potential mapped on electron density isosurface)
• Quantitative Structure-Activity Relationships
  (QSAR)
• LAB 11. NMR shift and charge calculations
  using Gaussian 03 on a Linux cluster
  Introduction to Grid computing via GridNexus
  (file formats and their interconversion)
• WWW computational chemistry resources modeling
  biomolecules (special visualization methods)

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Summary and Conclusions, Part 1

• Computational applications have been integrated
  throughout the chemistry curriculum at UNCW.
• The process requires interested / convinced
  faculty.
• Ongoing training of faculty and TAs is critical.
• We found that to be most effective, computer
  exercises should be verified by laboratory
  results.
• Integration into multiple courses and all levels
  (freshman through senior level) is critical in
  order to demonstrate to students the
  general applicability of computational
  methods.

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Part 2. Grid Computing
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Rationale for Grid Computing
The recent proliferation of fast, interconnected
underutilized cpus
ts/104
over 150,000,000 pcs are sold each year!
34
Grid Computing

• A computing Grid is analogous to an electrical
  power grid. The user simply taps into the
  resource (with permission), but is usually
  unaware of the origin of the resource.

35
Grid Computing at UNCW

• Current efforts by a group of UNCW computer
  science faculty and undergraduate students, plus
  faculty and students in several application
  areas are focused on developing a graphical
  user interface (GUI) called
• GridNexus serves as a front-end to simplify data
  manipulations, searching or calculations of
  various types performed on remote computers over
  a Grid.
• This project has grant support from the UNC
  Office of the President

36
GridNexus

• GridNexus is based on JXPL, a new graphical
  programming language developed by UNCW computer
  science faculty and students.
• GridNexus allows users to link modules that
  perform various operations into a usable
  workflow, then save these for later use.
• Once a workflow has been created, one only need
  to specify the path/filename of the data set to
  be operated on and the path/filename for the
  output file.
• This greatly simplifies repetitive operations,
  and takes much of the mystery out of
  computing for non-computer science
  users.

37
File Interconversion in GridNexus

• One of the limitations of most computational
  chemistry software packages is that they do not
  read or write many different (proprietary) file
  types, so it is difficult to transfer data from
  one program to another.
• GridNexus allows users to input some of the most
  common types of geometry specification, such as
  .pdb (.ent) and .mol files, and use a default
  set of options (or select from a list) to write a
  Gaussian input (.dat) file.
• GridNexus also allows the user to orient a
  molecule in a specified way in Cartesian
  coordinates.

38
Gaussian 03 under GridNexus
Functions can be selected from lists at the top
left, dragged onto the workspace and joined.
The entire workflow can be hidden in a single
multifunction box
39
Gaussian 03 under GridNexus
Submitting a Gaussian job can be as simple as
selecting the input file name (from a variety of
file types) and the desired output file name.
40
Molecule Orientation in GridNexus

• One module allows a molecule to be oriented in
  Cartesian space in a specified way,
  then writes a proper Gaussian03 input file.

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Gaussian 03 Input File

• chktmp/martinn/phenanthreneNH2.chk
• HF/6-31G(d,p) opt freq
• phenanthreneNH2
• 0 1
• H -1.963715 -3.198017
  1.280991
• C -1.127512 -2.730904
  0.750482
• H -0.184242 -4.593909
  0.244859
• C -0.149560 -3.501921
  0.166986
• C 0.000000 -0.715690
  0.000000
• N 0.000000 0.715690 0.000000
• C 0.908090 -2.892498
  -0.536779
• C -1.036579 -1.338948
  0.691052
• C 0.971979 -1.491079
  -0.702775
• C 1.943981 -3.742718
  -1.057698
• H -1.800364 -0.744862
  1.210005
• H 1.238823 1.070292
  -1.769705
• C 2.993024 -3.223318
  -1.730309

Note C N along the Y axis, the midpoint of
their bond at the origin
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Whats next for GridNexus?

• Develop more filters to transform data.
• Enhance the graphics for appearance and
  usability.
• Include more software applications.
• Extend Grid services to other disciplines.
• Include industry and businesses as users and
  developers.
• Add more computational nodes to the Grid. The
  goal is to include all NC institutions of higher
  learning

43
Acknowledgements

• NSF
• ACS-PRF
• HyperCube, Inc.
• Pearson Education Foundation
• Camille and Henry Dreyfus Foundation
• UNCW Department of Chemistry and Biochemistry,
  College of Arts and Sciences, Division of
  Academic Affairs, and Information Technology
  Systems Division (ITSD)
• (former) North Carolina Supercomputing Center
• UNC-Office of the President