CONTENT - PowerPoint PPT Presentation

1 / 44
About This Presentation
Title:

CONTENT

Description:

Title: Computer As Virtual Chemistry Labs Author: LAC/Togni Last modified by: Ivano Tavernelli Created Date: 5/3/1999 12:48:31 PM Document presentation format – PowerPoint PPT presentation

Number of Views:56
Avg rating:3.0/5.0
Slides: 45
Provided by: LACT4
Category:

less

Transcript and Presenter's Notes

Title: CONTENT


1
CONTENT
  • Doing Chemistry with Computers
  • Description of the tools
  • - classical and quantum models
  • - dynamics
  • - QM/MM computation in a complex envirnoment
  • Applications

2
Doing Chemistry with Computers
I.
3
Complement and Alternative to Lab Experiments
  • investigate unusual temperature/pressure regions
  • simulate dangerous experiments
  • find alternative for hazardous chemicals
  • gain an atomistic description of a reaction
  • save lab costs

Understanding of Reaction Mechanism
  • characterize reactive intermediates
  • identify rate determining or stereoselective
    steps

4
COMPUTER PERFORMANCE
(10th fastest computer)
Cray T3E
Performance (GFLOPS)
Fujitsu VPP
Cray T3D
Cray Y-MP
Year
5
COMPUTER PERFORMANCE
(10th fastest computer)
Cray T3E
Early 1990s
up to 30 atoms
main group elements
Performance (GFLOPS)
Fujitsu VPP
Cray T3D
Cray Y-MP
Year
6
COMPUTER PERFORMANCE
(10th fastest computer)
Cray T3E
Present
100-1000 of atoms
heavy elements
dynamics
Performance (GFLOPS)
Fujitsu VPP
Cray T3D
Cray Y-MP
Year
7
Relative Cost of the Most Powerful Commercial
Computer
100
IBM 650
10
1
IBM7094
10-1
Relative Cost per MFLOP
CDC 7600
10-2
CDC 205
10-3
CRAY Y-MP
10-4
SGI/CRAY T3E
10-5
1950
1960
1970
1980
1990
2000
8
II.
Computer experiments need models and theories to
describe nature laws with the language
of mathematics
  • environmental sciences
  • biology
  • chemistry
  • physics
  • .

9
When Newton meets Schrödinger...
Sir Isaac Newton
Erwin Schrödinger
(1642 - 1727)
(1887 - 1961)
10
Electronic Structure Methods
Classical MD Simulations
  • parameter-free MD
  • ab initio force field
  • no transferability
  • problem
  • chemical reactions
  • improved optimization
  • finite T effects
  • thermodynamic
  • dynamic properties
  • solids liquids

11
Electronic Structure Methods
Classical MD Simulations
Force field approach
Ab-initio approach
12
Schrödingers equations made easy with DFT !
Walter Kohn and John Pople Nobelprize in
chemistry 1998
13
Mixed Quantum-Classical
Classical MD Simulations
Traditional QC Methods
First-Principles Car-Parrinello MD
14
Our needs for a virtual lab
  • Atoms
  • Electrons
  • Eq. of Motion
  • Reactions

Density functional theory Car-Parrinello
Molecular Dynamics
15
Main idea
  • Partitioning the system into
  • chemical active part treated by QM methods
  • 2. Interface region
  • 3. large environment that is modeled by a
    classical force field

16
Main idea
  • Partitioning the system into
  • chemical active part treated by QM methods
  • 2. Interface region
  • 3. large environment that is modeled by a
    classical force field

17
APPLICATIONS
III.
18
Improved Optimization Techniques
(simulated annealing)
Nanoscale Silicon Clusters
Si45
Phys.Rev.Lett. 72, 665 (1994)
19
In Situ Simulation of Chemical Reactions
ONOOH NO2- ? HNO3 NO2-
Cis/trans isomerization ONOOH
Gas Phase
Aqueous Solution
J. Phys. Chem. A, 104, 6464 (2000)
Chem. Phys. Lett. 297, 205 (1998)
Aqueous Solution
ONOO- ? NO- 1O2
PNAS 97 , 10307 (2000)
ONOO- CO2 ? ?
In collaboration with W. Koppenol, ETH Zurich
20
(No Transcript)
21
Structure Determination of

Ta Cp (Si(HPh)N(Ar)) - H
2
2
2
2
NMR suggests
asymmetric Tas
TaH 11.63, -1.00 ppm
d
Collaboration with Prof. D. Tilley, University
of California, Berkeley, U.S.A.
22
Lowest Energy Structure
  • one bridged and


one terminal H
  • excellent agreement

with Xray and NMR
Collaboration with Prof. D. Tilley, University
of California, Berkeley, U.S.A.
23
Excitation spectra of molecules in
solution Solvent Shift in Aceton
U. Röhrig, A. Laio, J. VandeVondele, J. Hutter,
I. Frank, U.R. (in preparation)
24
Anti-AIDS HIV-1 Protease
Molecular Mechanisms of ApoptosisCaspase-3
DNA-Repair Endonuclease IV
Prions and Metal Ions
Selectivity of KcsA Channel
Photoisomerization in Rhodopsin
25
Modelling Understanding
  • Engineering
  • inhibitors
  • metal centers
  • new residues
  • Biomimetics
  • easy preparation
  • easy handling
  • easy tuning

26
Rational Design of Biomimetics
Galactose Oxidase
Synthetic Compound
t
i
Stack et al., Science (1999)
27
QM/MM Hybrid Car-Parrinello Modeling of GOase
Tyr495
Cu
His496
Cys228
28
Parallel Modeling of the Catalytic Cycle
21 kcal/mol
16 kcal/mol
U.R, P. Carloni, K. Doclo and M. Parrinello
JBIC 5, 236 (2000)
29
Biomimetic
Goase
U.R, P. Carloni Intl. J. Quant. Chem. 73, 209
(1999)
30
Mimetic Stack
GOase
16 kcal/mol
21 kcal/mol
New Biomimetics
M1 16 kcal/mol M2 16 kcal/mol M3 18
kcal/mol M4 14 kcal/mol
31
HIV- Virus (AIDS)
HIV- I Protease
32
HIV-PR is essential for the formation of
infective viruses
Immature, non-infective Viral particles
Infective viruses
33
Viewing Enzymes at work
HIV- I Protease
34
Prion Proteins
http\\ www.mad-cow.org
Human Prion Protein
(Wuthrich et al. PNAS 97, 145 (2000))
35
Localization of Possible Binding Sites via a
Parallel Statistical and QM Approach
  • 111 PDB structures
  • ? 2.0 Å resolution
  • 216 copper binding sites
  • 928 donor atoms

36
Secondary structure changes inducedby external
factors (pH, temperature, Cu)
Method Enhanced sampling techniques
37
Metal Ion / DNA Interactions
Cis-Pt anticancer drugs
38
Metal Ion / DNA Interactions
Cis-Pt anticancer drugs
39
Cis/Trans Photoisomerisation in Rhodopsin The
First Steps of Vision
40
Cis/Trans Photoisomerisation in Rhodopsin The
First Steps of Vision
41
10ns classical MD simulations
total of atoms 24000
? RMS backbone 0.9Å
42
Photoisomerisation in the Excited State
43
Dynamics in the first excited singlet state
(in collaboration with I. Frank, Univ. Munich, C.
Molteni, Univ. Cambridge, M. Parrinello, CSCS
Manno)
44
Not all chemists wear white coats...
Computer Experiments
  • provide atomistic picture of (bio)chemical
    systems
  • help to characterize and understand reaction
    mechanisms
  • planning of laboratory experiments
  • computational modelling of catalysts and enzymes
  • rational design of drugs and biomimetics
Write a Comment
User Comments (0)
About PowerShow.com