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

CONTENT

•Doing Chemistry with Computers•Description of the tools

- classical and quantum models

- dynamics

- QM/MM: computation in a complex envirnoment• Applications

Doing Chemistry with ComputersDoing Chemistry with ComputersI.I.

•investigate unusual temperature/pressure regionsinvestigate unusual temperature/pressure regions•simulate dangerous experimentssimulate dangerous experiments•find alternative for hazardous chemicalsfind alternative for hazardous chemicals•ggain an atain an atoomistic description of mistic description of a reactiona reaction•save lab costssave lab costs

Why Do Computer Experiments?Why Do Computer Experiments?

Complement and Alternative to Lab ExperimentsComplement and Alternative to Lab Experiments

Understanding of Reaction Understanding of Reaction MechanismMechanism• characterize reactive intermediatescharacterize reactive intermediates

• identify rate determining or stereoselective stepsidentify rate determining or stereoselective steps

optimization of catalystsoptimization of catalysts rational drug designrational drug design

controlling and tuning of chemical reactionscontrolling and tuning of chemical reactions

Per

form

ance

Per

form

ance

(G

FL

OP

S)

(G

FL

OP

S)

0

100100

200200

300300

400400

500500

9494 9595 9696 9797 98989393

YearYear

COMPUTER PERFORMANCECOMPUTER PERFORMANCE(10th fastest computer)(10th fastest computer)

Cray Y-MPCray T3D

Fujitsu VPP

Cray T3E

diatomics triatomics

1970s1970s

Per

form

ance

Per

form

ance

(G

FL

OP

S)

(G

FL

OP

S)

0

100100

200200

300300

400400

500500

9494 9595 9696 9797 98989393

YearYear

COMPUTER PERFORMANCECOMPUTER PERFORMANCE(10th fastest computer)(10th fastest computer)

Cray Y-MPCray T3D

Fujitsu VPP

Cray T3E

aspirin

caffeineup to 30 atoms

main group elements

Early 1990sEarly 1990s

Per

form

ance

Per

form

ance

(G

FL

OP

S)

(G

FL

OP

S)

0

100100

200200

300300

400400

500500

9494 9595 9696 9797 98989393

YearYear

COMPUTER PERFORMANCECOMPUTER PERFORMANCE(10th fastest computer)(10th fastest computer)

Cray Y-MPCray T3D

Fujitsu VPP

Cray T3E

100-1000 of atoms

PresentPresent

heavy elementsdynamics

IBM 650IBM 650

CDC 7600CDC 7600

IBM7094IBM7094

CRAY Y-MPCRAY Y-MP

CDC 205CDC 205

Rel

ativ

e C

ost

per

MF

LO

PR

elat

ive

Co

st p

er M

FL

OP

Relative Cost of the Most Powerful Relative Cost of the Most Powerful Commercial ComputerCommercial Computer

SGI/CRAY T3ESGI/CRAY T3E

Computer experiments needComputer experiments needmodels and theories models and theories

to describe nature lawsto describe nature laws

with the language ofwith the language ofmathematicsmathematics

•environmental sciencesenvironmental sciences•biologybiology•chemistrychemistry•physicsphysics•……..

II.II.

When Newton meets Schrödinger...

maF H

Sir Isaac Newton(1642 - 1727)

Erwin Schrödinger(1887 - 1961)

Computational Chemistry and BiologyComputational Chemistry and Biology

Electronic StructureMethods

Classical MDSimulations

• parameter-free MD• ab initio force field• no transferability problem• chemical reactions

• improved optimization• finite T effects• thermodynamic & dynamic properties• solids & liquids

Computational Chemistry and BiologyComputational Chemistry and Biology

Electronic StructureMethods

Classical MDSimulations

Force field approach Ab-initio approach

Walter Kohn and John Pople

Nobelprize in chemistry 1998

Schrödingers equations made easy with DFT !

Traditional QCMethods

First-Principles Car-Parrinello

MD

Classical MDSimulations

When Quantum Chemistry Starts to Move...When Quantum Chemistry Starts to Move...

Mixed Quantum-Classical

Our needs for a virtual labOur needs for a virtual lab

•ElectronsElectrons

•Eq. Eq. oof Motionf Motion

ReactionsReactions

•AtomsAtoms

Density functional theory & Car-Parrinello Molecular Dynamics

Mixed Quantum-Classical in a complex environment - QM/MM

Main idea

Partitioning the system into

1. chemical active part treated by QM methods

2. Interface region

3. large environment that is modeled by a classical force field

QM

interface

Classical MM

Mixed Quantum-Classical in a complex environment - QM/MM

Main idea

Partitioning the system into

1. chemical active part treated by QM methods

2. Interface region

3. large environment that is modeled by a classical force field

QM

interface

Classical MM

APPLICATIONS

Phys.Rev.Lett. 72, 665 (1994)

III.III.

Improved Optimization Techniques:Improved Optimization Techniques:(simulated annealing)(simulated annealing)

Nanoscale Silicon Nanoscale Silicon ClustersClusters

Si4545

2C2Li H2

Li

Li

C C

H

H

Phys.Rev.Lett. 72, 665 (1994)

Li

Li

C CH

H

J. Am. Chem. Soc. 177, 42 (1995)

In SituIn Situ Simulation of Chemical Reactions Simulation of Chemical Reactions

Chem. Phys. Lett. 297, 205 (1998)

.OH + .NO2 ONOOH

Gas Phase

Aqueous Solution

J. Phys. Chem. A,104, 6464 (2000)

Cis/trans isomerization ONOOH

ONOOH + NO2-

HNO3 + NO2-

Aqueous Solution

ONOO- NO- + 1O2

PNAS 97 , 10307 (2000)

ONOO- + CO2 ?

In collaboration with W. Koppenol, ETH Zurich

PdSi

SiCl

Cl

Cl

Cl

Cl

Cl

PFe

Homogeneous CatalysisHomogeneous Catalysis

OrganoLithium

Pd-Phosphine Ta2-Hydride

Pd(ll)-bis(trichlorosilyl)

Re,Tc-Thioether

W2Cl2(PMe3)2(NHR)2

Structure Determination ofStructure Determination of

Collaboration with Prof. D. Tilley, University of California, Berkeley, U.S.A.

Ta Cp (Si(HPh)N(Ar)) - HTa Cp (Si(HPh)N(Ar)) - H22 22

**22 22

NMR suggests NMR suggests asymmetric Ta’sasymmetric Ta’s

TaH 11.63, -1.00 ppmTaH 11.63, -1.00 ppm

Lowest Energy Structure:Lowest Energy Structure:

Collaboration with Prof. D. Tilley, University of California, Berkeley, U.S.A.

• one bridged andone bridged and

• excellent agreementexcellent agreement

with Xray and NMRwith Xray and NMR

one terminal Hone terminal H

Excitation spectra of molecules in Excitation spectra of molecules in solution;solution;

Solvent Shift in AcetonSolvent Shift in Aceton

n -> *

Solvent Shift: Solvent Shift: 0.21 eV 0.21 eV (exp) (exp) 0.23eV 0.23eV (ROKS, QM = Solute) (ROKS, QM = Solute) = 0.03-0.04eV= 0.03-0.04eV (ROKS, QM = Solute (ROKS, QM = Solute + 12 H+ 12 H22O)O)

U. Röhrig, A. Laio, J. VandeVondele, J. Hutter, I. Frank, U.R. (in preparation)

Anti-AIDS: Anti-AIDS: HIV-1 ProteaseHIV-1 Protease

PrionsPrions and and

Metal IonsMetal Ions

DNA-Repair: DNA-Repair: Endonuclease IVEndonuclease IV

Photoisomerization Photoisomerization in Rhodopsinin Rhodopsin

Molecular MechanismsMolecular Mechanismsof Apoptosis:Caspase-3of Apoptosis:Caspase-3

Selectivity of Selectivity of KcsA ChannelKcsA Channel

Ab initio Modelling of EnzymesAb initio Modelling of Enzymes Rational Design of Biomimetics & Enzyme-EngineeringRational Design of Biomimetics & Enzyme-Engineering

Biomimetics• easy preparation• easy handling• easy tuning

Engineering• inhibitors• metal centers• new residues

Modelling &

Understanding

Rational Design of Biomimetics

Galactose Oxidase

O

N

O

NCu

R5

R3R3

R5

Synthetic Compound

t i R3 = SPh, SPr , Bu , BrR5 = Bu , Brt

R- H2 C - OH + O2 R-C + H2O2

O

H=

\Stack et al., Science (1999)

QM/MM Hybrid Car-Parrinello Modeling of GOase

Cu

Tyr495

Cys228

His496

U.R, P. Carloni, K. Doclo and M. Parrinello JBIC 5, 236 (2000)

Parallel Modeling of the Catalytic Cycle

resting stateresting stateinactiveinactive

GOaseGOase MimicMimic GOaseGOase

resting stateresting stateactiveactive

MimicMimic

after protonafter protontransfertransfer

transition statetransition state H-abstractionH-abstraction

16 kcal/mol16 kcal/mol

21 kcal/mol21 kcal/mol

Biomimetic

Goase

U.R, P. Carloni Intl. J. Quant. Chem. 73, 209 (1999)

GOaseMimeticStack

New BiomimeticsM1: 16 kcal/molM2: 16 kcal/molM3: 18 kcal/molM4: 14 kcal/mol

16 kcal/mol 21 kcal/mol

HIV- Virus (AIDS)

HIV- I Protease

Asp25Asp25

Asp25’Asp25’Gly27Gly27

Gly27’Gly27’

Thr26Thr26

Thr26’Thr26’

HIV-PR is essential for the formation of infective viruses

Immature, non-infective Immature, non-infective Viral particlesViral particles

HIV-1 PRHIV-1 PR

Infective virusesInfective viruses

Viewing Enzymes at work

HIV- I Protease

Prion ProteinsPrion Proteins

Fatal NeurodegenerativeFatal NeurodegenerativeDiseases:Diseases: Mad Cow Disease (BSE)Mad Cow Disease (BSE)• ScrapieScrapie• Creutzfeldt-Jakob Creutzfeldt-Jakob • caused by abnormalcaused by abnormal isoform PrP(Sc)isoform PrP(Sc)Human Prion ProteinHuman Prion Protein

(Wuthrich et al. PNAS 97, 145 (2000))(Wuthrich et al. PNAS 97, 145 (2000))

http:\\ www.mad-cow.org

Localization of Possible Binding Sites via Localization of Possible Binding Sites via a Parallel Statistical and QM Approach a Parallel Statistical and QM Approach

• 111 PDB structures 111 PDB structures 2.0 Å resolution2.0 Å resolution• 216 copper binding sites216 copper binding sites• 928 donor atoms 928 donor atoms

0

10

20

30

40

50

60

70

H C M G D Y E Q S

Cu-coordinatedCu-coordinatedNatural Natural

abundanceabundance

His 187

Met 206

Tyr 157

R = 24

His 140

Asp 147

Asp 144

R = 21His 140

Asp 147

Asp 144

R = 21

His 140

Asp 147

Asp 144

R = 21

Secondary structure changes inducedSecondary structure changes inducedby external factors by external factors

(pH, temperature, [Cu++]) (pH, temperature, [Cu++])

Method: Enhanced sampling techniques

Metal Ion / DNA Interactions

Cis-Pt anticancer drugs

Metal Ion / DNA Interactions

Cis-Pt anticancer drugs

A piano chair to fight cancer

Organoruthenium anticancer drugs(in collaboration with

Prof. Paul Dyson, EPFL)

Cis/Trans Photoisomerisation in Rhodopsin:Cis/Trans Photoisomerisation in Rhodopsin:The First Steps of VisionThe First Steps of Vision

200fs0.67

Cis/Trans Photoisomerisation in Rhodopsin:Cis/Trans Photoisomerisation in Rhodopsin:The First Steps of VisionThe First Steps of Vision

200fs0.67

10ns classical MD simulations10ns classical MD simulations

RMS backbone: 0.9ÅRMS backbone: 0.9Åtotal # of atoms: 24000total # of atoms: 24000

Photoisomerisation in the Excited StatePhotoisomerisation in the Excited State

Dynamics in the first excited singlet stateDynamics in the first excited singlet state

(in collaboration with I. Frank, Univ. Munich, C. Molteni, (in collaboration with I. Frank, Univ. Munich, C. Molteni, Univ. Cambridge, M. Parrinello, CSCS Manno)Univ. Cambridge, M. Parrinello, CSCS Manno)

Not all chemists wear white coats...Not all chemists wear white coats...

Computer ExperimentsComputer Experiments• provide atomistic picture of (bio)chemical systemsprovide atomistic picture of (bio)chemical systems• help to characterize and understand reaction mechanismshelp to characterize and understand reaction mechanisms

planning of laboratory experimentsplanning of laboratory experiments computational modelling of catalysts and enzymescomputational modelling of catalysts and enzymes rational design of drugs and biomimeticsrational design of drugs and biomimetics

Current Limits and Future PerspectivesCurrent Limits and Future Perspectives• accuracy of electronic structure method• system size• limited time scale

improved QM/MM methodsimproved QM/MM methods long time scale techniqueslong time scale techniques