varuna: an integrated modeling environment and database for quantum chemical simulations

Varuna: An Integrated Modeling Varuna: An Integrated Modeling Environment and Database for Quantum Environment and Database for Quantum

Chemical SimulationsChemical Simulations

Chemical Prototype ProjectsChemical Prototype Projects

CICC - Chemical Informatics And Cyberinfrastructure CollaboratoryCICC - Chemical Informatics And Cyberinfrastructure CollaboratoryDepartment of Chemistry & School of InformaticsDepartment of Chemistry & School of InformaticsIndiana University BloomingtonIndiana University Bloomington

October 21, 2005October 21, 2005

Mu-Hyun BaikMu-Hyun Baik

2

State of Affairs in Computational ChemistryState of Affairs in Computational Chemistry

High-level quantum simulations based on Density Functional Theory allow for very reliable simulations of chemical reactions for systems containing up to 500 atoms.

Combining Quantum Mechanics and Molecular Mechanics, we can construct highly realistic computer models of biologically relevant reactions.

Currently, chemical modeling studies are done in an isolated fashion and the computed data is typically collected in an unorganized manner (directory-jungle) and disregarded after completion of the study.

Modeling is currently done manually: vi, emacs and ssh are currently the most common interfaces of computational chemists.

3

Cyberinfrastructure DevelopmentCyberinfrastructure Development

Depository for computational chemistry data. Automated data collection and categorization Chemical structure recognition Mining of quantum chemical data User independent domain expertise

Development of an integrated modeling environment Services: Automated execution of calculations

Automatic generation of input files, communication with number crunchers, recognition and correction of typical failures, automated import of main results, etc.

Computational resource management Visualization

4

Data StructureData Structure

Currently Implemented:

- Metadata: QM parameters,Project data

- Results: Energy components - Parser extracts all important results

- Visualizations

Future Work:

- Structure recognition (2D and 3D fingerprints, SMILES, etc….)- Automatic generation of new structures based on computed results

5

Automated Computational ChemistryAutomated Computational Chemistry

Researcher Varuna

Hardware

Modeling SoftwareFORTRAN Code

SFTP, SSH

Data

File TransferJob-SubmissionResource Management

3D-CoordinatesWave Functions

VisualizationMO's (VRML), Rxn Profiles

Input FileGeneration

QueriesRecycling

External DataPubChem, CCDC

- Increase efficiency through automation => Make life easier

- Allow high-throughput production=> Combinatorial Computational Chemistry

- Increase depth of wavefunction analysis => Automated pattern-search

- Simplify and visualize complicated data in intuitive graphical representations

- Allow information recycling => Accumulation of group expertise (Data depository system, Web-Interface)

6

Chemical Prototype ProjectsChemical Prototype Projects

7

Pathogenesis of Alzheimer’s DiseasePathogenesis of Alzheimer’s Disease

AD with cortical atrophy

Neuritic plaque with a core madeof Cu--Amyloid complex

8

9

How does Varuna fit into all this?How does Varuna fit into all this?

Force-field Database: Currently, Cu-Ligand force-fields are being generated manually. We

would like to develop a Service component that will do this automatically These force-fields will be made available in the database.

We already have ~400 plausible Cu--Amyloid high-resolution structures with QM energies: Data Mining Services are needed to compare structural similarities, reactivity indices, etc.

The reactivity of the Cu-center in the peptide must be compared systematically against small molecule models.

10

Immediate ChallengesImmediate Challenges

A 3D structural representation is needed that can deal with: Non-integer bond-orders, transition state structures

with multi-center/multi-electron bonds

Many different quantum chemically derived property topologies

The metadata is complex because of many technical parameters that make calculations difficult to compare

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Cisplatin: Profiling an Anticancer DrugCisplatin: Profiling an Anticancer Drug

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Computational Organic ChemistryComputational Organic Chemistry

13

Diastereoselective [4+2+2] CarbocyclizationDiastereoselective [4+2+2] Carbocyclization

1 2 3

RhCl(IMes)(COD)TsN

R1

R3

R2

TsN

HR1

R2

R3

TsN

HR1

R2

R3

vs

ds 19:1>

2 2 2AgOTf, PhMe,

- What is the mechanism of this transformation?

- What is the source of the diastereoselectivity?

- Can the scope of the reaction be extended?

- Can we reverse the stereo-control using the same methodology?

Evans, P. A. et al. Chem. Commun. 2005, 63

14

Who cares ?Who cares ?

Mehta, Singh. Chem. Rev. 1999, 99, 881

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Reaction Energy ProfilesReaction Energy ProfilesLow CO Pressure High CO Pressure

Low diastereoselectivity High diastereoselectivity

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Collaborative NetworkCollaborative Network

Baik-Group (IU)Computational Chemistry

Molecular Modelling

Lippard (MIT)Cisplatin,

Methane Monooxygenase

Newcomb (UI-Chicago)B12-Dependent Enzymes

Center for Catalysis (IU)CaultonMindiolaEvans

JohnstonWilliams

Sames (Columbia)Ir-, Rh-Catalyzed

C-H activation

Jacobsen (Harvard)Asymmetric Catalysis,Enzymatic Oxidations

Szalai (UMBC)Alzheimer’s Disease

CICC

17

Center for Catalysis at IU-BloomingtonCenter for Catalysis at IU-Bloomington

OrganicSynthesis

Andy Evans Jeff Johnston

Organometallic Catalyst Design

Dan Mindiola Ken Caulton

MolecularModeling

Mookie Baik

Rational Design of Well-Defined, Efficient and mechanistically fully understood Catalysts for Natural Product Synthesis,Polymerization and C-C/C-H activation.

Educational Goal: A new breed of chemists who can conduct high-level research in all three areas of Organic, Inorganic and Computational/Theoretical Research

18

19

General Research PhilosophyGeneral Research Philosophy

Theoretical Tools

DFT, MP2, MM, QM/MM, etc..

Experiments

Structures, Lifetimes, Rates, Isotope-EffectsActivation Enthalpies,Redox-Potentials….

Model Chemistry

HOW?

Analysis

Chemical IntuitionMO-DiagramEnergy-DecompositionWhat-If GameHandwaving

Model Chemistry

WHY?

New Chemistry

Prediction

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Inherent Problems of Organic Mechanism DiscoveryInherent Problems of Organic Mechanism Discovery

Most of the time all you have is a reactant and a product, if you are lucky.

Intermediates, particularly the interesting reactive ones, can’t be observed directly.

“Classical Approach” of Constructing a New Mechanism: Memorize as many as possible known mechanisms Try to recognize similarities (mostly structural) and assume

that what worked for one reaction may work for another

Mechanisms are often quite “arbitrary”.

21

““Classical” Approach to Proposing a MechanismClassical” Approach to Proposing a Mechanism

XLnM(n)

M(n)LnX

M(n+2)LnXOxidative Addition

CO

XM(n+2)Ln

O

X O

Insertion

Migratory InsertionReductiveElimination

What we’ve seen before: Pauson-Khand-type Reaction

Evans, P. A. et al. J. Am. Chem. Soc. 2001, 123, 4609Magnus, P. et al. Tetrahedron 1985, 41, 5861Buchwald S. L. et al. J. Am. Chem. Soc. 1996, 118, 11688.

22

““Classical” Approach to Proposing a MechanismClassical” Approach to Proposing a Mechanism

LnRh(I)A

X

R1

RhX

R1

RhX

HR1

X

HR1

ii

i

+

iii

iv

vi

+

R2

Rh+

X

R1

R2

R2

R2

R2

Ln

Ln

+

“Logical” mechanism for the [4+2+2]:

Stereocontrol:Rh coordination is faciallyselective. The sterically bulkyR1 group directs Rh to the correct side of the -component.

Evans, P. A. et al. Chem. Commun. 2005, 63

23

Let’s think about this….Let’s think about this….

X

R1

A

B

C

- Oxidative Addition involving the triple bond should be facile.=> (A) and (B) can’t be rate determining!

- So, forming either bond (A) or (B) first is plausible, but:- Form (B) first => Stereochemistry at C2 is fixed !!- Stereocontrol at a reaction Step that is NOT rate determining??

24

New ProposalNew Proposal

LnRh(I)X Rh

R

+

X Rh

R1

+

Rh+

A B

X

R1

RhX

R

RhX

HR

X

HR1

X

R1ii

i

+

iii

iv

vi

+

vii

viii

R2R2

R2

Rh+

X

R1

R2

ii

R2

R2

R2

R2

LnLn

Ln Ln

J. Am. Chem. Soc. 2005, 127, 1603

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Computational Model ChemistryComputational Model Chemistry

Compute from VibrationalFrequency Calculation.

Compute from Continuum Solvation Model.

Electronic SCF Energy

Correction for Changesin Zero-Point-Energy

Thermal Corrections of theEnthalpy.

G(GP) = H(GP) - TS(GP)

G = G(GP) + G(Solv)

H(GP) = E(SCF) + ZPE + TCp

- Density Functional Theory @ B3LYP/cc-pVTZ(-f) (Jaguar)- Numerically efficient up to 300 atoms => no compromises with respect to Model Size

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EntropyEntropy

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Continuum Solvation ModelContinuum Solvation Model

ˆ ˆ| |

Mgi

k

as

ik

ki

q

rh

rh

. ( ) ( ) ( )

( )( )

E S S S S S S

S A

lSt AS S S

A A SS S S

SS

S

S S

ZE dr dr dr

R

dr

rr dr

r r r

r r r

r

r

H H

O

– ––

––

––

––– –

++

+++

++++

++

+

+

++

++ + +

++

++

–

–

–

––––

–––

–

–

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Computed Reaction Energy ProfilesComputed Reaction Energy Profiles

LnRh(I)A

X

R1

RhX

R

RhX

HR

X

HR1

ii

i

+

iii

iv

vi

+

R2

Rh+

X

R1

R2

R2

R2

R2

Ln

Ln

J. Am. Chem. Soc. 2005, 127, 1603

29

Computed Reaction Energy ProfilesComputed Reaction Energy Profiles

LnRh(I)X Rh

R

+

X Rh

R1

+

Rh+

B

X

R1

X

HR1

X

R1

i

vi

vii

viii

R2R2

R2ii

R2

R2

Ln

Ln

J. Am. Chem. Soc. 2005, 127, 1603

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Diastereoselectivity ??Diastereoselectivity ??

J. Am. Chem. Soc. 2005, 127, 1603

31

Reason for DiastereoselectivityReason for Diastereoselectivity

J. Am. Chem. Soc. 2005, 127, 1603

32

Understanding Pauson-Khand-Type Reactions: [2+2+1]Understanding Pauson-Khand-Type Reactions: [2+2+1]

O

R1

R2

CO O

R1

R2

H

O O

R1

R2

H

O[RhCl(CO)L]x

+

4 5a 5bds 5a:5b = 19:1>

2 2 2

Oxidative Addition

CO

Insertion

Migratory InsertionReductiveElimination

Rh(I)Cl(CO)

O

R1

R2

RhCO

ClO

R1

R2

RhO

R1

Cl

CO

R2

H

RhO

R1

ClR2

CO

HO

O

R1

R2

H

O

45a

710a

8a

C

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Mechanistic AlternativesMechanistic Alternatives

CO

Rh(I)Cl(CO)

O

R1

R2

RhCO

ClO

R1

R2

RhO

R1

Cl

CO

R2

H

RhO

R1

ClR2

CO

HO

O

R1

R2

H

O

Oxidative AdditionInsertion

Migratory InsertionReductiveElimination

45a

710a

8a

CO

RhO

R1

Cl

CO

R2

CO

H

RhCl

CO

CO

O

R1

R2

Oxidative Addition

CO

Insertion

RhO

R1

ClR2

CO

HOCO

O

R1

R2

H

O

5aRh(I)Cl(CO)2

ReductiveElimination Migratory Insertion

11

9a

13a

C D

Low CO pressure High CO pressure

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What about Structural Alternatives?What about Structural Alternatives?

RhO

R1

CO

Cl

R2

H

RhO

R1

Cl

CO

R2

H

RhO

R1

Cl

CO

R2

H

RhO

R1

CO

Cl

R2

H

RhO

R1

Cl

CO

R2

CO

H

RhO

R1

CO

Cl

R2

CO

H

RhO

R1

Cl

CO

R2

CO

H

RhO

R1

CO

Cl

R2

CO

H

RhO

R1

Cl

CO

R2

CO

H

RhO

R1

CO

Cl

R2

CO

H

RhO

R1

Cl

CO

R2

CO

H

RhO

R1

CO

Cl

R2

CO

H

35

Reaction Energy ProfilesReaction Energy ProfilesLow CO Pressure High CO Pressure

Low diastereoselectivity High diastereoselectivity

36

Why is this reaction diastereoselective?Why is this reaction diastereoselective?

RhO

R1

Cl

CO

R2

CO

H

RhO

R1

Cl

CO

R2

CO

H

O

R1

R2

H

Rh

Cl

CO

COO

R1

R2

H

Rh

Cl

CO

CO

-0.510.34

-0.08 -0.30

11-TSa

0.06-0.35

0.11-0.38

11-TSb

Partial Charge Analysis

Syn-Product forms by (+)-directed polarization.

Anti-Product forms by (-)-directed polarization.

37

What is the physical basis of the new rule?What is the physical basis of the new rule?

38

What is the physical basis of the new rule?What is the physical basis of the new rule?

39

But, can we predict new chemistry?But, can we predict new chemistry?

Diastereoselectivity is CO-pressure dependent!

O

H3C

1atm CO O

H3C H

O O

H3C H

O+

4 5a 5bds 5a:5b = 19:1>

2 2 2

O

H3C

reduced CO-pressureO

H3C H

O O

H3C H

O+

4 5a 5b

2 2 2

ds 5a:5b = 10:1< ????

[RhCl(CO)2]2

[RhCl(CO)2]2

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Precision in the Eyes of an Organic ChemistPrecision in the Eyes of an Organic Chemist

O

H3C

O

H3C H

O O

H3C H

OCat.

+

4 5a 5b

>

2 2 2

ds 5a:5b

19:1

Cat.

[Rh(CO)Cl(dppp)]2 0:100

Ar:CO

> 19:1[Rh(CO)Cl(dppp)]2 90:10 --[Rh(CO)Cl(dppp)]2 95:5

dppp: 1,3-bis(diphenylphosphino)propane

41

Hey – who said anything about phosphine?Hey – who said anything about phosphine?

O

H3C

O

H3C H

O O

H3C H

OCat.

+

4 5a 5b

>

2 2 2

ds 5a:5b

19:10:100

Ar:CO

11:190:10 6:195:5

[RhCl(CO)2]2

42

So, WHY is this happening?So, WHY is this happening?Low CO Pressure High CO Pressure

Low diastereoselectivity High diastereoselectivity

43

Does this make sense NOW?Does this make sense NOW?

O

H3C

O

H3C H

O O

H3C H

OCat.

+

4 5a 5b

>

2 2 2

ds 5a:5b

19:1

Cat.

[Rh(CO)Cl(dppp)]2 0:100

Ar:CO

> 19:1[Rh(CO)Cl(dppp)]2 90:10 --[Rh(CO)Cl(dppp)]2 95:5

dppp: 1,3-bis(diphenylphosphino)propane

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More PredictionsMore Predictions

O

H3C

syn

anti

Low CO High CO

27.59 26.57

28.82 33.56

O

Et

syn

anti

Low CO High CO

27.63 26.53

28.58 28.83

O

H3C

CF3

syn

anti

Low CO High CO21.58 22.21

25.72 23.72

O

F3C

CF3

syn

anti

Low CO High CO27.79 24.75

32.34 29.38

O

H3C

CH3

syn

anti

Low CO High CO26.42 28.77

27.79 29.24

Will Electron withdrawing groups on R1 reverse ds ??

No! But:

syn

anti

Low CO High CO30.12 31.80

26.38 30.35

O

O

O

H3C

O

C

syn

anti

Low CO High CO25.83 27.28

29.58 31.42

OH3CO

Can’t be made?

O

H2N

syn

anti

Low CO High CO25.14 25.48

25.78 29.41

O

Cl

O

F

syn

anti

Low CO High CO26.57 25.99

22.28 20.70

syn

anti

Low CO High CO30.95 26.54

26.73 25.33

Target:

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ConclusionsConclusions

Theoretical “Characters” can actually predict new stuff if they try hard.

The diastereoselectivity of Rh-catalyzed Pauson-Khand reaction is a rare example of a purely electronically driven stereo-control (close to no steric influence!).

“Spectator Ligands” are actually not really just spectators at all.

Organic Chemistry does not necessarily have to be synonymous with: Alchemy or Mindless Memorizing

46

Center for Catalysis at IU-BloomingtonCenter for Catalysis at IU-Bloomington

OrganicSynthesis

Andy Evans Jeff Johnston

Organometallic Catalyst Design

Dan Mindiola Ken Caulton

MolecularModeling

Mookie Baik

Rational Design of Well-Defined, Efficient and mechanistically fully understood Catalysts for Natural Product Synthesis,Polymerization and C-C/C-H activation.

Educational Goal: A new breed of chemists who can conduct high-level research in all three areas of Organic, Inorganic and Computational/Theoretical Research

47