varuna: an integrated modeling environment and database for quantum chemical simulations
DESCRIPTION
CICC - Chemical Informatics And Cyberinfrastructure Collaboratory Department of Chemistry & School of Informatics Indiana University Bloomington. Varuna: An Integrated Modeling Environment and Database for Quantum Chemical Simulations Chemical Prototype Projects. October 21, 2005 - PowerPoint PPT PresentationTRANSCRIPT
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
11
Cisplatin: Profiling an Anticancer DrugCisplatin: Profiling an Anticancer Drug
12
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
15
Reaction Energy ProfilesReaction Energy ProfilesLow CO Pressure High CO Pressure
Low diastereoselectivity High diastereoselectivity
16
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
20
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
25
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
26
EntropyEntropy
27
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
– ––
––
––
––– –
++
+++
++++
++
+
+
++
++ + +
++
++
–
–
–
––––
–––
–
–
28
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
30
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
33
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
34
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
40
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
44
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