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Computer Modeling Dr. GuanHua CHEN Department of Chemistry University of Hong Kong http://yangtze.hku.hk/lecture/comput05-06.ppt
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Computational Chemistry Quantum Chemistry Schr Ö dinger Equation H = E Molecular Mechanics F = Ma F : Force Field Bioinformatics
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Computational Chemistry Industry CompanySoftware Gaussian Inc.Gaussian 94, Gaussian 98 Schrödinger Inc.Jaguar WavefunctionSpartanQ-Chem AccelrysInsightII, Cerius 2 HyperCubeHyperChem Informatix Celera Genomics Applications: material discovery, drug design & research R&D in Chemical & Pharmaceutical industries in 2000: US$ 80 billion Bioinformatics: Total Sales in 2001 US$ 225 million Project Sales in 2006US$ 1.7 billion
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Vitamin C C60 Cytochrome c heme OH + D 2 --> HOD + D energy
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Quantum Chemistry Methods Ab initio Molecular Orbital Methods Hartree-Fock, Configurationa Interaction (CI) MP Perturbation, Coupled-Cluster, CASSCF Density Functional Theory Semiempirical Molecular Orbital Methods Huckel, PPP, CNDO, INDO, MNDO, AM1 PM3, CNDO/S, INDO/S
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H E Schr Ö dinger Equation Hamiltonian H = ( h 2 /2m h 2 /2m e ) i i 2 i e 2 /r i + Z Z e r i j e 2 /r ij Wavefunction Energy One-electron terms: ( h 2 /2m h 2 /2m e ) i i 2 i e 2 /r i Two-electron term: i j e 2 /r ij
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1. Hartree-Fock Equation F i = i i F Fock operator i the i-th Hartree-Fock orbital i the energy of the i-th Hartree-Fock orbital Hartree-Fock Method Orbitals
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2. Roothaan Method (introduction of Basis functions) i = k c ki k LCAO-MO { k } is a set of atomic orbitals (or basis functions) 3. Hartree-Fock-Roothaan equation j ( F ij - i S ij ) c ji = 0 F ij i F j S ij i j 4. Solve the Hartree-Fock-Roothaan equation self-consistently (HFSCF)
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Graphic Representation of Hartree-Fock Solution 0 eV Ionization Energy Electron Affinity
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Basis Set i = p c ip p { k } is a set of atomic orbitals (or basis functions) STO-3G, 3-21G, 4-31G, 6-31G, 6-31G*, 6-31G** ------------------------------------------------------------------------------------- complexity & accuracy # HF/6-31G(d) Route section water energy Title 0 1 Molecule Specification O -0.464 0.177 0.0 (in Cartesian coordinates H -0.464 1.137 0.0 H 0.441 -0.143 0.0 A Gaussian Input File for H 2 O
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Gaussian type functions g ijk = N x i y j z k exp(- r 2 ) (primitive Gaussian function) p = u d up g u (contracted Gaussian-type function, CGTF) u = {ijk}p = {nlm}
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Electron Correlation: avoiding each other The reason of the instantaneous correlation: Coulomb repulsion (not included in the HF) Beyond the Hartree-Fock Configuration Interaction (CI) Perturbation theory Coupled Cluster Method Density functional theory
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Configuration Interaction (CI) + + …
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Single Electron Excitation or Singly Excited
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Double Electrons Excitation or Doubly Excited
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Singly Excited Configuration Interaction (CIS): Changes only the excited states +
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Doubly Excited CI (CID): Changes ground & excited states + Singly & Doubly Excited CI (CISD): Most Used CI Method
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Full CI (FCI): Changes ground & excited states + + +...
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H = H 0 + H’ H 0 n (0) = E n (0) n (0) n (0) is an eigenstate for unperturbed system H’ is small compared with H 0 Perturbation Theory
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Moller-Plesset (MP) Perturbation Theory The MP unperturbed Hamiltonian H 0 H 0 = m F(m) where F(m) is the Fock operator for electron m. And thus, the perturbation H ’ H ’ = H - H 0 Therefore, the unperturbed wave function is simply the Hartree-Fock wave function . Ab initio methods: MP2, MP3, MP4
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= e T (0) (0) : Hartree-Fock ground state wave function : Ground state wave function T = T 1 + T 2 + T 3 + T 4 + T 5 + … T n : n electron excitation operator Coupled-Cluster Method = T1T1
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CCD = e T 2 (0) (0) : Hartree-Fock ground state wave function CCD : Ground state wave function T 2 : two electron excitation operator Coupled-Cluster Doubles (CCD) Method = T2T2
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Complete Active Space SCF (CASSCF) Active space All possible configurations
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Density-Functional Theory (DFT) Hohenberg-Kohn Theorem: Phys. Rev. 136, B864 (1964) The ground state electronic density (r) determines uniquely all possible properties of an electronic system (r) Properties P (e.g. conductance), i.e. P P[ (r)] Density-Functional Theory (DFT) E 0 = h 2 /2m e ) i dr e 2 (r) / r 1 dr 1 dr 2 e 2 /r 12 + E xc [ (r) ] Kohn-Sham Equation Ground State : Phys. Rev. 140, A1133 (1965) F KS i = i i F KS h 2 /2m e ) i i 2 e 2 / r 1 j J j + V xc V xc E xc [ (r) ] / (r) A popular exchange-correlation functional E xc [ (r) ] : B3LYP
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B3LYP/6-311+G(d,p)B3LYP/6-311+G(3df,2p) RMS=21.4 kcal/molRMS=12.0 kcal/mol RMS=3.1 kcal/molRMS=3.3 kcal/mol B3LYP/6-311+G(d,p)-NEURON & B3LYP/6-311+G(d,p)-NEURON: same accuracy Hu, Wang, Wong & Chen, J. Chem. Phys. (Comm) (2003)
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Time-Dependent Density-Functional Theory (TDDFT) Runge-Gross Extension: Phys. Rev. Lett. 52, 997 (1984) Time-dependent system (r,t) Properties P (e.g. absorption) TDDFT equation: exact for excited states Isolated system Open system Density-Functional Theory for Open System Further Extension: X. Zheng, F. Wang & G.H. Chen (2005) Generalized TDDFT equation: exact for open systems
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Ground State Excited State CPU Time Correlation Geometry Size Consistent (CHNH,6-31G*) HFSCF 1 0 OK DFT ~1 CIS <10 OK CISD 17 80-90% (20 electrons) CISDTQ very large 98-99% MP2 1.5 85-95% (DZ+P) MP4 5.8 >90% CCD large >90% CCSDT very large ~100%
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Reactant Product Transition State: one negative frequency Reaction Coordinate Search for Transition State GG k e - G/RT
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#b3lyp/6-31G opt=qst2 test the first is the reactant internal coordinate 0 1 O H 1 oh1 H 1 oh1 2 ohh1 oh1 0.90 ohh1 104.5 The second is the product internal coordinate 0 1 O H 1 oh2 H 1 oh3 2 ohh2 oh2 0.9 oh3 10.0 ohh2 160.0 Gaussian Input File for Transition State Calculation
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Semiempirical Molecular Orbital Calculation Extended Huckel MO Method (Wolfsberg, Helmholz, Hoffman) Independent electron approximation Schrodinger equation for electron i H val = i H eff (i) H eff (i) = -(h 2 /2m) i 2 + V eff (i) H eff (i) i = i i
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LCAO-MO: i = r c ri r s ( H eff rs - i S rs ) c si = 0 H eff rs r H eff s S rs r s Parametrization: H eff rr r H eff r minus the valence-state ionization potential (VISP)
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Atomic Orbital Energy VISP ---------------e 5 -e 5 ---------------e 4 -e 4 ---------------e 3 -e 3 ---------------e 2 -e 2 ---------------e 1 -e 1 H eff rs = ½ K (H eff rr + H eff ss ) S rs K:1 3
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CNDO, INDO, NDDO (Pople and co-workers) Hamiltonian with effective potentials H val = i [ -(h 2 /2m) i 2 + V eff (i) ] + i j>i e 2 / r ij two-electron integral: (rs|tu) = CNDO: complete neglect of differential overlap (rs|tu) = rs tu (rr|tt) rs tu rt
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INDO: intermediate neglect of differential overlap (rs|tu) = 0 when r, s, t and u are not on the same atom. NDDO: neglect of diatomic differential overlap (rs|tu) = 0 if r and s (or t and u) are not on the same atom. CNDO, INDO are parametrized so that the overall results fit well with the results of minimal basis ab initio Hartree-Fock calculation. CNDO/S, INDO/S are parametrized to predict optical spectra.
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MINDO, MNDO, AM1, PM3 (Dewar and co-workers, University of Texas, Austin) MINDO: modified INDO MNDO: modified neglect of diatomic overlap AM1: Austin Model 1 PM3: MNDO parametric method 3 *based on INDO & NDDO *reproduce the binding energy
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Relativistic Effects Speed of 1s electron: Zc / 137 Heavy elements have large Z, thus relativistic effects are important. Dirac Equation: Relativistic Hartree-Fock w/ Dirac-Fock operator; or Relativistic Kohn-Sham calculation; or Relativistic effective core potential (ECP).
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(1) Neglect or incomplete treatment of electron correlation (2) Incompleteness of the Basis set (3) Relativistic effects (4) Deviation from the Born-Oppenheimer approximation Four Sources of error in ab initio Calculation
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Quantum Chemistry for Complex Systems
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Quantum Mechanics / Molecular Mechanics (QM/MM) Method Combining quantum mechanics and molecular mechanics methods: QM MM
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Hamiltonian of entire system: H = H QM +H MM +H QM/MM Energy of entire system: E = E QM ( QM ) + E MM ( MM ) + E QM/MM ( QM/MM ) E QM/MM ( QM/MM ) = E elec ( QM/MM ) + E vdw ( MM ) + E MM-bond ( MM ) E QM ( QM ) + E elec ( QM/MM ) = H eff = - 1/2 i i 2 + ij 1/r ij - i Z /r i - i q /r i + i V v-b (r i ) + Z Z /r + Z q /r QM MM
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Quantum Chemist’s Solution Linear-Scaling Method: O(N) Computational time scales linearly with system size Time Size
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Linear Scaling Calculation for Ground State W. Yang, Phys. Rev. Lett. 1991 Divide-and-Conqure (DAC)
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Superoxide Dismutase (4380 atoms) York, Lee & Yang, JACS, 1996 Strain, Scuseria & Frisch, Science (1996): LSDA / 3-21G DFT calculation on 1026 atom RNA Fragment
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Liang, Yokojima & Chen, JPC, 2000 Linear Scaling Calculation for Excited State
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LDM-TDDFT: C n H 2n+2 Fast Multiple Method
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LODESTAR: Software Package for Complex Systems Characteristics : O(N) Divide-and-Conquer O(N) TDHF (ab initio & semiemptical) O(N) TDDFT CNDO/S-, PM3-, AM1-, INDO/S-, & TDDFT-LDM Light Harvesting System Nonlinear Optical
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Photo-excitations in Light Harvesting System II generated by VMD strong absorption: ~800 nm generated by VMD
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Carbon Nanotube
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Quantum mechanical investigation of the field emission from the tips of carbon nanotubes Zettl, PRL 2001 Zheng, Chen, Li, Deng & Xu, Phys. Rev. Lett. 2004
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Molecular Mechanics Force Field Bond Stretching Term Bond Angle Term Torsional Term Electrostatic Term van der Waals interaction Molecular Mechanics F = Ma F : Force Field
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Bond Stretching Potential E b = 1/2 k b ( l) 2 where, k b : stretch force constant l : difference between equilibrium & actual bond length Two-body interaction
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Bond Angle Deformation Potential E a = 1/2 k a ( ) 2 where, k a : angle force constant : difference between equilibrium & actual bond angle Three-body interaction
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Periodic Torsional Barrier Potential E t = (V/2) (1+ cosn ) where, V : rotational barrier : torsion angle n : rotational degeneracy Four-body interaction
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Non-bonding interaction van der Waals interaction for pairs of non-bonded atoms Coulomb potential for all pairs of charged atoms
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Force Field Types MM2Molecules AMBERPolymers CHAMMPolymers BIOPolymers OPLSSolvent Effects
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Algorithms for Molecular Dynamics Runge-Kutta methods: x(t+ t) = x(t) + (dx/dt) t Fourth-order Runge-Kutta x(t+ t) = x(t) + (1/6) (s 1 +2s 2 +2s 3 +s 4 ) t +O( t 5 ) s 1 = dx/dt s 2 = dx/dt [w/ t=t+ t/2, x = x(t)+s 1 t/2] s 3 = dx/dt [w/ t=t+ t/2, x = x(t)+s 2 t/2] s 4 = dx/dt [w/ t=t+ t, x = x(t)+s 3 t] Very accurate but slow!
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Algorithms for Molecular Dynamics Verlet Algorithm: x(t+ t) = x(t) + (dx/dt) t + (1/2) d 2 x/dt 2 t 2 +... x(t - t) = x(t) - (dx/dt) t + (1/2) d 2 x/dt 2 t 2 -... x(t+ t) = 2x(t) - x(t - t) + d 2 x/dt 2 t 2 + O( t 4 ) Efficient & Commonly Used!
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Goddard, Caltech Multiple Scale Simulation
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Large Gear Drives Small Gear G. Hong et. al., 1999
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Nano-oscillators Zhao, Ma, Chen & Jiang, Phys. Rev. Lett. 2003 Nanoscopic Electromechanical Device (NEMS)
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Computer-Aided Drug Design GENOMICS Human Genome Project
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Computer-aided drug design Chemical Synthesis Screening using in vitro assay Animal Tests Clinical Trials
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ALDOSE REDUCTASE Diabetes Diabetic Complications Glucose Sorbitol
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Design of Aldose Reductase Inhibitors Aldose Reductase Inhibitor
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Database for Functional Groups Descriptors: Electron negativity Volume
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Possible drug leads: ~ 350 compounds
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TYR48LYS77 HIS110 TRP111 PHE122 TYP219 TRP20 CYS298 LEU300 NADPH TRP79 VAL47 Aldose Reductase Active Site Structure Cerius2 LigandFit
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To further confirm the AR-ARI binding, We perform QM/MM calculations on drug leads. CHARMM 5'-OH, 6'-F, 7'-OH Binding energy is found to be –45 kcal / mol
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Docking of aldose reductase inhibitor Cerius2 LigandFit Aldose reducatse (4R)-6’-fluoro-7’-hydroxyl-8’-bromo-3’-methylspiro- [imidazoli-dine-4,4’(1’H)-quinazoline]-2,2’,5(3’H)-trione Inhibitor Hu & Chen, 2003
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Interaction energy between ligand and protein Quantum Mechanics/Molecular Mechanics (QM / MM) Hu & Chen, 2003
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a:Inhibitor concentration of inhibit Aldose Reductase; b: the percents of lower sciatic nerve sorbitol levels c: interaction with AR in Fig. 4
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Our Design Strategy QSAR determination & prediction (Neural Network) Docking (Cerius2) QM / MM (binding energy) ?
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Software in Department 1. Gaussian 2. Insight II CHARMm: molecular dynamics simulation, QM/MM Profiles-3D: Predicting protein structure from sequences SeqFold: Functional Genomics, functional identification of protein w/ sequence and structure comparison NMR Refine: Structure determination w/ NMR data 3. Games 4. HyperChem 5. AutoDock(docking) 6. MacroModel 6. In-House Developed Software LODERSTAR Neural Network for QSAR Monte Carlo & Molecular Dynamics
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