10/10/2011 1 MOLECULAR MODELING & IN SILICO DRUG DESIGN Amirhossein sakhteman Amirhossein sakhteman MOLECULAR MODELING AND In silico DRUG DESIGN 1-Benefits? 2- The levels of computations 3- Energy Minimization 4- MD and Monte-Carlo simulation 5- Homology modeling 6- Virtual screening 7- QSAR
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Molecular modeling & in silico drug design · 10/10/2011 1 MOLECULAR MODELING & IN SILICO DRUG DESIGN Amirhossein sakhteman MOLECULAR MODELING AND In silico DRUG DESIGN 1-Benefits?
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10/10/2011
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MOLECULAR MODELING & IN SILICODRUG DESIGN
Amirhossein sakhtemanAmirhossein sakhteman
MOLECULAR MODELING AND In silico DRUG DESIGN
1-Benefits? 2- The levels of computations 3- Energy Minimization 4- MD and Monte-Carlo simulation 5- Homology modeling 6- Virtual screening 7- QSAR
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R&D SPENDING UP, NEW DRUGS DOWN
Taken from http://www.newscientistjobs.com/biotech/ernstyoung/blues.jsp
DRUG DISCOVERY & DEVELOPMENT
Identify disease
Find a drug effectiveagainst disease protein(2-5 years)
Isolate proteininvolved in disease (2-5 years)
Preclinical testing(1-3 years)
Formulation &
Human clinical trials(2-10 years)
Scale-up
FDA approval(2-3 years)
The pharmaceutical industry is a high-riskindustry with very long development times and short product lifespans
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GENOMICS, PROTEOMICS & BIOPHARM.
HIGH THROUGHPUT SCREENING
Potentially producing many more targetsand “personalized” targets
Identify disease
Isolate protein
VIRTUAL SCREENING
COMBINATORIAL CHEMISTRY
Screening up to 100,000 compounds aday for activity against a target protein
Using a computer topredict activity
R idl d i t b Find drug
Preclinical testing
MOLECULAR MODELING
IN VITRO & IN SILICO ADME MODELS
Rapidly producing vast numbersof compounds
Computer graphics & models help improve activity
Tissue and computer models begin to replace animal testing
INSILICO METHODS IN DRUG DISCOVERY
Molecular docking Virtual High through put screening Virtual High through put screening.
Drug receptor Interactions;MD simulations; Drug receptor Interactions;MD simulations; Docking studies, pharmacophore search, etc.
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FOUR LEVELS OF THEORY IN COMPUTATIONS
Ab initio DFT Quantum Mechanics DFT Semiempirical Empirical
Quantum Mechanics
Molecular Mechanics
QM: SCHRODINGER’S EQUATION
ˆ - Hamiltonian operator
H Eˆ H
ˆ H ˆ T ˆ V
Gravity?
2
2mi
2
i
N
Ceie j
ri rji j
N
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ELECTRONIC SCHRODINGER EQUATION
Solutions:(r ) cm m (r )
F
, the basis set, are of a known form Need to determine coefficients (cm)
Wavefunctions gives probability of finding electrons in space (e. g. s,p,d and f orbitals)
( ) m m ( )
m
m(r )
Molecular orbitals are formed by linear combinations of electronic orbitals (LCAO)
HYDROGEN MOLECULE
HOMO HOMO
LUMO
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AB INITIO
Hartree Fock (HF) Hartree Fock (HF) No experimental datra Calculation of hamiltonian for each electron For small molecules Gaussian Gamess
DENSITY FUNCTION
Energy depends to density of the electron Energy depends to density of the electron Kohn-Sham method For energy calculations in semiconductors, insulators Carbon nanotubes
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SEMIEMPIRICAL (E-E INTERACTIONS)
CNDO (Complete Neglect of Differential Overlap) CNDO (Complete Neglect of Differential Overlap) MNDO (Modified Neglect of Differential Overlap) PCILO AM1 PM3
MOLECULAR MECHANICS
Bonding Non-bonding
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LEONAED-JONES
MM FORCE FIELDS
AMBER(Assisted Model Building and Energy Refinement)
CHARMM CHARMM (Chemistry at HARvard Macromolecular Mechanics)
Gromos OPLS CVFF MM
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MOLECULAR MODELING AND In silico DRUG DESIGN
1-The benefits? 2- The levels of computations 3- Energy Minimization 4- MD and Monte-Carlo simulation 5- Homology modeling 6- Virtual screening 7- QSAR
ENERGY MINIMIZATIONENERGY MINIMIZATION
Local minimum vs global minimumg Many local minima; only ONE global minimum Methods: Newton-Raphson (block diagonal), steepest
descent, conjugate gradient, others.
global minimumglobal minimum
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POTENTIAL ENERGY SURFACEPOTENTIAL ENERGY SURFACE
maximasaddle point
minimum
MOLECULAR MODELING AND In silico DRUG DESIGN
1-The benefits? 2- The levels of computations 3- Energy Minimization 4- MD and Monte-Carlo simulation 5- Homology modeling 6- Virtual screening 7- QSAR
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MOLECULAR DYNAMICS SIMULATION
F = ma/ 2 / 2 F = ma = −dE/dr = m.d2r/dt2
r(t+∆t)= r(t) + V∆t + a ∆t2/2
To find the stable conformation of a system To study residue distances
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MONTE-CARLO SIMULATION
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PARALLEL COMPUTING: UNIX BASED OS
Drug Design and Discovery for Developing Countries, 3-5th July, 2008
Submit input files and distribute jobs to several clusters on Grid environment
Receive input files from Hawk and run jobs on each assigned nodes
rom
ng ed
Output files generated and uploaded to Hawk
d and k
Cluster B Cluster A
Grid environment
Input files
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Linus TorvaldsBill Gates
PARALLEL COMPUTING: OS
Bill Gates
Steve Jobs
MOLECULAR MODELING AND In silico DRUG DESIGN
1-The benefits? 2- The levels of computations 3- Energy Minimization 4- MD and Monte-Carlo simulation 5- Homology modeling 6- Virtual screening 7- QSAR
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10.10.2011
- The form of restraints was obtained from a statistical analysis relied on a database of 105 family alignments that included 416 proteins with known 3D structure [Šali & Overington, 1994]
Alignment file: Can be prepare by ModellerDSPrimeClustalwT-Cofee
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HOMOLOGY MODELING LACTATE DEHYDROGENASE ISOZYMES
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HOMOLOGY MODELIING OF GPCRS
MOLECULAR MODELING AND In silico DRUG DESIGN
1-The benefits? 2- The levels of computations 3- Energy Minimization 4- MD and Monte-Carlo simulation 5- Homology modeling 6- Virtual screening 7- QSAR