Transcript of Molecular Simulation to build models for enzyme induced fit
- 1. http://www.bmdrc.org/ 02-393-9550, mskim@bmdrc.org 3 -
Molecular Simulation to build models for enzyme induced fit 2015 5
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- 2. Lab : B408 Phone : 02-2123-7739 Mail : ktno@yonsei.ac.kr
Homepage : http://www.csblab.or.kr Computational Systems Biology
Lab. Professor : Kyoung Tai No Computational Chemistry
Cheminformatics Solvation free energy, charge model, and
forcefields; gives concrete understanding and analysis tool for
further developments. Statistical analysis of multivariate chemical
feature space via machine learning techniques. Spectral similarity
Structural similarity Activity similarity Natural Product
Profiling&Networking Profiling natural product/metabolite in
high-throughput manner, revealing its biological activity.
Commercial available screening Database (12 Millions) PPI Screening
Library Development of PPI focused screening library (0.2 Millions)
Target-focused Library Design Pharmacophore Based Screening
Structure-based Pharmacophore screen Screen of protein Interaction
surface Ligand-based pharmacophore screen Virtual screening Virtual
hits Predicted binding mode ASN159 Hot Spot region GLU196 Hot Spot
region ASN159 GLN160 LYS154 GLU196 Hotspot binding region: Define
binding site Hydrogen bond region Biding Site Prediction Flora
Genesis System In silico Drug Design RESEARCH INTEREST
- 3. What is molecular Dynamics A computational microscope An
experiment on a computer A simulation of the classical mechanics of
atoms
- 4. GOOD Energy Calculation Function, Force Fields, for DGsystem
GOOD Simulation Method for DGsystem t1 t2 t3 t4 t5 t6 t7 t8 tn tn+1
tn+2 tn+3 S1 S2 S3 S4 S5 S6 S7 S8 Sn Sn+1 Sn+2 Sn+3 G1 G2 G3 G4 G5
G6 G7 G8 Gn Gn+1 Gn+2 Gn+3 Energy/Mechanics Based Design Time
Structure Free Energy
- 5. Systems in a Life System Atom 10-12 m Protein 10-9 m Cell
10-6 m Tissue 10-3 m Organ 100 m Organ System & Organism
Physiology Gene Networks Pathway Models Stochastic Models
Differential Equation Continuum Model Partial Diff. Eqn Systems
Model 10-6s Molecular Events ion channel gating 10-3s Diffusion
Cell signaling 100s Mobility 103s Mitosis 104s Protein Turnover
109s Human Lifetime Spatial and temporal levels encompassed by
biological systems
- 6. Protein-Protein Interaction Electron carriers of the SQR
complex. FADH2, iron-sulfur centers, heme b, and ubiquinone. We can
Observe Protein-Protein Interaction with MD
- 7. Induced fit model of enzyme
- 8. Speed Isnt Everything How accurate are molecular mechanics
force fields? - Clearly good enough for some biologically and
pharmacologically important applications Where are the weak points?
- Polarizability? Hydrogen bonds? Combinning rules? Can we Improve
the accuracy of todays force fields? - At what cost in execution
speed? Even negative results could provide biologically and
pharmacologically relevant insights
- 9. Research Interest Areas Force Fields SBFF CHARM AMMBER MMFF
Simulator Lammps Gaussian Schrdinger Application PPI Molecular
Modeling Eco Engineering Appropriate Tech Consilience Approach
- 10. Nature Process Mimetic Inter Particle Interaction Analysis
Modeling Prediction Commercial Product Inter Molecular PEF
Solvation Models QM calculations Statistical PEF Scoring Function,
.. Molecular Mechanics MD, MC, FEP Regression methods ANN, GFA
Statistical methods Bioinformatics Protein structure prediction
Drug design ADME/Tox prediction PK prediction
- 11. Force Field: Potential Energy Function: )(StructureE f
Potential Energy Function :PEF
- 12. 2 0 )( ddkEstretch )( 0 1 dd estretch eDE 2 0 )( kEbend
)cos(1 S S S kEtorsion Intra Molecular Motions and their PEF
- 13. Classification of Force Fields Classical FFs AMBER, CHARMm,
CVFF, ECEPP/2, Homans FF, Pullman (DNA) Second-generation FFs
CFF91, PCFF, CFF95, MMFF93, MM Water potential models (Flexible or
non-flexible, inclusion of ploarization or not ST2, TIP3, TIP4,
SPC, CVFF, OPLS COSMO, FDM, BEM, SMx, SFED Broadly applicable FFs
UFF, Dreiding FF, ESFF (Extensible systematic FF), ..
Special-purpose FFs Glass, Zeolite, sorption, Morphology, ..
- 14. For Small Organic molecules MM2 - For structure
determination of small organic molecules - Developed by Allinger at
U. Georgia - FF parameters are determined with spectroscopic data
MM3 - Accurate vibrational frequency than MM2 MMFF93: Merck
Molecular FF - Using QM calculation as constraints for FF
parameters fitting Tripos force field - For small organic molecules
Classification of FFs; Small Organic Molecules
- 15. CFF : Consistant FF (CFF91, PCFF, CFF95) - Contains both
Anharmonic term and cross terms CFF91- Hydrocarbons, Proteins,
protein-ligand PCFF- Polymer, organic materials CFF95-Biomolecules,
organic polymers - for small organics and liquid and solid
simulations Shortcomings of above force fields - inadequate for
inter molecular interaction - does not include electrostatic
interaction - van der Waals radii are too small Classification of
FFs; Small Organic Molecules
- 16. ECEPP, ECEPP/2 SBFF (Self Balance Force Field) Protein
structure, in torsional space (no stretching & bending) Harold
Scheraga at Cornell U, Kyoung Tai No at Yonsei U AMBER (Assisted
Model Building with Energy Refinement) Protein / Nucleic Acids,
Peter Kollman at UCSF CHARMM (Chemistry at HARvard using Molecular
Mechanics) Mainly for Protein, Martin Karplus at Havard GROMOS
(GROenigen MOlecular Simulation) van Gunsteren and Berendsen at ETH
Zurich. CVFF(Consistent-valence force field ) Dauber-Osguthorpe,
out-of-plane energy calculation included For amino acids, water,
and a variety of other functional groups Classification of FFs;
Biomolecules
- 17. Dreiding force field, 1st and 2nd period elements Goddard
at Caltec / Mayo at Biodesign / Olafson UFF (Universal Force Field)
Include most of elements in Periodic table Rappe at Colorado State
U. / Casewit at Calleo Scientific / Skiff at Shell Research
Classification of FFs; Broadly Used
- 18. Self-Balanced Force Field (SBFF) 1) accurate intra- and
inter-molecular Potential Energy Function (PEF), and 2) good
simulation algorithm that describes nature of the molecular
worlds.
- 19. Bioinformatics & Molecular Design Research Center
()
- 20. Bioinformatics & Molecular Design Research Center
()
- 21. 23 Lammps code is Object oriented which is very similar to
JAVA Lammps has a huge diversity of force-fields you can use, and
also you can define new force-fields. Which makes it seems good
candidate for BMDRC Object Oriented Lammps
- 22. 24 Generating Animation
- 23. 25 Practice 4 : Aluminum Uniaxial Tension
- 24. 26 This example script shows how to run an atomistic
simulation of uniaxial tensile loading of an aluminum single
crystal oriented in the direction. Practice 4 : Aluminum Uniaxial
Tension Data retrieval was denied due to Dr. Rajus Calculation
- 25. 27 Peptide solvation
- 26. 28 Result - Peptide solvation Lammps with Charmn force
field
- 27. PotentialE Conformational Space PotentialE Conformational
Space PotentialE Conformational Space PotentialE Conformational
Space Energy Minimization Normal Mode Analysis Molecular Dynamics
Monte Carlo Simulation Illustration Credit: M. Levitt 0.5kx2
X=X(t)
- 28. Length & Tome Scale of Molecular Motions Motion Length
(in A) Time (in fs) Bond Vibration 0.1 10 Water Hindered Rotation
0.5 1000 Surface Sidechain Rotation 5 105 Water Diffusion Motion 4
105 Buried Sidechain Libration 0.5 105 Hinge Bending of Chain 3 106
Buried Sidechain Rotation 5 1013 Allosteric Transition 3 1013 Local
Denaturation 7 1014 Values from McCammon & Harvey (1987) &
Eisenberg & Kauzmann
- 29. 32 Parallel Computation
- 30. 33 Result - Peptide solvation 72.105 74.11 1 THREAD 4
THREAD timesteps/s Comparison of serial & parallel calc Loop
time of 346.715 on 1 procs for 25000 steps with 2004 atoms 99.0%
CPU use with 1 MPI tasks x 1 OpenMP threads Performance: 0.019
ns/day 1284.129 hours/ns 72.105 timesteps/s Loop time of 337.334 on
4 procs for 25000 steps with 2004 atoms 99.2% CPU use with 1 MPI
tasks x 4 OpenMP threads Performance: 0.019 ns/day 1249.386
hours/ns 74.110 timesteps/s
- 31. 34 High Performance Computing(HPC) Cloud Platform Key Cloud
Properties Cloud HPC: Good & Evil Success Stories Features
& Opportunities
- 32. 35 High Performance Computing(HPC) Cloud Platform What
differentiates the Cloud from non-Cloud? Cloud is awesome Cloud is
OSSM
- 33. 36 High Performance Computing(HPC) Cloud Platform
- 34. 37 High Performance Computing(HPC) Cloud Platform What
kinds of clouds are there?
- 35. 38 High Performance Computing(HPC) Cloud Platform Cloud
gives an illusion of unlimited capacity Sounds useful for HPC!
- 36. 39 High Performance Computing(HPC) Cloud Platform Key Cloud
Properties Cloud HPC: Good & Evil Success Stories Features
& Opportunitie
- 37. 40 High Performance Computing(HPC) Cloud Platform 1. Works
even with limited budget. 2. Perfect for infrequent monster jobs.
3. Helps to reduce Time to Market. 4. Enables disaster-resiliency.
5. Reduces IT complexity. The Bright Side 1. Performance and
latency issues. 2. Data volume issues. 3. Vendor-related issues. 4.
Security concerns. 5. Cost-effectiveness concerns. The Dark
Side
- 38. 41 High Performance Computing(HPC) Cloud Platform Efficient
workload patterns?
- 39. 42 High Performance Computing(HPC) Cloud Platform We
probably dont want to use the Cloud if we have this*: * however,
the costs might not be our primary concern
- 40. 43 High Performance Computing(HPC) Cloud Platform Key Cloud
Properties Cloud HPC: Good & Evil Success Stories Features
& Opportunitie
- 41. 44 High Performance Computing(HPC) Cloud Platform Batch
Processing: New York Times and MapReduce - 4 TB raw images, 11M
PDFs, 100 Hadoop workers = $240 Data Processing: Morgridge
Institute for Research, gene indexing - 1M core-hours, high-memory
EC2 Spot instances: < $20K paid Simulations and Analysis:
Schrdinger (drug research) - 50K cores, 21M chemical compounds:
< $5K paid - (Amazon infrastructure value estimated at $20~40M)
HPC Cloud Case Studies
- 42. 45 Simulations and Analysis: Schrdinger (drug research)
High Performance Computing(HPC) Cloud Platform
- 43. 46 High Performance Computing(HPC) Cloud Platform
- 44. 47 High Performance Computing(HPC) Cloud Platform
- 45. 48 Novartis Uses AWS to Conduct 39 Years of Computational
Chemistry In 9 Hours High Performance Computing(HPC) Cloud Platform
http://youtu.be/oa-M9GcaDN0
- 46. Molecular modeling is the study of the geometry and
properties of molecules by computer-aided techniques. Molecular
modeling is a growing area in science & technology to explain
the phenomena at molecular level. visualize molecules study the
structure of molecules study the properties of a molecule compare
the structure and properties of molecules study interactions
between molecules study reaction mechanisms predict the structure
of molecules predict the properties of molecules predict reaction
mechanisms Molecular Modeling (Design)
- 47. Computer Aided Drug Design Receptor Structure Unkonwn
Receptor Structure Konwn Ligand Structure Unknown Combinatorial
Chemistry 3D Structure Generation De novo Design Receptor Based 3D
Searching Ligand Structure Known Pharmacophore Define QSAR
Structure Based Optimization Affinity Calculation
- 48. Computer Added Molecular Design Energy Mechanics Based
Design Research Subject Mechanics Based Model Simulation X, T, t, E
Expiments Analysis Prediction QM, E-FF, TD / MM, MC, MD Knowledge
Based Design DATA Analysis RULEs Prediction QSAR 13.
- 49. Plan Conclusion
- 50. Thank you