Computational Modelling of Chemical and Biochemical Reactivity Chemistry Ian Williams.

Slides:



Advertisements
Similar presentations
Time averages and ensemble averages
Advertisements

Simulazione di Biomolecole: metodi e applicazioni giorgio colombo
Introduction to Computational Chemistry NSF Computational Nanotechnology and Molecular Engineering Pan-American Advanced Studies Institutes (PASI) Workshop.
Ab Initio and Effective Fragment Potential Dynamics Heather M. Netzloff and Mark S. Gordon Iowa State University.
Molecular Biophysics III – dynamics
Molecular Dynamics at Constant Temperature and Pressure Section 6.7 in M.M.
Transfer FAS UAS SAINT-PETERSBURG STATE UNIVERSITY COMPUTATIONAL PHYSICS Introduction Physical basis Molecular dynamics Temperature and thermostat Numerical.
© copyright 2013-William A. Goddard III, all rights reservedCh120a-Goddard-L06 Ch121a Atomic Level Simulations of Materials and Molecules William A. Goddard.
ChE 452 Lecture 16 Quantum Effects In Activation Barriers 1.
A Digital Laboratory “In the real world, this could eventually mean that most chemical experiments are conducted inside the silicon of chips instead of.
The Hybrid Quantum Trajectory/Electronic Structure DFTB-based Approach to Molecular Dynamics Lei Wang Department of Chemistry and Biochemistry University.
Potential Energy Surface. The Potential Energy Surface Captures the idea that each structure— that is, geometry—has associated with it a unique energy.
Introduction to Molecular Orbitals
Photoactivation of the Photoactive Yellow Protein chemistry department Imperial Colege London London SW7 2AZ United Kingdom Gerrit Groenhof, Berk Hess,
The Protein Folding Problem David van der Spoel Dept. of Cell & Mol. Biology Uppsala, Sweden
Case Studies Class 5. Computational Chemistry Structure of molecules and their reactivities Two major areas –molecular mechanics –electronic structure.
2. Modeling of small systems Building the model What is the optimal conformation of a molecule? What is the relative energy of a given conformation? What.
Modeling the Growth of Clusters and Aerosols from First Principles: How do We Understand Feedback Systems in a Warming Climate? George C. Shields Department.
1 Exploring the Possible Pathways of DNA Polymerase λ’s Nucleotidyl Transfer Reaction Meredith Foley Schlick Lab Retreat -- February 9, 2008 Chemistry.
Computing Resources Joachim Wagner Overview CNGL Cluster MT Group Cluster School Cluster Desktop PCs.
Potential Energy Surfaces
Water cluster- silica collision Water cluster, 104 H 2 O Simulation time, 17ps NVE simulations O 1560 Si atoms Molecular mass g/mole.
Bioinf. Data Analysis & Tools Molecular Simulations & Sampling Techniques117 Jan 2006 Bioinformatics Data Analysis & Tools Molecular simulations & sampling.
Introduction. What is Computational Chemistry?  Use of computer to help solving chemical problems Chemical Problems Computer Programs Physical.
Geometry Optimisation Modelling OH + C 2 H 4 *CH 2 -CH 2 -OH CH 3 -CH 2 -O* 3D PES.
‘Tis not folly to dream: Using Molecular Dynamics to Solve Problems in Chemistry Christopher Adam Hixson and Ralph A. Wheeler Dept. of Chemistry and Biochemistry,
Lectures Introduction to computational modelling and statistics1 Potential models2 Density Functional.
Algorithms and Software for Large-Scale Simulation of Reactive Systems _______________________________ Ananth Grama Coordinated Systems Lab Purdue University.
ChE 452 Lecture 24 Reactions As Collisions 1. According To Collision Theory 2 (Equation 7.10)
Computational Solid State Physics 計算物性学特論 第8回 8. Many-body effect II: Quantum Monte Carlo method.
Deca-Alanine Stretching
Basic Monte Carlo (chapter 3) Algorithm Detailed Balance Other points.
Work Done by a Varying Force (1D). Force Due to a Spring – Hooke’s Law.
Molecular Dynamics Simulation
Computational Chemistry Molecular Mechanics/Dynamics F = Ma Quantum Chemistry Schr Ö dinger Equation H  = E 
Water layer Protein Layer Copper center: QM Layer Computing Redox Potentials of Type-1 Copper Sites Using Combined Quantum Mechanical/Molecular Mechanical.
The Birmingham Environment for Academic Research Setting the Scene Peter Watkins, School of Physics and Astronomy (on behalf of the Blue Bear team)
Photoactivation of the Photoactive Yellow Protein chemistry department Imperial Colege London London SW7 2AZ United Kingdom Gerrit Groenhof, Berk Hess,
Computer simulations and the Laplace demon Alessandro Laio, SISSA (Trieste) Capability to predict the futureCapability to predict the future Lots of demon-like.
Molecular Dynamics simulations
Molecular simulation methods Ab-initio methods (Few approximations but slow) DFT CPMD Electron and nuclei treated explicitly. Classical atomistic methods.
Molecular Dynamics Simulations of Compressional Metalloprotein Deformation Andrew Hung 1, Jianwei Zhao 2, Jason J. Davis 2, Mark S. P. Sansom 1 1 Department.
Advanced methods of molecular dynamics 1.Monte Carlo methods 2.Free energy calculations 3.Ab initio molecular dynamics 4.Quantum molecular dynamics 5.Trajectory.
Advanced methods of molecular dynamics 1.Monte Carlo methods 2.Free energy calculations 3.Ab initio molecular dynamics 4.Quantum molecular dynamics III.
Lecture 10. Chemical Bonding. H 2 Molecule References Engel, Ch. 12 Ratner & Schatz, Ch. 10 Molecular Quantum Mechanics, Atkins & Friedman (4th ed. 2005),
Role of Theory Model and understand catalytic processes at the electronic/atomistic level. This involves proposing atomic structures, suggesting reaction.
Advanced methods of molecular dynamics 1.Monte Carlo methods 2.Free energy calculations 3.Ab initio molecular dynamics 4.Quantum molecular dynamics 5.Trajectory.
Statistical Mechanics for Free Energy Calculations
Multicore Applications in Physics and Biochemical Research Hristo Iliev Faculty of Physics Sofia University “St. Kliment Ohridski” 3 rd Balkan Conference.
Lecture 12. Potential Energy Surface
Parastou Sadatmousavi§, & Ross C. Walker*
Introduction to Structural Dynamics
ReMoDy Reactive Molecular Dynamics for Surface Chemistry Simulations
Maintaining Adiabaticity in Car-Parrinello Molecular Dynamics
Understanding Biomolecular Systems
Algorithms and Software for Large-Scale Simulation of Reactive Systems
Masoud Aryanpour & Varun Rai
Chemistry Thermodynamics
Molecular Mechanics Molecular Dynamics.
1.
Austin Huang, Collin M. Stultz  Biophysical Journal 
Molecular simulation methods
Lesson 6-1 Energy and Power Technologies
Algorithms and Software for Large-Scale Simulation of Reactive Systems
Classical Mechanics Pusan National University
Classical Principles of Electromagnetism
Protein Grabs a Ligand by Extending Anchor Residues: Molecular Simulation for Ca2+ Binding to Calmodulin Loop  Chigusa Kobayashi, Shoji Takada  Biophysical.
Energy Review.
Car Parrinello Molecular Dynamics
Materials Oriented Modelling - Catalysis and Interactions in Solid and Condensed Phases Stockholm, Sweden on 28 June - 1 July, 2009.
Presentation transcript:

Computational Modelling of Chemical and Biochemical Reactivity Chemistry Ian Williams

Bath English Lake District Buttermere Borrowdale Honister Pass Youth Hostel + car park

B C D T E W G R W ‡ ‡ ‡ ‡ ‡ ‡ ‡ ‡ A Chemical Landscape: mountain pass ‡  transition state  E peak  E pass geometry the transition state ‡ of a molecular system controls the direction and rate of chemical change between reactants R and products P Map coordinates: longitude & latitude Contour lines: vertical height  potential energy (gravitational)

glycoprotein O cell sialic acid 

Relenza and Tamiflu stop the virus from budding out of the cell

neuraminidase 37 atoms 85 atoms quantum mechanics: Schrödinger equation

37 atoms 85 atoms quantum mechanics: Schrödinger equation Neuraminidase 5668 atoms

classical mechanics: Hooke & Coulomb 37 atoms 85 atoms quantum mechanics: Schrödinger equation 5668 atoms Neuraminidase 5668 atoms Neuraminidase in water: atoms

MMQM QM/MM “QM/MM” E total = E QM + E MM + E QM/MM quantumclassicalinteraction QM only too many electrons MM only cannot treat electronic reorganisation Quantum mechanicsMolecular mechanics

‡ ‡ ‡ ‡ ‡ ‡ ‡ TYR ASP GLU ‡ ‡ ‡ ‡ ‡‡ ‡ ‡ ‡ ‡ ‡ ‡ ~36 CPU hrs per point on 2D projection of ~10 5 D QM/MM PE surface

Elaboration of series of MD simulations along an appropriate coordinate using a biasing potential Molecular dynamics: Newton’s Laws T = 300K QM/MM potential for 50,000 atoms within periodic boundary conditions A typical MD trajectory within an “umbrella sampling” window takes ~10 CPU days to perform 20 ps equilibration + 20 ps production run to average over the sampled configurations  Potential of Mean Force  Free energy changes corresponding to chemical kinetics and equilibria

timescale Pople: systematic improvement of QM methods electron correlation basis set systematic improvement of QM/MM MD simulations requires simultaneous advances in multiple dimensions, each one being computationally demanding MM atoms degrees of freedom exchange /correlation functional

Chemistry machine room: ~ 30 x Pentium PCs running Linux 3 x dual 2.2 GHz AMD Opteron, 2 x 4 Gb + 1 x 8 Gb memory, 2 x 80 Gb + 1 x 300 Gb disk IHW group’s computing resources at Bath BUCS machine room: Share of Skein (HEFCE JREI, May 2002) Upgrade 2007 with EPSRC funding (awarded) Further BBSRC pending decision Pauling (BBSRC, June 2005) Linux (SUSE 9) cluster with: 1 x Front-end dual 2.2 GHz AMD Opteron, 2 Gb memory, 1 Tb RAID 5 32 x (dual 2.4 GHz CPU, 4 Gb memory, 120 Gb disk) 4 x (dual-core dual 2.2 GHz CPU, 8 Gb memory, 120 Gb disk) Gigabit interconnect Thank you for listening!