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Biochemie IV – Struktur und Dynamik von Biomolekülen II. (Mittwochs 8-10 h, INF 230, klHS) 30.4.Jeremy Smith: Intro to Molecular Dynamics Simulation. 7.5.Stefan.

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Presentation on theme: "Biochemie IV – Struktur und Dynamik von Biomolekülen II. (Mittwochs 8-10 h, INF 230, klHS) 30.4.Jeremy Smith: Intro to Molecular Dynamics Simulation. 7.5.Stefan."— Presentation transcript:

1 Biochemie IV – Struktur und Dynamik von Biomolekülen II. (Mittwochs 8-10 h, INF 230, klHS) 30.4.Jeremy Smith: Intro to Molecular Dynamics Simulation. 7.5.Stefan Fischer: Molecular Modelling and Force Fields Matthias Ullmann: Current Themes in Biomolecular Simulation Ilme Schlichting: X-Ray Crystallography-recent advances (I) Klaus Scheffzek: X-Ray Crystallography-recent advances (II). 4.6.Irmi Sinning: Case Study in Protein Structure Michael Sattler: NMR Applications in Structural Biology Jörg Langowski: Brownian motion basics Jörg Langowski: Single Molecule Spectroscopy Karsten Rippe: Scanning Force Microscopy Jörg Langowski: Single Molecule Mechanics Rasmus Schröder: Electron Microscopy Jeremy Smith: Biophysics, the Future, and a Party.

2 Universität Heidelberg Protein Computational Molecular Biophysics

3 IBM today will announce its intention to invest $100 million over the next five years to build Blue Gene, a supercomputer that will be 500 times faster than current supercomputing technology. Researchers plan to use the supercomputer to simulate the natural biological process by which amino acids fold themselves into proteins. (New York Times 12/06/99) IBM PLANS SUPERCOMPUTER THAT WORKS AT SPEED OF LIFE

4 Protein Folding Exploring the Folding Landscape

5 Uses of Molecular Dynamics Simulation: structure flexibility solvent effects chemical reactions ion channels thermodynamics (free energy changes, binding) spectroscopy NMR/crystallography

6 Atomic-Detail Computer Simulation Model System Molecular Mechanics Potential Energy Surface  Exploration by Simulation..

7 Model System set of atoms explicit/implicit solvent periodic boundary conditions Potential Function empirical chemically intuitive quick to calculate Tradeoff: simplicity (timescale) versus accuracy

8 Lysozyme in explicit water

9 2/8 MM Energy Function   l r q i q j

10 Newton’s Law: Potential Function  Force

11 Taylor expansion: Verlet’s Method

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13 Ensemble AverageObservable Statistical Mechanics 1 hour here1 hour here 1 hour here

14 Ergodic Hypothesis: MD Simulation:

15 Analysis of MD Configurations Averages Fluctuations Time Correlations

16 Molecular dynamics: Integration timestep - 1 femtosecond Set by fastest varying force. Accessible timescale about 10 nanoseconds. Bond vibrations - 1 fs Collective vibrations - 1 ps Conformational transitions - ps or longer Enzyme catalysis - microsecond/millisecond Ligand Binding - micro/millisecond Protein Folding - millisecond/second Timescales.

17 SOME EXAMPLES

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22 11 Sequences in 9 clades A1LEU PRO CYS ARG ILE LYS GLN PHE ILE ASN MET TRP GLN GLU VAL +2 B1 LEU PRO CYS ARG ILE LYS GLN ILE VAL ASN MET TRP GLN GLU VAL +2 C1 ILE PRO CYS ARG ILE LYS GLN ILE ILE ASN MET TRP GLN GLU VAL +2 D2 LEU PRO CYS ARG ILE LYS PRO ILE ILE ASN MET TRP GLN GLU VAL +2 E2LEU PRO CYS LYS ILE LYS GLN ILE ILE ASN MET TRP GLN GLY VAL +3 E3LEU PRO CYS LYS ILE LYS GLN ILE ILE LYS MET TRP GLN GLY VAL +4 F1LEU LEU CYS LYS ILE LYS GLN ILE VAL ASN LEU TRP GLN GLY VAL +2 G2LEU PRO CYS LYS ILE LYS GLN ILE VAL ARG MET TRP GLN ARG VAL +5 1A0LEU PRO CYS LYS ILE LYS GLN ILE VAL ASN MET TRP GLN ARG VAL +4 2A3LEU GLN CYS ARG ILE LYS GLN ILE VAL ASN MET TRP GLN LYS VAL +4 OC4ILE PRO CYS LYS ILE LYS GLN VAL VAL ARG SER TRP ILE ARG GLY +5 Does CD4-binding peptide have a similar structure in all strains of HIV-1 ?

23 Molecular Dynamics Simulation Setup Box dimensions: 53x40x40 Ǻ Explicit water molecules (TIP3P) (~8600 atoms) Explicit ions (Sodium and Chloride, 26 ions in total); physiological salt: 0.23M ~240 peptide atoms => approx atoms in total Uncharged system NPT ensemble: 300K, 1atm 5ns simulation time for each strain => 55ns total simulation time

24 Dihedral angles  

25 Surface electrostatic properties conserved.

26 Detection of Individual p53- Autoantibodies in Human Sera Cancer Biotechnology.

27 Rhodamine 6G

28 MR121 Fluorescence Quenching of Dyes by Trytophan Dye Quencher

29 Fluorescently labeled Peptide ?

30 Analysis r

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32 Strategy: QuenchedFluorescent Results: Healthy Person Serum Cancer Patient Serum

33 Protein Folding/Unfolding

34 Protein Folding Exploring the Folding Landscape

35 BSE cattle bovine spongiform encephalopathy scrapie sheep CWD elkchronic wasting disease TME mink transmissible mink encephalopathy kuru human CJD humanCreutzfeldt-Jakob disease sporadic genetic infectious vCJD humanvariant CJD GSS humanGerstmann-Sträussler-Scheinker disease FFI humanfatal familial insomnia Prion diseases of animal and man

36 Properties of the prion protein -The natural prion protein is encoded by a single exon as a polypeptide chain of about 250 to 260 amino acid residues. -Posttranslational modification: cleavage of a 22 (N-terminal) and 23 (C- terminal) residue signal sequence => about 210 amino acid residues -PrP contains a single disulfide bridge. -PrP contains 2 glycosylation sites. -PrP inserts into the cellular plasma membrane through a glycosyl- phosphatidyl-inositol anchor at the C-terminus.

37 Structure of the prion protein

38 Superimposed PrP structures The first image below shows the structure of part of the hamster and mouse PrP C molecules superimposed. The close similarity in the structures is obvious, as is the preponderance of alpha helical structure.

39 Location of human mutations The picture shows the position of various mutations important for prion disease development in humans modelled on the hamster structure PrP C. Many of these mutations are positioned such that they could disrupt the secondary structure of the molecule.

40 Mouse Prion Protein (PrP c ) NMR Structure

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43 Structure of PrP Sc The PrP Sc has a much higher  -sheet content.

44 Bundeshochleistungsrechner Hitachi SR8000-F1

45 IBM today will announce its intention to invest $100 million over the next five years to build Blue Gene, a supercomputer that will be 500 times faster than current supercomputing technology. Researchers plan to use the supercomputer to simulate the natural biological process by which amino acids fold themselves into proteins. (New York Times 12/06/99) IBM PLANS SUPERCOMPUTER THAT WORKS AT SPEED OF LIFE

46 Safety in Numbers

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50 Large-Scale Conformational Change

51 Structural Changes in Proteins: The Physical Problem ENERGY LANDSCAPE: high-dimensional, rugged. Need to find PATHWAY WITH LOWEST SADDLE POINT.

52 Conformational Pathways Navigate energy landscape to find continuous path of lowest free energy from one end point to the other. `

53 Thick filament Muscle Contraction of Myosin and Actin Sliding filaments….filaments…. Thin filament Z disc

54 ATP Hydrolysis by Myosin SONJA SCHWARZL STEFAN FISCHER

55 Power Stroke in Muscle Contraction.

56 End ss 2003


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