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1 Laboratoire d Ingénierie et de Modélisation Moléculaire 2 Institut Curie Université Paris-Sud 91405 Orsay SIMULATIONS DE REPLIEMENT DE CHAÎNES POLYPEPTIDIQUES.

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Presentation on theme: "1 Laboratoire d Ingénierie et de Modélisation Moléculaire 2 Institut Curie Université Paris-Sud 91405 Orsay SIMULATIONS DE REPLIEMENT DE CHAÎNES POLYPEPTIDIQUES."— Presentation transcript:

1 1 Laboratoire d Ingénierie et de Modélisation Moléculaire 2 Institut Curie Université Paris-Sud 91405 Orsay SIMULATIONS DE REPLIEMENT DE CHAÎNES POLYPEPTIDIQUES David PERAHIA 1 Charles ROBERT 1 Liliane MOUAWAD 2

2 Primary structure 20 different types of amino acid residues aliphatic side chains aromatic side chains sulfur containing side chains aliphatic hydroxyl side chains basic side chains acidic side chains and their amide derivatives

3 Secondary structure helix strands

4 Tertiary structure Different architectures only Mixed myoglobin retinol-binding protein triosephosphate isomerase Mixed triosephosphate isomerase

5 Quaternary structure hemoglobin coat of poliovirus

6 Objectives: Find the native structure from the sequence information Find metastable structures Large scale exploration of the conformational space around the native structure Folding kinetics Prerequisits: Simple model in order to perform very fast calculations Realistic force field conformationel space extremely large native structure should correspond to an energy minimum

7 A SIMPLE MODEL 2 points per residue ser ala thr tyr ala leu ile Center of mass of side chains C atoms

8 interactions between pseudo-atoms 1 2 3 4 C C C C C C C C C C

9 Statistical force field C 2 – C 3 Ile C 1 - C 2 Ile Histogram 1 2 C C C C 3 1230 PDB X-ray structures with sequence identity < 20%, and atomic resolution < 2 Å

10 Force Field w2w2 w1w1 w3w3 w4w4 w5w5 w6w6 w7w7 w8w8 w9w9 w 10 w 11

11 Molecular dynamics simulated annealing simulations 2000K 300K 800K folded conformations linear conformations

12 Contributions of C C and C - C interactions 1a32 1r69 rmsd E(decoy)-E(X-ray) total C C C C C - C C - C

13 ENERGY PARAMETER OPTIMIZATION ALGORITHM energy parameter set error rate function R 0 Assignment of parameters Randomly pick a parameter Assign a random value to it new energy parameter set and error rate function R 1 if R 1 < R 0 or (mean of energy variations of decoys with respect to native energy) > 0 yes norestore the previous parameters no evolution of R stop

14 Objectifs immédiats Optimiser les paramètres sur une grande variété de structures de protéines Recherche dune fonction dénergie optimale Recherche dune stratégie de repliement optimale

15

16 native 4.17 Å 3.98 Å 4.60 Å


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