1. Structural Bioinformatics Elodie Laine Master BIM-BMC Semester 3, 2013-2014 Genomics of Microorganisms, UMR 7238, CNRS-UPMC e-documents: http://www.lgm.upmc.fr/laine/STRUCThttp://www.lgm.upmc.fr/laine/STRUCT e-mail: elodie.laine@upmc.frelodie.laine@upmc.fr

2. Elodie Laine – 18.12.2013

3. Protein structure Peptidic bond aRginine lysine (K) aspartate (D) glutamate (E) asparagiNe glutamine (Q) Cysteine Methionine Histidine Serine Threonine Valine Leucine Isoleucine phenylalanine (F) tYrosine tryptophan (W) Glycine Alanine Proline 20 amino acids one amino-acid Elodie Laine – 18.12.2013

4. Protein structure …QNCQLRPSGWQCRPTRGDCDLPEFCPGDSSQCPDVSLGDG… 1 protein = 1 polypeptidic chain ~10’s to ~1000’s of amino acid residues 1 st level of organisation : primary structure Covalent bonds Elodie Laine – 18.12.2013

5. Protein structure β-sheet α-helix 2 nd level of organisation : secondary structure Other elements: 3 10 helix > turns > loops > random coil Backbone-backbone weak chemical bonds Elodie Laine – 18.12.2013

6. Protein structure β-sheet α-helix 2 nd level of organisation : secondary structure Other elements: 3 10 helix > turns > loops > random coil Weak chemical bonds backbone-backbone α-helix β-sheet Elodie Laine – 18.12.2013

7. Protein structure 3 rd level of organisation : tertiary structure A protein sequence adopts a particular fold in solution, which corresponds to a free energy minimum Types of non-covalent interactions: salt bridges hydrogen bonds hydrophobic contacts pi-pi stacking… Elodie Laine – 18.12.2013

8. Protein structure 4 th level of organisation : quaternary structure Arrangements of domains within a protein or of proteins within a macro- molecular assembly Elodie Laine – 18.12.2013

9. Protein structure: a brief history Space-filling model of the α-helix Pauling & Corey (1951) PNAS 3-Dimensional structure of myoglobin Kendrew et al. (1958) Nature Elodie Laine – 18.12.2013

10. Sequence-structure-function paradigm Tumour-supressor protein p53’s disordered segments help it interact with hundreds of partners. Dynamics Elodie Laine – 18.12.2013

11. Protein functions pumps drugs and poisons out of cells sensor of light hormones breaks down food in the stomach recognizes foreign objects copies the information held in a DNA strand stores iron ions inside cells Rotary motor powered by electrochemical energy supports organs and tissues forms structural girders Elodie Laine – 18.12.2013

12. The geometric configuration of a protein’s native state determines its macroscopic properties, behaviour and function. Protein folding prediction problem The number of possible conformations for a given protein is astronomical. ex: 100aa, 3 conf/aa => 5 10 47 conf 1 fold/10 -13 sec => 10 27 years (age of Universe 10 10 years) And yet protein do fold spontaneously in a matter of milliseconds. How can it be ? Hydrophobic- polar (HP) 2D- lattice model Levinthal’s paradox Elodie Laine – 18.12.2013

13. Protein dynamics spatio-temporal scales Elodie Laine – 18.12.2013 Native state formation

14. Algorithms in structural bioinformatics: what for ?  To predict protein structures experimental data analysis and 3-dimensional model building secondary or tertiary structure prediction based on the sequence  To predict protein structures experimental data analysis and 3-dimensional model building secondary or tertiary structure prediction based on the sequence known protein sequences protein sequences with function known protein structures increasing gap Elodie Laine – 18.12.2013

15. Algorithms in structural bioinformatics: what for ?  To compare protein structures classification of proteins (divergent/convergent evolution) identification of active sites, functional motifs or binding sites  To compare protein structures classification of proteins (divergent/convergent evolution) identification of active sites, functional motifs or binding sites Elodie Laine – 18.12.2013  To predict protein structures Phylogenetic tree of 38 CATH Architecture domain structures

16. Algorithms in structural bioinformatics: what for ?  To compare protein structures Elodie Laine – 18.12.2013  To predict protein structures  To simulate protein motions atomic-level desciption of the mechanisms underlying protein activity characterization of intermediate conformations that can be targetd by drugs  To simulate protein motions atomic-level desciption of the mechanisms underlying protein activity characterization of intermediate conformations that can be targetd by drugs

17. Algorithms in structural bioinformatics: what for ?  To compare protein structures Elodie Laine – 18.12.2013  To predict protein structures  To simulate protein motions  To characterize protein interactions protein interaction sites identification and complex structures prediction discimination between true partners in the cell and non-interactors  To characterize protein interactions protein interaction sites identification and complex structures prediction discimination between true partners in the cell and non-interactors

18. Algorithms in structural bioinformatics: what for ?  To compare protein structures Elodie Laine – 18.12.2013  To predict protein structures  To simulate protein motions  To characterize protein interactions  To discover and design drugs putative druggable pockets identification binding mode and relative affinity prediction  To discover and design drugs putative druggable pockets identification binding mode and relative affinity prediction