Structural Bioinformatics

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1 Structural Bioinformatics D. Ritchie, P. Tufféry Paris Nancy BISTRO Strasbourg Lyon Th IFB, Jan. 9, 2015

2 BISTRO Scien&fic leader: Julie Thompson Technical leader: Valérie Cognat IFB correspondent: Valérie Cognat Web: bistro.fr Par&cipa&ng ins&tutes: GMGM Géné&que Moléculaire, Génomique, Microbiologie IBMC Ins&tut de Biologie Moléculaire et Cellulaire IBMP Ins&tut de Biologie Moléculaire des Plantes ICube Ins&tut de Ingénierie, Informa&que, Imagérie IGBMC Ins&tut de Géné&que et de Biologie Moléculaire et Cellulaire IPHC Ins&tut Pluridisciplinaire Hubert Curien Exper&se: Bioinforma&cs tools and resources, data mining algorithms, focused on evolu&onary and func&onal analyses in various applica&on domains, including biomedical studies, plants, yeast and bacteria

3 LORIA Scien&fic leader: Marie- Dominique Devignes Technical leader: Olivier Demengeon IFB correspondent : Marie- Dominique Devignes Web : Par&cipa&ng Teams: Capsid, Orpailleur (INRIA) Exper&se: Protein- protein docking and interac&ons, biological data mining, protein structure alignment, small molecule virtual screening, molecular dynamics, cryo- EM, GPUs; various applica&on domains such as bacterial secre&on systems, GPCRs, plant enzymes, drug side effects, drug reposi&oning

4 PRABI Scien&fic leader: Raphaël Terreux Technical leader: Gilbert Deléage IFB correspondent : Raphaël Terreux Web : Par&cipa&ng Teams: IBCP - Ins&tut de Biologie et Chimie des Protéines (UMR N 5086) Exper&se: Drugs, Pep&des & Protein Design ; Structural Bioinforma&cs of proteins - Large scale automa&c homology modelling of protein. - Large scale comparisons of surface of proteins. - Genera&on of library of organic compound and pep&des : 2D/3D, ADMET predic&on. - Drugs / pep&de - protein interac&ons, Docking, de novo design. - Molecular Dynamics of large system.

5 RPBS Scien&fic leader: Pierre Tufféry Technical leader: Julien Rey IFB correspondent: Julien Rey Web: bioserv.rpbs.univ- paris- diderot.fr Par&cipa&ng Teams: MTi (INSERM UMR- S 973 Université Paris- Diderot) IMPMC (CNRS UMR Université P. et M. Curie) IbiTec- S (CEA - Saclay) CNAM- STIC (CNAM) ABI (Université P. et M. Curie) DSIMB (INSERM U665 Université Paris- Diderot) Exper&se: Structural Bioinforma&cs of proteins; Drugs & Pep&des Design Protein structure and func&on analysis. Compara&ve modeling. Folding nucleus. 3D similari&es. Protein- protein interac&ons. Small compounds: 2D/3D, ADME/tox, focused libraries, ippis, pharmacological profiling, systems toxicology, screening. Pep&des: de novo structure predic&on, protein- pep&de docking, bacterial pep&des. Various applica&ons to cancer, cardiovascular, rare diseases.

6 Structural Bioinformatics

7 Structural Bioinformatics DNA Proteins Molecular dynamics Macromolecular assemblies RNA Binding affinity, specificity Molecular structure Chemicals Amino acid variations Solvent, Membranes Peptides Aileron therapeutics

8 Structural Bioinformatics As A IFB Focusing on platform skills Molecular dynamics Proteins Macromolecular assemblies Molecular structure Amino acid variations Chemicals Peptides Aileron therapeutics

9 Structural Bioinformatics As A IFB De novo structure prediction: Hazardous when > 100 aas. Service vs Research Simulation cost heavy (too for IFB?) Molecular dynamics De novo dimer complex: ~60% success only Proteins Macromolecular assemblies Molecular structure Ranking / scoring: not OK Amino acid variations Chemicals Peptides Aileron therapeutics

10 Structural Bioinformatics As A IFB 2015 priorities: 1. Large scale flexible and integrative modeling 2. Modeling protein complexes 3. Assist search for candidate drugs

11 Structural Bioinformatics As A IFB Task1:Large scale flexible and integrative modeling BISTRO: Automatic, high quality multiple sequence alignment Clustalw/Omega, DbClustal, ClusPack, RASCAL, LEON, Secator, NorMD, MACSIMS Flexible workflow for classical sequence homology analysis Bayesian statistics for sequence alignments (SIBIS) (IA BipBip) Work plan PRABI: Comparative modeling and comparisons of whole protein genome. Geno3D Compara&ve modeling Hhalign-kbest De novo modeling PEP-FOLD (5-50 aas) Model refinement (Gromacs) Hybrid modeling (linkers,...) (IA BipBip) RPBS: Modeling at low sequence identity.

12 Structural Bioinformatics As A IFB Task2: Modeling protein complexes RPBS: De novo complex modeling LORIA: Template based complex modeling Work plan KBDock, Kpax, Hex Scoring complexes using co-evolution (InterEvScore) Template based complexes KBDock + Kpax Pair-wise protein docking (Hex, Piper, Zdock) Refinement: interface to RosettaDock BCSearch Multiple alignment of interologs (InterEvolAlign) De novo binding site candidates (InterEvScore + Hex, Zdock) Considering alternative conformations (BCSearch)

13 Structural Bioinformatics As A IFB Task3: Assist search for candidate drugs RPBS: Small compounds u u u 2D/3D generation ADME/tox libraries On-line screening u u u 3D model Candidate protein binding site Docking Peptides Work plan PRABI: Similar sites in proteins (SuMo) Determined cross allergy reaction

14 Structural Bioinformatics As A IFB Miscellaneous tools (Contributed by all sites) Interactive on-line visualization Java based (Jmol, jalview) Javascript based (PV,JSmol) Data formats, Interconversion tools (open-babel, squiz,...) Structure analysis / edition tools (secondary structure, side chains,...) Data collections Deployment framework (Contributed by all sites) MobyleNet, Galaxy, VREs, Docker,... Interactions with IFB-core (Contributed by all sites)

15 Structural Bioinformatics A one year IFB CDD hiring: Ø BISTRO: Arnaud Kress (IE), 09/01/2014 (18 months) Ø LORIA: Jérémie Bourseau (IE), 11/01/2014 (LORIA) then 04/01/2015 (IFB, 15 months). Ø PRABI: in progress, scheduled for 02/01/2015 Ø RPBS: Marek Vavruša (IE), 11/01/2014 (18 months) Tasks: 1.Large scale flexible and integrative modeling 2.Modeling protein complexes 3.Assist search for candidate drugs Workflows on local platform sites expected ~ ok for mid-2015 for most services Interconnection with IFB-core?

16 Thank you!

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