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Docking@GRID – A Web Portal for Massively Parallel Flexible Docking, using the ChemAxon toolkit.

Docking@GRID – A Web Portal for Massively Parallel Flexible Docking, using the ChemAxon toolkit. Dragos Horvath* , Kun Attila  , Benjamin Parent*, Cyrielle Boutroue # , Even Gaël # , Alexandru Tantar # , Nouredine Melab # , Sylvaine Roy  & El-Ghazali Talbi #

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Docking@GRID – A Web Portal for Massively Parallel Flexible Docking, using the ChemAxon toolkit.

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  1. Docking@GRID – A Web Portal for Massively Parallel Flexible Docking, using the ChemAxon toolkit. Dragos Horvath*, Kun Attila, Benjamin Parent*, Cyrielle Boutroue#, Even Gaël#, Alexandru Tantar#, Nouredine Melab#, Sylvaine Roy & El-Ghazali Talbi# * UMR 8576, CNRS – Univ. Lille 1, FR  Chemistry Dept, Univ. Babes-Bolyai, Cluj, RO # LIFL CNRS/INRIA – Univ. Lille 1, FR  DSV/iRTSV - CEA, Grenoble, FR

  2. Outline… • The goal: automated fully flexible docking on computer grids • GRID5000, http://www.grid5000.fr • Specific conformational sampling & docking software based on hybrid genetic algorithms • Upfront chemoinformatics tools to preprocess submitted ligands. • Upfront tools to define the active site and its key degrees of freedom (!) • Interface to start docking calculations & analyze results.

  3. Customized CVFF force field, employing: • a 10 Å cutoff (with a termination function) • a smoothing procedure to avoid interatomic clashes • a continuum solvent model ‘Smoothing’ distance dij q1 q2 q3 … ... qn Effective interatomic distance d0ij Genetic Algorithm-driven Conformational Sampling Tool • Based on a Genetic Algorithm, coding conformers as "chromosomes" in which each locus stands for a torsional angle value. • The In Silico Darwinian Evolution, leading to fitter and fitter (lower energy) conformers, was enhanced by • hybridization with various optimization heuristics • Fine-tuning of the parameters controlling the evolutionary strategy

  4. GRID 5000-based ‘Planetary’ Model • Stablest Chromosomes • Sampling Success Score Sampling Success vs. Operational Pars Operational Pars Selector If (free node) DEPLOY Island Model Solution Merger & Clusterer • Stop: • max. ‘Mission Nr.’ • no new clusters since N ‘missions’ • - Executables • - Molecule File • - Constraint Files • - Seeds List • - Taboo List • Operational Pars Conformer & Cluster Database ‘Panspermia’ policy center ‘recent’ clusters: seeds ‘old’ clusters: taboo www.grid5000.fr

  5. Ab initio folding of Trp cage 1L2Y: native structure (reproducibly) found and ranked as most stable. Planetary model used max. 20 nodes for 4…5 days Conformer # 1, RMS~1.8 Ǻ - good match to native structure

  6. Ab initio folding of Trp zipper 1LE1: native structure found and ranked as most stable. Planetary model used max. 20 nodes for 4…5 days Conformer # 1, RMS~0.8 Ǻ - perfect match to native structure

  7. However, there is a high risk that almost well folded solutions, being declared taboo, block the access to the correct fold !! Conformer # 79, RMS~2.4 Ǻ - near-optimal fold closest to native structure Conformer # 1, RMS~3.8 Ǻ - is a poor match of the native structure

  8. Outline… • The goal: automated fully flexible docking on computer grids • GRID5000, http://www.grid5000.fr • Specific conformational sampling & docking software based on hybrid genetic algorithms • Upfront chemoinformatics tools to pre-process submitted ligands. • Upfront tools to define the active site and its key degrees of freedom (!) • Interface to start docking calculations & analyze results.

  9. User Toggle Main Tautomer & Major µSpecies Standardize Main Tautomer & Key µSpecies (occurrence > m%) JChem DataBase Cannonical SMILES  Dockable Conformer Families All Tautomers & Major µSpecies All Tautomers & Key µSpecies Generate Conformer(s) Force Field Typing (PMapper) Partial Charge Calculation Add Explicit H If new… Potential problems with resonant structures in the ChargePlugin: try { ChgPlug.setTakeResonantStructure(true); chgMol=ChgPlug.setMolecule(currSpec,false,false); ChgPlug.run(); … } catch (Exception ResonantStructureFailed) { try { ChgPlug.setTakeResonantStructure(false); … } catch (Exception WhateverYouDoItBreaks) { … } } Ligand Preprocessor… Ligand File Upload • Issues yet to be settled: • use the Conformer Plugin to generate several hundreds of geometries • Conformer diversity control ? • How many degrees of freedom can be handled without significant risk of missing key minima ? • Docking will use a different force field – how ‘compatible’ are ConformerPlugin & CVFF energies? • use the Conformer Plugin to generate a starting geometry, then use a ligand-specific GA-driven sampling engine to explore the phase space. A selector of top N most likely tautomeric forms would be of outstanding help here – many among the enumenated tautomers are chemically meaningless! • Using PMapper to assign CVFF types to ligand atoms • required SMARTS encoding of the CVFF ‘templates’ corresponding to local neighborhoods defining each potential type

  10. Outline… • The goal: automated fully flexible docking on computer grids • GRID5000, http://www.grid5000.fr • Specific conformational sampling & docking software based on hybrid genetic algorithms • Upfront chemoinformatics package to pre-process submitted ligands. • Upfront tools to define the active site and its key degrees of freedom (!) • Interface to start docking calculations & analyze results.

  11. This part of the backbone is a « frozen » part of the flexible loop: Rigid body rototranslations Active Site Definition… Formally « break » bond to unlock degrees of freedom in loop Flexible Loop: Backbone (f,y but not w) & sidechains Ligand.. Fixed backbone, Mobile sidechains Fixed protein residues

  12. Protein Preprocessing Tools… • At this point, the user has to explicitly provide: • A BioSym .car protein file, with correct protonation states, partial charges and force field types for all protein atoms • A list of fixed atoms • A list of explicitly ‘broken’ bonds to enable sampling ring and fixed end loop geometries • A list of active torsional degrees of freedom (otherwise, all potentially rotatable exocyclic single bonds will be considered) • Will MarvinSpace evolve such as to allow for graphical input the above-mentioned information? • Would the Charge Plugin, the MicroSpecies Plugin and PMapper work upon input of a .pdb file? • JChem Database of defined active sites and their sampled unbound state geometries…

  13. Outline… • The goal: automated fully flexible docking on computer grids • GRID5000, http://www.grid5000.fr • Specific conformational sampling & docking software based on hybrid genetic algorithms • Upfront chemoinformatics tools to pre-process submitted ligands. • Upfront tools to define the active site and its key degrees of freedom (!) • Interface to start docking calculations & analyze results.

  14. The Dock Manager • In an ideal world, an academic user may add own molecule collections to the database, but should be allowed to try docking other people’s molecules as well… • Paranoia Manager: who’s allowed to dock ‘my’ compounds and use ‘my’ active sites? • Make use of JChem facilities to search ligand database by cannonical structures, and return all the conformers of associated µSpecies/Tautomers. Chemoinformatic filters welcome, even based on the Holy Rule of Five! • Methodological progress on the docking algorithms still required: • Is rigid docking of each of ~102 ligand conformers into each one of the ~104 active site geometries feasible? Would it be assimilable to flexible docking? • How to score: free energy based on docked vs. unbound ensembles? What about µSpecies & Tautomer penalties?

  15. Docked Conformer Visualization

  16. Conclusions & Perspectives • This is a long-term ANR-funded public research project: http://dockinggrid.gforge.inria.fr/ • The primary goal is developing efficient GRID-based conformational sampling & docking methodologies • http://paradiseo.gforge.inria.fr/ to provide the core routines for parallel evolutionary computing • However, chemically meaningful ligand and active site management is as important as the docking step! • ChemAxon tools for ligand standardizing, protonation, charge & force field management, 3D-buildup, storage & retrieval, visualizing,…, are perfectly suited! • Progress needed on macromolecule & active site management. TTHANKSHTHANKSATHANKSNTHANKSKTHANKSS

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