A new tri-objective model for the flexible docking problem J-C. BOISSON1, L. JOURDAN1, E-G. TALBI1 and D.HORVATH2 1Project Team INRIA DOLPHIN, Lille, France. 2 « Laboratoire de Glycobiologie Structurale et Fonctionnelle », CNRS, Lille1, France. J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

+ Molecular docking HIV-1 PROTEASE + XK263 RECEPTOR + XK263 Inhibitor LIGAND Molecular docking  prediction of the optimal complex receptor/ligand according to chemical and geometric properties. 23/04/2018 J-C. BOISSON META 2008

Molecular docking Docking simulation: rigid  no conformation modification of the molecules. semi-flexible  one of the two molecules may have its conformation modified during the process (generally the ligand). flexible  conformational modifications for the both molecules. Several sites can exist for docking the ligand. 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

ANR Dock project ANR  french research agency. Dock project  3-year project about protein structure prediction and docking. One of the objectives of the Dock project : Find new multi-objective models for the flexible docking. Implement them with effective (parallel) optimization methods. Propose these methods to the community. 23/04/2018 J-C. BOISSON META 2008

Docking@Grid: conformational sampling and docking on grids PSP = protein structure prediction Ligand files Conformations Ligand PSP User Docking Receptor PSP Receptor files Conformations More information on : http://dockinggrid.gforge.inria.fr 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (1/8) An energy objective  qualify the stability of the gained complexes. A geometric objective  describe the degree of penetration of the ligand into the site. A robustness objective  ability of the complex to resist to small perturbations. A-A Tantar, N. Melab, E-G. Talbi and B. Toursel. A Parallel Hybrid Genetic Algorithm for Protein Structure Prediction on the Computational Grid. Elsevier Science, Future Generation Computer Systems, 23(3):398-409, 2007. 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (2/8) 1. Ligand/site complex energy Force field used = originaly based on the Consistent Valence Force Field (CVFF) 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (3/8) 2. Complex surface  3 possibilities:  Van Der Waals surface (a: blue),  solvant accessible surface (b: red),  Connolly surface (c: green). 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (4/8) 2. Complex surface  3 possibilities:  Van Der Waals surface,  solvant accessible surface  Connolly surface.  SASA Solvent Accessible Surface Area Original paper S.M. Le Grand and K.M. Merz, Jr. Rapid Approximation to Molecular Surface Area via the Use of Boolean Logic and Look-Up Tables. Journal of Computational Chemistry, 14(3):349-352 (1993). Recent paper using SASA A. Leaver-Fay, G.L. Butterfoss, J. Snoeyink and B. Kuhlman. Maintaining solvent accessible surface area under rotamer substitution for protein design. Journal of Computational Chemistry, 28(8):1336-1341 (2007). 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (5/8) SASA = 6201 Å2 SASA = 5548 Å2 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (6/8) 3. Complex robustness G = 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (7/8): sampling around optimal complex (ligand rotation) 23/04/2018 J-C. BOISSON META 2008

A tri-objective model (8/8): sampling around optimal complex (ligand translation) 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design  the genetic algorithms (GA) Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

Motivation for choosing the GA Efficient multi-objective GA scheme are available. These algorithms allow to gain a set of solutions of good compromise. They have a good power of exploration of the search space. The GA are easy to parallelize. 23/04/2018 J-C. BOISSON META 2008

Solution representation Site Ligand X1 Y1 Z1 X2 Y2 Z2 X3 Y3 Z3 . XN YN ZN X’1 Y’1 Z’1 X’2 Y’2 Z’2 X’3 Y’3 Z’3 . X’N Y’N Z’N « docking complex » 23/04/2018 J-C. BOISSON META 2008

Indicator-Based EA (IBEA) [Zitzler et al. 2004] Initialization initial population P. Fitness assignment quality indicator Qi : Fitness (x) = Qi (x , P\{x}) Diversity preservation  none. Selection binary tournament. Recombination and mutation operators. Replacement remove the worst individual and update fitness values until |P| = N. Elitism archive A of potentially efficient solutions. Output archive A. 23/04/2018 J-C. BOISSON META 2008 22

Recombination operator Parents S1 + L1 S2 + L2 Children S1 + L2 S2 + L1 23/04/2018 J-C. BOISSON META 2008

Classic docking mutations Translation Rotation of a torsion angle Rotation 23/04/2018 J-C. BOISSON META 2008

Advanced docking mutations (1/2) Reverse mutation  big ligand rotation to avoid bad results due to symmetry in it. Big and small rotation/translation windows  adapting the impact of ligand rotations and translations during the docking process. SMO mutation (Several Mutations in One)  mechanism to make several modifications without evaluate an individual in order to gain access to new search space areas. 23/04/2018 J-C. BOISSON META 2008 25

Advanced docking mutation (2/2) Hybridizing mechanisms : Local search based on ligand rotations. Local search based on torsion rotations.  goal : minimizing the complex energy. (mono-objective local searches) 23/04/2018 J-C. BOISSON META 2008 26

PARAllel and DIStributed Evolving Objects http://paradiseo.gforge.inria.fr/ EO PEO MO MOEO  Evolving Object (EO) for population of solution based metaheuristics : EA, PSO.  Moving Objects (MO) for solution base metaheuristics : HC, SA, TS, ILS, VNS, …  Multi-Objective EO (MOEO) for multi-objective evolutionary algorithms : NSGA-II, SPEA, IBEA, …  ParadisEO (PEO)  EO, MO and MOEO on clusters and/or grids. S. Cahon, N. Melab and E-G. Talbi, ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics. Journal of Heuristics, vol. 10(3), pp.357-380, May 2004. A. Liefooghe, M. Basseur, L. Jourdan and E-G. Talbi. ParadisEO-MOEO: A Framework for Multi-Objective Optimization. Proceedings of EMO’2007, pages 457-471, LNCS, Springer-Verlag, 2007. 23/04/2018 J-C. BOISSON META 2008

Performance assessment Comparison of the final complexes with the crystallographic one. Root Mean Square Deviation (RMSD) computation : with :  n the number of heavy atoms.  dx, dy and dz the deviation between complex and model structures for x, y and z coordinate. 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

Data and results Tests on 6 instances of the CDCC-Astex clean list: 6rsa, 1mbi, 2tsc, 1htf, 1dog and 2mcp. Instances prepared with the Chimera software : Extraction of the ligand from the site to have a « seed » ligand used for population initialisation. Correct results obtained (average RMSD = 2 Å) but not good enough comparing to standard docking algorithms (generally < 1 Å). 23/04/2018 J-C. BOISSON META 2008

Outline Molecular docking. ANR Dock project & Docking@GRID. A new tri-objective model. Algorithm design. Data and results. Conclusions and perspectives. 23/04/2018 J-C. BOISSON META 2008

Conclusions and perspectives (1/2) A new tri-objective has been proposed. It appears to be able to give promising results on 6 instances. It needs : To be tested on other instances. To have its behaviour improved. But it is an exploratory study … 23/04/2018 J-C. BOISSON META 2008

Conclusions and perspectives (2/2) It is only one (the first) model designed. Eight multi-objective models have been designed: Bi and tri objective models. Using two different force fields: CVFF. Autodock 4.0. Tested on the same instances for twelve operator configurations of the parallel GA. 23/04/2018 J-C. BOISSON META 2008

Questions ? 23/04/2018 J-C. BOISSON META 2008