• DocumentCode
    1634766
  • Title

    Local vs. global search strategies in evolutionary GRID-based conformational sampling & docking

  • Author

    Horvath, Dragos ; Brillet, Lorraine ; Roy, Sylvaine ; Conilleau, Sébastien ; Tantar, Alexandru-Adrian ; Boisson, Jean- Charles ; Melab, Nouredine ; Talbi, El-Ghazali

  • Author_Institution
    Lab. d´´Infochimie, Univ. de Strasbourg, Strasbourg
  • fYear
    2009
  • Firstpage
    247
  • Lastpage
    254
  • Abstract
    Conformational sampling, the computational prediction of the experimental geometries of small proteins (folding) or of protein-ligand complexes (docking), is often cited as one of the most challenging multimodal optimization problems. Due to the extreme ruggedness of the energy landscape as a function of geometry, sampling heuristics must rely on an appropriate trade-off between global and local searching efforts. A previously reported ldquoplanetary strategyrdquo, a generalization of the classical island model used to deploy a hybrid genetic algorithm on computer grids, has shown a good ability to quickly discover low-energy geometries of small proteins and sugars, and sometimes even pinpoint their native structures-although not reproducibly. The procedure focused on broad exploration and used a tabu strategy to avoid revisiting the neighborhood of known solutions, at the risk of ldquoburyingrdquo important minima in overhastily set tabu areas. The strategy reported here, termed ldquodivide-and-conquer planetary modelrdquo couples this global search procedure to a local search tool. Grid nodes are now shared between global and local exploration tasks. The phase space is cut into ldquocellsrdquo corresponding to a specified sampling width for each of the N degrees of freedom. Global search locates cells containing low-energy geometries. Local searches pinpoint even deeper minima within a cell. Sampling width controls the important trade-off between the number of cells and the local search effort needed to reproducibly sample each cell. The probability to submit a cell to local search depends on the energy of the most stable geometry found within. Local searches are allotted limited resources and are not expected to converge. However, as long as they manage to discover some deeper local minima, the explored cell remains eligible for further local search, now relying on the improved energy level to enhance chances to be picked again. This competition prevents the syst- em to waste too much effort in fruitless local searches. Eventually, after a limited number of local searches, a cell will be ldquoclosedrdquo and used - first as ldquoseedrdquo, later as tabu zone-to bias future global searches. Technical details and some folding and docking results will be discussed.
  • Keywords
    divide and conquer methods; genetic algorithms; grid computing; proteins; search problems; conformational docking; conformational sampling; divide-and-conquer planetary model; evolutionary GRID; global search strategies; hybrid genetic algorithm; multimodal optimization; protein-ligand complexes; tabu strategy; Computational geometry; Energy states; Fellows; Genetic algorithms; Grid computing; Information geometry; Proteins; Sampling methods; Solid modeling; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4982955
  • Filename
    4982955