• DocumentCode
    2302649
  • Title

    Using an annealing genetic algorithm to solve global energy minimization problem in molecular binding

  • Author

    Wang, Leuo-hong ; Chen, Wen-Chin ; Ouh-Young, Ming ; Wen-Chin Cheu

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • fYear
    1994
  • fDate
    6-9 Nov 1994
  • Firstpage
    404
  • Lastpage
    410
  • Abstract
    Molecular binding, important in drug design, explores the accurate binding structures between molecules. This exploration can be formulated as a global optimization problem. However, the problem in molecular binding is that the search space is very large and the computational cost increases tremendously with the growth of the degrees of freedom. In this paper, we utilize a new algorithm called the annealing genetic algorithm to solve the global optimization problem in molecular binding. Using a protein with three anti-cancer drugs in our model, our algorithm can find a binding structure with a complicated energy computation within a couple of hours and the experimental results indicate that the solutions are reasonable
  • Keywords
    biology; computational complexity; genetic algorithms; simulated annealing; annealing genetic algorithm; drug design; global energy minimization; molecular binding; protein; search space; Annealing; Computer science; Drugs; Force feedback; Genetic algorithms; Genetic engineering; Humans; Minimization methods; Pharmaceuticals; Power engineering and energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-8186-6785-0
  • Type

    conf

  • DOI
    10.1109/TAI.1994.346464
  • Filename
    346464