Title :
A comparison of GA and RSNR docking
Author :
Xiao, Yong L. ; Williams, Donald E.
Author_Institution :
Dept. of Chem., Louisville Univ., KY, USA
Abstract :
Molecular docking calculations with genetic algorithms (GA) are compared with results calculated by a numeric random sampling Newton-Raphson (RSNR) method. The intermolecular interaction energy minimum is searched for using both a genetic algorithm approach and a numeric one for the docking process. Intermolecular interactions of a larger molecular complex of an anticancer drug have been investigated. The performance of GAs on molecular docking calculations is discussed and compared with the numerical method. The results of implementation indicate that the GA approach is superior to conventional methods used in energy minimization when there exist many local minima as well as a global minimum. The GA method, which is computationally more practical for applications to large biological systems, provides a rational approach to drug discovery and novel molecular structure design
Keywords :
association; biology computing; genetic algorithms; intermolecular mechanics; macromolecules; minimisation; molecular biophysics; numerical analysis; random processes; anticancer drug; drug discovery; energy minimization; genetic algorithms; global minimum; intermolecular interaction energy minimum; large biological systems; large molecular complex; local minima; molecular docking calculations; novel molecular structure design; numerical random sampling Newton-Raphson method; Biological systems; Biology computing; Chemistry; Drugs; Genetic algorithms; Geometry; Minimization methods; Sampling methods; Shape; Surface structures;
Conference_Titel :
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1899-4
DOI :
10.1109/ICEC.1994.349953