TY - GEN
T1 - An improved LGA for protein-ligand docking prediction
AU - Tsai, Chun Wei
AU - Chen, Jui Le
AU - Yang, Chu Sing
PY - 2012/10/4
Y1 - 2012/10/4
N2 - Since the high computational cost of the structure-based protein-Ligand docking prediction is one of the major problems in designing new drugs, many researchers keep looking for a high performance search algorithm to find the workable directions to drug design as well as a simulator platform being able to test and verify the new drugs. In this paper, an improved version of Lamarckian genetic algorithm (ILGA) is first presented for enhancing the performance of LGA by using pattern reduction to reduce the computation cost and using tabu search to increase the search diversity to further find the better results. In addition, the proposed algorithm is also applied to a well-known simulator platform (AutoDock) to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm can enhance the performance of ILGA in terms of convergence performance especially for highly flexible ligands.
AB - Since the high computational cost of the structure-based protein-Ligand docking prediction is one of the major problems in designing new drugs, many researchers keep looking for a high performance search algorithm to find the workable directions to drug design as well as a simulator platform being able to test and verify the new drugs. In this paper, an improved version of Lamarckian genetic algorithm (ILGA) is first presented for enhancing the performance of LGA by using pattern reduction to reduce the computation cost and using tabu search to increase the search diversity to further find the better results. In addition, the proposed algorithm is also applied to a well-known simulator platform (AutoDock) to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm can enhance the performance of ILGA in terms of convergence performance especially for highly flexible ligands.
UR - http://www.scopus.com/inward/record.url?scp=84866848238&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866848238&partnerID=8YFLogxK
U2 - 10.1109/CEC.2012.6256513
DO - 10.1109/CEC.2012.6256513
M3 - Conference contribution
AN - SCOPUS:84866848238
SN - 9781467315098
T3 - 2012 IEEE Congress on Evolutionary Computation, CEC 2012
BT - 2012 IEEE Congress on Evolutionary Computation, CEC 2012
T2 - 2012 IEEE Congress on Evolutionary Computation, CEC 2012
Y2 - 10 June 2012 through 15 June 2012
ER -