DocumentCode :
617826
Title :
Muti-objective evolutionary approach of ligand design for protein-ligand docking problem
Author :
Rakshit, Pratyusha ; Konar, Amit ; Chowdhury, Abishi ; Eunjin Kim ; Nagar, Atulya K.
Author_Institution :
ETCE Dept., Jadavpur Univ., Kolkata, India
fYear :
2013
fDate :
20-23 June 2013
Firstpage :
237
Lastpage :
244
Abstract :
The paper addresses a novel approach to protein-ligand docking problem using Non-dominated Sorting Bee Colony optimization algorithm. In this work, protein-ligand docking is formulated as a multi-objective optimization problem. The docking energy, molecular weight and oral bioavailability are used as three scoring functions for the solutions. Results are demonstrated for six different target proteins both numerically and pictorially. Experimental results reveal that the proposed method outperforms Multi-Objective Particle Swarm Optimization, Non-dominated Sorting Genetic Algorithm-II and Artificial Bee Colony based ligand design method considering the three objectives of the evolved molecules.
Keywords :
biology computing; genetic algorithms; particle swarm optimisation; proteins; docking energy; ligand design; molecular weight; multiobjective particle swarm optimization; mutiobjective evolutionary approach; nondominated sorting bee colony optimization algorithm; nondominated sorting genetic algorithm-II; oral bioavailability; protein-ligand docking problem; Compounds; Force; Optimization; Proteins; Sociology; Sorting; Statistics; CHARMM energy; active site; fragment based approach; ligand; non-dominated bee colony optimization algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
Type :
conf
DOI :
10.1109/CEC.2013.6557576
Filename :
6557576
Link To Document :
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