Paper Info
Title
Molecular docking with opposition-based differential evolution
Abstract
Computer simulation of binding a small molecule (ligand) to the protein receptor is one of the most important issues in present drug design research. The goal of this procedure is to find the best protein-ligand complex by in silico methods. Among different types of approaches that have been developed, metaheuristic algorithms have a major contribution to solve docking problem. In this paper, a population based iterative search algorithm is used for finding the best docking pose. This algorithm is an extension of the differential evolution (DE) algorithm called opposition-based differential evolution (ODE). Also ODE is enhanced by a local search algorithm and a pseudo-elitism operator. The scoring function which is used in this paper is the AutoDock scoring function. Six different protein-ligand complexes are used to verify the efficiency of the proposed algorithm. The experimental results show that the modified ODE (mODE) is more robust and reliable than the other algorithms such as simulated annealing and Lamarckian genetic algorithm.
Year
DOI
Venue
2012
10.1145/2245276.2231996
SAC
Keywords
Field
DocType
different protein-ligand complex,best docking,iterative search algorithm,autodock scoring function,local search algorithm,lamarckian genetic algorithm,opposition-based differential evolution,metaheuristic algorithm,modified ode,differential evolution,molecular docking,proposed algorithm,search algorithm,simulated annealing,genetic algorithm,computer simulation,score function,drug design
Simulated annealing,Population,Mathematical optimization,Computer science,Differential evolution,Local search (optimization),AutoDock,Ode,Genetic algorithm,Metaheuristic
Conference
Citations 
PageRank 
References 
3
0.36
11
Authors
2
Name
Order
Citations
PageRank
Mohamad Koohi-Moghadam130.36
Adel Torkaman Rahmani213919.77