An Efficient ABC_DE_Based Hybrid Algorithm for Protein-Ligand Docking.

Boxin Guan,Yuhai Zhao,Changsheng Zhang

doi:10.3390/ijms19041181

Boxin Guan, Yuhai Zhao + Show 1 more

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https://doi.org/10.3390/ijms19041181

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Abstract

Protein–ligand docking is a process of searching for the optimal binding conformation between the receptor and the ligand. Automated docking plays an important role in drug design, and an efficient search algorithm is needed to tackle the docking problem. To tackle the protein–ligand docking problem more efficiently, An ABC_DE_based hybrid algorithm (ADHDOCK), integrating artificial bee colony (ABC) algorithm and differential evolution (DE) algorithm, is proposed in the article. ADHDOCK applies an adaptive population partition (APP) mechanism to reasonably allocate the computational resources of the population in each iteration process, which helps the novel method make better use of the advantages of ABC and DE. The experiment tested fifty protein–ligand docking problems to compare the performance of ADHDOCK, ABC, DE, Lamarckian genetic algorithm (LGA), running history information guided genetic algorithm (HIGA), and swarm optimization for highly flexible protein–ligand docking (SODOCK). The results clearly exhibit the capability of ADHDOCK toward finding the lowest energy and the smallest root-mean-square deviation (RMSD) on most of the protein–ligand docking problems with respect to the other five algorithms.

Highlights

The development of new drugs is costly and inefficient, so it is urgent to apply new theoretical methods and new technologies to improve it
The degrees of freedom include three parameters denote the translation of the ligand relative to a specified center, a quaternion represents the orientation of the ligand with four parameters, and T torsion parameters where T is the number of rotatable bonds
ADHDOCK is a hybrid search algorithm based on artificial bee colony (ABC) [34] and differential evolution (DE) [35], and it is designed for protein–ligand docking

Summary

Introduction

The development of new drugs is costly and inefficient, so it is urgent to apply new theoretical methods and new technologies to improve it. Computer aided drug design (CADD) is developed gradually under the strong impetus of this social demand [1,2]. CADD takes advantage of advanced multidisciplinary technology, methods, and achievements, and has been a necessary basic tool for drug design. Protein–ligand docking, as an important part of CADD, is a computer simulation to predict the binding pose when the three-dimensional structures of protein receptors and ligands are known [3,4,5,6]. The purpose of protein–ligand docking is to find the conformation with the lowest energy when a ligand binds the active region of a receptor. For the main process of protein–ligand docking, all possible active sites of the receptor are first detected. The results are sorted by a specific scoring function, and the binding pose with the lowest energy score is found

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