MoDock: A multi-objective strategy improves the accuracy for molecular docking

Algorithms for Molecular Biology

Junfeng Gu¹  Xu Yang¹  Ling Kang²  Jinying Wu¹  Xicheng Wang¹ 

[1] State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116023, China

[2] Department of Computer Science and Technology, Dalian Neusoft Institute of Information, Dalian 116023, China

关键词: Optimization;    Scoring function;    Molecular docking;    Multi-objective;   

Others  :  1141274
DOI  :  10.1186/s13015-015-0034-8

 received in 2013-10-28, accepted in 2015-01-08,  发布年份 2015

【 摘 要 】

Background

As a main method of structure-based virtual screening, molecular docking is the most widely used in practice. However, the non-ideal efficacy of scoring functions is thought as the biggest barrier which hinders the improvement of the molecular docking method.

Results

A new multi-objective strategy for molecular docking, named as MoDock, is presented to further improve the docking accuracy with available scoring functions. Instead of simple combination of multiple objectives with fixed weight factors, an aggregate function is adopted to approximate the real solution of the original multi-objective and multi-constraint problem, which will simultaneously smooth the energy surface of the combined scoring functions. Then, method of centers and genetic algorithm are used to find the optimal solution. Tests of MoDock against the GOLD test data set reveal the multi-objective strategy improves the docking accuracy over the individual scoring functions. Meanwhile, a 70% ratio of the good docking solutions with the RMSD value below 1.0 Å outperforms other 6 commonly used docking programs, even with a flexible receptor docking program included.

Conclusions

The results show MoDock is an effective strategy to overcome the deviations brought by single scoring function, and improves the prediction power of molecular docking.

【 授权许可】

   
2015 Gu et al.; licensee BioMed Central.

【 图 表 】

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