A Similarity-Based Grouping Method for Molecular Docking in Distributed System

摘要

Molecular docking is one main technique in Virtual Screening. During a molecular docking process, the molecule docking time presents serious diversity because of different chemical structures. The time diversity can cause certain nodes to overload, thereby reducing the data processing ability of the whole distributed molecular docking system. Therefore, a reasonable and efficient data grouping strategy is essential in the molecular docking system. In this paper, molecular structural similarity is researched in depth, and a similarity-based data grouping method is proposed. On the basis of the work in Database Management System for Virtual Screening, the method takes advantage of the computational chemistry software Chemistry Development Kit and cluster analysis methods to process the chemical molecules data. Finally, we deploy and implement the data grouping method on the Hadoop distributed platform. The experimental results show that this data grouping method can improve the efficiency of molecular docking.