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Exploring effectiveness of ab-initio protein-protein docking methods on a novel antibacterial protein complex dataset

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 6, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbab150

关键词

ab-initio protein docking; antibacterial protein complex; Benchmark 5.0; CAPRI

资金

  1. National Natural Science Foundation of China [NSFC 61772362, 61972280]
  2. National Key R&D Program of China [2020YFA0908400]

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This study evaluated the effectiveness of ab-initio docking methods in antibacterial protein-protein docking. By constructing a dataset and selecting different docking tools for structure identification, efficient tools were recommended and valuable research insights were provided.
Diseases caused by bacterial infections become a critical problem in public heath. Antibiotic, the traditional treatment, gradually loses their effectiveness due to the resistance. Meanwhile, antibacterial proteins attract more attention because of broad spectrum and little harm to host cells. Therefore, exploring new effective antibacterial proteins is urgent and necessary. In this paper, we are committed to evaluating the effectiveness of ab-initio docking methods in antibacterial protein-protein docking. For this purpose, we constructed a three-dimensional (3D) structure dataset of antibacterial protein complex, called APCset, which contained protein complexes whose receptors or ligands are homologous to antibacterial peptides from Antimicrobial Peptide Database. Then we selected five representative ab-initio protein-protein docking tools including ZDOCK3.0.2, FRODOCK3.0, ATTRACT, PatchDock and Rosetta to identify these complexes' structure, whose performance differences were obtained by analyzing from five aspects, including top/best pose, first hit, success rate, average hit count and running time. Finally, according to different requirements, we assessed and recommended relatively efficient protein-protein docking tools. In terms of computational efficiency and performance, ZDOCK was more suitable as preferred computational tool, with average running time of minutes, average Fnat of best pose of and average rank of best pose of . Meanwhile, ZDOCK still yielded better performance on Benchmark 5.0, which proved ZDOCK was effective in performing docking on large-scale dataset. Our survey can offer insights into the research on the treatment of bacterial infections by utilizing the appropriate docking methods.

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