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Prediction of the binding modes between macrolactin N and peptide deformylase from Staphylococcus aureus by molecular docking and molecular dynamics simulations
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  • 作者:Jian Gao (1)
    Yuanhua Cheng (1) (2)
    Wei Cui (1)
    Fushi Zhang (2)
    Huai Zhang (1)
    Yuguo Du (1)
    Mingjuan Ji (1)
  • 关键词:Macrolactin N ; Peptide deformylase ; Docking ; Molecular dynamics simulation
  • 刊名:Medicinal Chemistry Research
  • 出版年:2013
  • 出版时间:June 2013
  • 年:2013
  • 卷:22
  • 期:6
  • 页码:2889-2901
  • 全文大小:923KB
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  • 作者单位:Jian Gao (1)
    Yuanhua Cheng (1) (2)
    Wei Cui (1)
    Fushi Zhang (2)
    Huai Zhang (1)
    Yuguo Du (1)
    Mingjuan Ji (1)

    1. College of Chemistry and Chemical Engineering, Graduate University of the Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China
    2. Key Laboratory of Organic Optoelectronics and Molecular Engineering of Ministry of Education, Department of Chemistry, Tsinghua University, Beijing, 100084, People’s Republic of China
文摘
Macrolactin N is a novel lactone compound against Staphylococcus aureus peptide deformylase (PDF) with an IC50 value of 7.5?μM, while its binding mode with PDF still remains largely unknown. In this study, the binding mechanism of macrolactin N to PDF was investigated using molecular docking, molecular dynamics (MD) simulations, and free energy calculations. Four typical binding modes were obtained by FlexX docking and cluster analysis, which are named as Model A, Model B, Model C, and Model D. The predicted binding free energy of Model A is more stable than those of the other three models. Besides, the free energy decomposition and structure analysis, as well as the hydrogen bond occupancy analysis further demonstrate that Model A is the most appropriate conformation for ligand binding. We found that the Zn2+ ion in Model A has positive contribution with the ligand, which implies the introduction of a metal chelating functional group on this model could further improve the binding affinity to PDF. The feasibility of the results of our molecular docking and MD simulation work was examined by the result about PDF-actinonin in terms of the theoretical simulation and the experimental results (e.g., crystal structure). Meanwhile, four predicted binding modes are validated by means of comparing their binding modes with actinonin, and the comparison result shows that the macrolactin N in Model A may have the highest similarity to the binding mode of actinonin. This work might be useful in designing more promising PDF inhibitors.

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