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Article

Ligand and Structure-Based Approaches for the Identification of Peptide Deformylase Inhibitors as Antibacterial Drugs

1
Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou 221004, Jiangsu, China
2
Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Xuzhou Medical University, Xuzhou 221004, Jiangsu, China
*
Author to whom correspondence should be addressed.
Academic Editor: Christo Z. Christov
Int. J. Mol. Sci. 2016, 17(7), 1141; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms17071141
Received: 13 April 2016 / Revised: 29 June 2016 / Accepted: 9 July 2016 / Published: 15 July 2016
Peptide deformylase (PDF) is a metalloprotease catalyzing the removal of a formyl group from newly synthesized proteins, which makes it an important antibacterial drug target. Given the importance of PDF inhibitors like actinonin in antibacterial drug discovery, several reported potent PDF inhibitors were used to develop pharmacophore models using the Galahad module of Sybyl 7.1 software. Generated pharmacophore models were composed of two donor atom centers, four acceptor atom centers and two hydrophobic groups. Model-1 was screened against the Zinc database and several compounds were retrieved as hits. Compounds with Qfit values of more than 60 were employed to perform a molecular docking study with the receptor Escherichia coli PDF, then compounds with docking score values of more than 6 were used to predict the in silico pharmacokinetic and toxicity risk via OSIRIS property explorer. Two known PDF inhibitors were also used to perform a molecular docking study with E. coli PDF as reference molecules. The results of the molecular docking study were validated by reproducing the crystal structure of actinonin. Molecular docking and in silico pharmacokinetic and toxicity prediction studies suggested that ZINC08740166 has a relatively high docking score of 7.44 and a drug score of 0.78. View Full-Text
Keywords: peptide deformylase; pharmacophore model; high-throughput virtual screening; molecular docking; antibacterial drug peptide deformylase; pharmacophore model; high-throughput virtual screening; molecular docking; antibacterial drug
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MDPI and ACS Style

Gao, J.; Liang, L.; Zhu, Y.; Qiu, S.; Wang, T.; Zhang, L. Ligand and Structure-Based Approaches for the Identification of Peptide Deformylase Inhibitors as Antibacterial Drugs. Int. J. Mol. Sci. 2016, 17, 1141. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms17071141

AMA Style

Gao J, Liang L, Zhu Y, Qiu S, Wang T, Zhang L. Ligand and Structure-Based Approaches for the Identification of Peptide Deformylase Inhibitors as Antibacterial Drugs. International Journal of Molecular Sciences. 2016; 17(7):1141. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms17071141

Chicago/Turabian Style

Gao, Jian, Li Liang, Yasheng Zhu, Shengzhi Qiu, Tao Wang, and Ling Zhang. 2016. "Ligand and Structure-Based Approaches for the Identification of Peptide Deformylase Inhibitors as Antibacterial Drugs" International Journal of Molecular Sciences 17, no. 7: 1141. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms17071141

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