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Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies

Published on Dec 17, 2018in Journal of Clinical Medicine
· DOI :10.3390/jcm7120563
Shailima Rampogu7
Estimated H-index: 7
,
Amir Zeb5
Estimated H-index: 5
+ 3 AuthorsKeun Woo Lee30
Estimated H-index: 30
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Abstract
Bacterial peptide deformylase (PDF) is an attractive target for developing novel inhibitors against several types of multidrug-resistant bacteria. The objective of the current study is to retrieve potential phytochemicals as prospective drugs against Staphylococcus aureus peptide deformylase (SaPDF). The current study focuses on applying ligand-based pharmacophore model (PharmL) and receptor-based pharmacophore (PharmR) approaches. Utilizing 20 known active compounds, pharmL was built and validated using Fischer’s randomization, test set method and the decoy set method. PharmR was generated from the knowledge imparted by the Interaction Generation protocol implemented on the Discovery Studio (DS) v4.5 and was validated using the decoy set that was employed for pharmL. The selection of pharmR was performed based upon the selectivity score and further utilizing the Pharmacophore Comparison module available on the DS. Subsequently, the validated pharmacophore models were escalated for Taiwan Indigenous Plants (TIP) database screening and furthermore, a drug-like evaluation was performed. Molecular docking was initiated for the resultant compounds, employing CDOCKER (available on the DS) and GOLD. Eventually, the stability of the final PDF–hit complexes was affirmed using molecular dynamics (MD) simulation conducted by GROMACS v5.0.6. The redeemed hits demonstrated a similar binding mode and stable intermolecular interactions with the key residues, as determined by no aberrant behaviour for 30 ns. Taken together, it can be stated that the hits can act as putative scaffolds against SaPDF, with a higher therapeutic value. Furthermore, they can act as fundamental structures for designing new drug candidates.
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#2Adlina Maisarah Mahadi (Monash University Malaysia Campus)H-Index: 1
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4 CitationsSource
#1Shailima Rampogu (Gyeongsang National University)H-Index: 7
#2Ayoung Baek (Gyeongsang National University)H-Index: 7
Last.Keun Woo Lee (Gyeongsang National University)H-Index: 30
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12 CitationsSource
#1Shailima Rampogu (Gyeongsang National University)H-Index: 7
#2Ayoung Baek (Gyeongsang National University)H-Index: 7
Last.Keun Woo Lee (Gyeongsang National University)H-Index: 30
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3 CitationsSource
5 CitationsSource
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#1Amir Zeb (Gyeongsang National University)H-Index: 5
#2Minky Son (Gyeongsang National University)H-Index: 8
Last.Keun Woo Lee (Gyeongsang National University)H-Index: 30
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