Integrated Cheminformatics-Molecular Docking Approach to Drug Discovery Against Viruses

(E-pub Ahead of Print)

Author(s): Muhammad Faraz Anwar, Ramsha Khalid, Alina Hasanain, Sadaf Naeem, Shamshad Zarina, Syed Hani Abidi*, Syed Ali*.

Journal Name: Infectious Disorders - Drug Targets

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Background: In the current study, we present an integrated in silico cheminformaticsmolecular docking approach to screen and test potential therapeutic compounds against viruses. Fluoroquinolones have been shown to inhibit HCV replication by targeting HCV NS3-helicase. Based on this observation, we hypothesized that natural analogs of fluoroquinolones will have similar or superior inhibitory potential while having potentially fewer adverse effects. Methods: To screen for natural analogs of fluoroquinolones, we devised an integrated in silico Cheminformatics-Molecular Docking approach. We used 17 fluoroquinolones as bait reference, to screen large databases of natural analogs. 10399 natural compounds and their derivatives were retrieved from the databases. From these compounds, molecules bearing physicochemical similarities with fluoroquinolones were analyzed using a cheminformatics-docking approach. Results: From the 10399 compounds screened using our cheminformatics approach, only 20 compounds were found to share physicochemical similarities with fluoroquinolones, while the remaining 10379 compounds were physiochemically different from fluoroquinolones. Molecular docking analysis showed 32 amino acids in the HCV NS3 active site that were most frequently targeted by fluoroquinolones and their natural analogues, indicating a functional similarity between the two groups of compounds. Conclusion: This study describes a speedy and inexpensive approach to complement drug discovery and design against viral agents. The in silico analyses we used here can be employed to shortlist promising compounds/putative drugs that can be further tested in wet-lab.

Keywords: Chemoinformatics, Molecular Docking , HCV, Drug Discovery

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Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1871526518666181019162359
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