Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Feb 23:10:1106128.
doi: 10.3389/fmolb.2023.1106128. eCollection 2023.

Ligand-based pharmacophore modeling and QSAR approach to identify potential dengue protease inhibitors

Anushka A Poola  1 , Prithvi S Prabhu  1 , T P Krishna Murthy  1 , Manikanta Murahari  2 , Swati Krishna  1 , Mahesh Samantaray  3 , Amutha Ramaswamy  3
Affiliations

Ligand-based pharmacophore modeling and QSAR approach to identify potential dengue protease inhibitors

Anushka A Poola et al. Front Mol Biosci. .

Abstract

The viral disease dengue is transmitted by the Aedes mosquito and is commonly seen to occur in the tropical and subtropical regions of the world. It is a growing public health concern. To date, other than supportive treatments, there are no specific antiviral treatments to combat the infection. Therefore, finding potential compounds that have antiviral activity against the dengue virus is essential. The NS2B-NS3 dengue protease plays a vital role in the replication and viral assembly. If the functioning of this protease were to be obstructed then viral replication would be halted. As a result, this NS2B-NS3 proves to be a promising target in the process of anti-viral drug design. Through this study, we aim to provide suggestions for compounds that may serve as potent inhibitors of the dengue NS2B-NS3 protein. Here, a ligand-based pharmacophore model was generated and the ZINC database was screened through ZINCPharmer to identify molecules with similar features. 2D QSAR model was developed and validated using reported 4-Benzyloxy Phenyl Glycine derivatives and was utilized to predict the IC50 values of unknown compounds. Further, the study is extended to molecular docking to investigate interactions at the active pocket of the target protein. ZINC36596404 and ZINC22973642 showed a predicted pIC50 of 6.477 and 7.872, respectively. They also showed excellent binding with NS3 protease as is evident from their binding energy of -8.3and -8.1 kcal/mol, respectively. ADMET predictionsofcompounds have shown high drug-likeness. Finally, the molecular dynamic simulations integrated with MM-PBSA binding energy calculations confirmedboth identified ZINC compounds as potential hit moleculeswith good stability.

Keywords: Dengue; QSAR; docking; molecular dynamics; pharmacophore modeling.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Visual representation of the docked complexes and the amino acid interactions of (A) ZINC36596404 (B) ZINC22973642.
FIGURE 2
FIGURE 2
RMSD study of top 2 ligands for 100 ns MD Simulation.
See this image and copyright information in PMC

References

    1. Adawara S. N., Shallangwa G. A., Mamza P. A., Ibrahim A. (2020). Molecular docking and QSAR theoretical model for prediction of phthalazinone derivatives as new class of potent dengue virus inhibitors. Beni-Suef Univ. J. Basic Appl. Sci. 9. 10.1186/s43088-020-00073-9 - DOI - PubMed
    1. Behnam M. A. M., Graf D., Bartenschlager R., Zlotos D. P., Klein C. D. (2015). Discovery of nanomolar dengue and west nile virus protease inhibitors containing a 4-benzyloxyphenylglycine residue. J. Med. Chem. 58 (23), 9354–9370. 10.1021/ACS.JMEDCHEM.5B01441 - DOI - PubMed
    1. Daina A., Michielin O., Zoete V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 7 (11), 42717–42813. 10.1038/srep42717 - DOI - PMC - PubMed
    1. Drwal M. N., Banerjee P., Dunkel M., Wettig M. R., Preissner R. (2014). ProTox: A web server for the in silico prediction of rodent oral toxicity. Nucleic Acids Res. 42 (W1), W53–W58. 10.1093/NAR/GKU401 - DOI - PMC - PubMed
    1. Dwivedi V. D., Arya A., Yadav P., Kumar R., Kumar V., Raghava G. P. S. (2021). DenvInD: Dengue virus inhibitors database for clinical and molecular research. Briefings Bioinforma. 22 (3), bbaa098. 10.1093/BIB/BBAA098 - DOI - PubMed