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Identification of promising multi-targeting inhibitors of obesity from Vernonia amygdalina through computational analysis

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Abstract

Vernonia amygdalina, a widely consumed West African food herb, can be a boon in the discovery of safe anti-obesity agents given the extensive reports on its anti-obesity and antidiabetic potentials. The main aim of this study was to screen 78 Vernonia—Derived Phytocompounds (VDPs) against the active site regions of Human Pancreatic Lipase (HPL), Human Pancreatic Amylase and Human Glucosidase (HG) as drug targets associated with obesity in silico. Structure-based virtual screening helped to identify Luteolin 7-O-glucuronoside and Andrographidoid D2 as hit compounds with dual targeting tendency towards the HPL and HG. Analysis of the molecular dynamic simulation trajectory files of the ligand-receptor complexes as computed from the thermodynamic parameters plots showed not only increased flexibility and greater interaction potential of the active site residues of the receptor towards the VDPs as indicated by the root mean square fluctuation but also higher stability as indicated by the root mean square deviation, radius of gyration and number of hydrogen bonds. The cluster analysis further showed that the interactions with important residues were preserved in the dynamic environment. These observations were further verified from Molecular Mechanics Generalized Born Surface Area Analysis, which also showed that residual contributions to the binding free energies were mainly from catalytic residues at the active sites of the enzymes. The hit compounds also feature desirable physicochemical properties and drug-likeness. This study provides in silico evidence for the inhibitory potential of phytochemicals from Vernonia amygdalina against two target enzymes in obesity.

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Acknowledgements

The authors acknowledge with thanks resources offered by the PhytoBioNet platform. The MDS and MM-GBSA calculations are done on the Bibliotheca Alexandrina HPC facility, Alexandria, Egypt. We appreciate and thank Taif University for the financial support for Taif University Researchers Supporting Project (TURSP-2020/09), Taif University, Taif, Saudi Arabia.

Funding

This study was supported by the Taif University Researchers Supporting Project (TURSP-2020/09), Taif University, Taif, Saudi Arabia.

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Authors and Affiliations

  1. Human Nutraceuticals and Bioinformatics Research Unit, Department of Biochemistry, Salem University, PMB 1060, Lokoja, Kogi, Nigeria

    Oludare M. Ogunyemi

  2. Department of Biochemistry, Faculty of Science and Technology, Bingham University, Karu, Nasarawa, Nigeria

    Gideon A. Gyebi

  3. Natural Products and Structural (Bio-Chem)-Informatics Research Laboratory (NpsBC-Rl), Bingham University, Karu, Nasarawa, Nigeria

    Gideon A. Gyebi

  4. Department of Biophysics, Faculty of Sciences, Cairo University, Giza, Egypt

    Ibrahim M. Ibrahim

  5. Nutritional and Industrial Biochemistry Unit, Department of Biochemistry, University of Ibadan, Ibadan, Nigeria

    Adewale M. Esan & Charles O. Olaiya

  6. Clinical Laboratory Sciences Department, Turabah University College, Taif University, Taif, 21995, Saudi Arabia

    Mohameed M. Soliman

  7. Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, 22511, AlBeheira, Egypt

    Gaber El-Saber Batiha

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  1. Oludare M. Ogunyemi
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Ogunyemi, O.M., Gyebi, G.A., Ibrahim, I.M. et al. Identification of promising multi-targeting inhibitors of obesity from Vernonia amygdalina through computational analysis. Mol Divers 27, 1–25 (2023). https://doi.org/10.1007/s11030-022-10397-6

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