Skip to main content
SpringerLink
Log in

Phytochemicals from Nigerian medicinal plants modulate therapeutically-relevant diabetes targets: insight from computational direction

  • Original Article
  • Published:
Advances in Traditional Medicine Aims and scope Submit manuscript

Abstract

Traditional medicines have played critical roles in the treatment of diabetes in Nigeria. Since plants extracts contain many phytochemical compounds, it is quite challenging to experimentally determine the exact pharmacological agent responsible for their antidiabetic activity from the abundant constituents. In this study, the antidiabetic potentials of compounds identified from Nigerian plants was explored using computational technique. Fifty chemical compounds commonly found in Nigerian medicinal plants were docked with diabetes prime targets adiponectin, α-amylase, α-glucosidase, dipeptidyl peptidase-iv, glycogen synthase kinase-3β, peroxisome proliferator-activated receptor-γ and glucose transporter-1 using autodock vina software. From the analysis, rutin, 1, 5-Dicaffeoylquinic acid, vitexin, chlorogenic acid, taxifolin, luteolin and alstonine had better docking score than the standard drug for each target. The seven top-scoring compounds were stable with the targets after calculating their binding free energy. DFT calculations (HOMO/LUMO and global descriptive parameters) was performed to determine the compounds reactivity, and it shows that alstonine, Dicaffeoylquinic acid and chlorogenic acid are the most chemical reactive ligands. The AMET filtering of the compounds through pain alert, RO5, carcinogenicity and oral availability showed that alstonine and vitexin exhibited better profile among the rest. Finally, the intrinsic biological activity of the ligands by webserver identified the compounds as potential antidiabetic compounds, with more potency to act as aldose reductase inhibitor. Although this study identified alstonine and vitexin as the most suitable ligands against the understudied diabetes implicated proteins, all the 7-top scoring compounds possess promising features which may be useful to develop drug targeting multiple therapeutically-relevant proteins of diabetes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Abdullahi AA (2011) Trends and challenges of traditional medicine in Africa. Afr J Tradit Complement Altern Med 8(5 SUPPL.):115–123. https://doi.org/10.4314/ajtcam.v8i5S.5

    Article  PubMed  PubMed Central  Google Scholar 

  • Achari AE, Jain SK (2017) Adiponectin, a therapeutic target for obesity, diabetes, and endothelial dysfunction. Int J Mol Sci 18(6):1321

    Article  PubMed Central  Google Scholar 

  • Baell JB, Holloway GA (2010) New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J Med Chem 53(7):2719–2740. https://doi.org/10.1021/jm901137j

    Article  PubMed  CAS  Google Scholar 

  • Bernstein FC, Koetzle TF, Williams GJ, Meyer EF, Brice MD, Rodgers JR, Kennard O, Shimanouchi T, Tasumi M (1977) The protein data bank: a computer-based archival file for macromolecular structures. J Mol Biol 112(3):535–542. https://doi.org/10.1016/S0022-2836(77)80200-3

    Article  PubMed  CAS  Google Scholar 

  • Brownlee M (2001) Biology of diabetic complications. Nature 414:813–820

    Article  PubMed  CAS  Google Scholar 

  • Chen B-W, Li W-X, Wang G-H, Li G-H, Liu J-Q, Zheng J-J, Wang Q, Li H-J, Dai S-X, Huang J-F (2018) A strategy to find novel candidate anti-alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants. PeerJ 6:e4756

    Article  PubMed  PubMed Central  Google Scholar 

  • Chikezie PC, Okey AO, Kanayo CN (2015) Overview of anti-diabetic medicinal plants: the Nigerian research experience. J Diabetes Metab 6(6):546. https://doi.org/10.4172/2155-6156.1000546

    Article  Google Scholar 

  • Dahiru T, Aliyu AA, Shehu AU (2016) A review of population-based studies on diabetes mellitus in Nigeria. Sub-Saharan Afr J Med 3(2):59

    Article  Google Scholar 

  • Dai S-X, Li W-X, Han F-F, Guo Y-C, Zheng J-J, Liu J-Q, Wang Q, Gao Y-D, Li G-H, Huang J-F (2016) In silico identification of anti-cancer compounds and plants from traditional chinese medicine database. Sci Rep 6:25462

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Daina A, Blatter M-C, Gerritsen VB, Palagi PM, Marek D, Xenarios I, Schwede T, Michielin O, Zoete V (2017) Drug design workshop: a web-based educational tool to introduce computer-aided drug design to the general public. J Chem Educ 94(3):335–344

    Article  CAS  Google Scholar 

  • Ebeling P, Koistinen HA, Koivisto VA (1998) Insulin-independent glucose transport regulates insulin sensitivity. FEBS Lett 436(3):301–303

    Article  PubMed  CAS  Google Scholar 

  • Elekofehinti OO, Ejelonu OC, Kamdem JP, Akinlosotu OB, Famuti A, Adebowale DD, Iwaloye O, Bulu YI, Kade IJ, Rocha JBT (2018) Discovery of potential visfatin activators using in silico docking and ADME predictions as therapy for Type 2 diabetes. Beni-Suef Univ J Basic Appl Sci 7(2):241–249

    Google Scholar 

  • Ezuruike UF, Prieto JM (2014) The use of plants in the traditional management of diabetes in Nigeria: pharmacological and toxicological considerations. J Ethnopharmacol 155(2):857–924. https://doi.org/10.1016/j.jep.2014.05.055

    Article  PubMed  CAS  Google Scholar 

  • Gbolade AA (2009) Inventory of antidiabetic plants in selected districts of Lagos State, Nigeria. J Ethnopharmacol 121(1):135–139

    Article  PubMed  Google Scholar 

  • Gfeller D, Grosdidier A, Wirth M, Daina A, Michielin O, Zoete V (2014) SwissTargetPrediction: a web server for target prediction of bioactive small molecules. Nucl Acids Res 42(W1):W32-38

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Gourgari E, Wilhelm EE, Hassanzadeh H, Aroda VR, Shoulson I (2017) A comprehensive review of the FDA-approved labels of diabetes drugs: indications, safety, and emerging cardiovascular safety data. J Diabetes Complic 31(12):1719–1727

    Article  Google Scholar 

  • Hanwell MD, Curtis DE, Lonie DC, Vandermeersch T, Zurek E, Hutchison GR (2012) Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. J Cheminform 4(1):17

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Hohenberg PC, Kohn W, Sham LJ (1990) The beginnings and some thoughts on the future. Adv Quant Chem 21:7–26

    Article  CAS  Google Scholar 

  • Huang CC, Meng EC, Morris JH, Pettersen EF, Ferrin TE (2014) Enhancing UCSF chimera through web services. Nucl Acids Res 42(W1):W478–W484

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • IDF (2015) Update of mortality attributable to diabetes for the IDF diabetes atlas: estimates for the year 2013. Diabetes Res Clin Pract 109(3):461–465

    Article  Google Scholar 

  • Iwaloye O, Olusola OE, Emmanuel AO, Babatom IK, Toyin MF (2020) Insight into glycogen synthase kinase-3β inhibitory activity of phyto-constituents from melissa officinalis. in silico studies. Silico Pharmacol 8(1):1–13

    Article  Google Scholar 

  • Iwaloye O, Olusola OE, Abiola IM, Kikiowo B, Esther OA (2020) In silico molecular studies of natural compounds as possible anti-alzheimer’s agents: ligand-based design. Netw Model Anal Health Inform Bioinform. https://doi.org/10.1007/s13721-020-00262-7

    Article  Google Scholar 

  • Iwaloye O, Elekofehinti OO, Kikiowo B, Fadipe TM, Akinjiyan MO, Ariyo EO, Aiyeku OO, Adewumi NA (2020a) Discovery of traditional Chinese medicine derived compounds as wild type and mutant plasmodium falciparum dihydrofolate reductase inhibitors: induced fit docking and ADME studies. Curr Drug Discov Technol. https://doi.org/10.2174/1570163817999200729122753

    Article  Google Scholar 

  • Lehrke M, Lazar MA (2005) The many faces of PPARγ. Cell 123(6):993–999

    Article  PubMed  CAS  Google Scholar 

  • Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Lead-and drug-like compounds: the rule-of-five revolution. Adv

  • Lu L, Seidel CP, Iwase T, Stevens RK, Gong Y-Y, Wang X, Hackett SF, Campochiaro PA (2013) Suppression of GLUT1; a new strategy to prevent diabetic complications. J Cell Physiol 228(2):251–257

    Article  PubMed  CAS  Google Scholar 

  • Macintyre AN, Gerriets VA, Nichols AG, Michalek RD, Rudolph MC, Deoliveira D, Anderson SM, Dale Abel E, Chen BJ, Hale LP (2014) The glucose transporter glut1 is selectively essential for cd4 t cell activation and effector function. Cell Metab 20(1):61–72

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Maffucci I, Xiao Hu, Fumagalli V, Contini A (2018) An efficient implementation of the Nwat-MMGBSA method to rescore docking results in medium-throughput virtual screenings. Front Chem 6:43

    Article  PubMed  PubMed Central  Google Scholar 

  • Mohammad M, Al-Masri IM, Issa A, Al-Ghussein MAS, Fararjeh M, Alkhatib H, Taha MO, Bustanji Y (2013) Famotidine inhibits glycogen synthase kinase-3β: an investigation by docking simulation and experimental validation. J Enzyme Inhib Med Chem 28(4):690–694

    Article  PubMed  CAS  Google Scholar 

  • Musoev A, Numonov S, You Z, Gao H (2019) Discovery of novel DPP-IV inhibitors as potential candidates for the treatment of type 2 diabetes mellitus predicted by 3D QSAR pharmacophore models, molecular docking and de novo evolution. Molecules 24(16):2870

    Article  PubMed Central  CAS  Google Scholar 

  • Olawale F, Aninye II, Ajaja UI, Nwozo SO (2020) Long-term hyperglycemia impairs hormonal balance and induces oxidative damage in ovaries of streptozotocin-induced diabetic wistar rat. Niger J Physiol Sci Off Publ Physiol Soc Nigeria 35(1):46–51

    Google Scholar 

  • Pereira ASP, den Haan H, Peña-García J, Moreno MM, Pérez-Sánchez H, Apostolides Z (2019) Exploring African medicinal plants for potential anti-diabetic compounds with the DIA-DB inverse virtual screening web server. Molecules 24(10):2002

    Article  PubMed Central  CAS  Google Scholar 

  • Prime S (2018) LLC: New York, NY, USA

  • Qian M, Haser R, Buisson G, Duee E, Payan F (1994) The active center of a mammalian α-amylase structure of the complex of a pancreatic α-amylase with a carbohydrate inhibitor refined to 2.2-. ANG. Resolution. Biochemistry 33(20):6284–6294

    Article  PubMed  CAS  Google Scholar 

  • Rehman K, Akash MSH (2017) Mechanism of generation of oxidative stress and pathophysiology of type 2 diabetes mellitus: how are they interlinked? J Cell Biochem 118(11):3577–3585

    Article  PubMed  CAS  Google Scholar 

  • Reynolds LJ, Credeur DP, Manrique C, Padilla J, Fadel PJ, Thyfault JP (2017) Obesity, type 2 diabetes, and impaired insulin-stimulated blood flow: role of skeletal muscle no synthase and endothelin-1. J Appl Physiol 122(1):38–47

    Article  PubMed  CAS  Google Scholar 

  • Riera-Guardia N, Rothenbacher D (2008) The effect of thiazolidinediones on adiponectin serum level: a meta-analysis. Diabetes Obes Metab 10(5):367–375

    Article  PubMed  CAS  Google Scholar 

  • Ruiz-Morales Y (2002) HOMO−LUMO gap as an index of molecular size and structure for polycyclic aromatic hydrocarbons (PAHs) and asphaltenes: a theoretical study. I. J Phys Chem A 106(46):11283–11308

    Article  CAS  Google Scholar 

  • Saltiel AR, Ronald Kahn C (2001) Insulin signalling and the regulation of glucose and lipid metabolism. Nature 414(6865):799–806. https://doi.org/10.1038/414799a

    Article  PubMed  CAS  Google Scholar 

  • Schneider P, Röthlisberger M, Reker D, Schneider G (2016) Spotting and designing promiscuous ligands for drug discovery. Chem Commun 52(6):1135–1138

    Article  CAS  Google Scholar 

  • Sgro J-Y (2017) MODELLER-II-Chimera GUI interface

  • Shinkafi TS, Bello L, Hassan SW, Ali S (2015) An ethnobotanical survey of antidiabetic plants used by Hausa-Fulani tribes in Sokoto, Northwest Nigeria. J Ethnopharmacol 172:91–99

    Article  Google Scholar 

  • Teague SJ, Davis AM, Leeson PD, Oprea T (1999) The design of leadlike combinatorial libraries. Angew Chem Int Ed 38(24):3743–3748

    Article  CAS  Google Scholar 

  • Trott O, Olson AJ (2010) AutoDock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31(2):455–461

    PubMed  PubMed Central  CAS  Google Scholar 

  • Tundis R, Loizzo MR, Menichini F (2010) Natural products as α-amylase and α-glucosidase inhibitors and their hypoglycaemic potential in the treatment of diabetes: an update. Mini Rev Med Chem 10(4):315–331

    Article  PubMed  CAS  Google Scholar 

  • Udenta EA, Ikemefuna CO, Oluwafemi OO (2014) Anti-diabetic effects of Nigerian indigenous plant foods/diets. Antioxidant-antidiabetic agents and human health, p 59–93

  • Yamauchi T, Kamon J, Waki H, Terauchi Y, Kubota N, Hara K, Mori Y, Ide T, Murakami K, Tsuboyama-Kasaoka N (2001) The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 7(8):941–946

    Article  PubMed  CAS  Google Scholar 

  • Yang H, Lou C, Sun L, Li J, Cai Y, Wang Z, Li W, Liu G, Tang Y (2019) AdmetSAR 2.0: web-service for prediction and optimization of chemical ADMET properties. Bioinformatics 35(6):1067–1069

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the technical support received from Computational Biologists at Bioinformatics and Molecular Biology Unit, Department of Biochemistry, Federal University of Technology, Akure, Ondo State, Nigeria.

Funding

Not available.

Author information

Authors and Affiliations

  1. Nano-Gene and Drug Delivery Group, Block F3, Level 4, Department of Biochemistry, School of Life Sciences, University of Kwazulu Natal (West Ville), Durban, 4000, South Africa

    Femi Olawale

  2. Nutritional and Industrial Biochemistry Unit, Department of Biochemistry, Faculty of Basic Medical Science, College of Medicine, University of Ibadan, Ibadan, 200005, Oyo State, Nigeria

    Femi Olawale

  3. Department of Biochemistry, Nile University of Nigeria, Abuja, Nigeria

    Kolawole Olofinsan

  4. Bioinformatics and Molecular Biology Unit, Department of Biochemistry, Federal University of Technology, Akure, Ondo State, Nigeria

    Opeyemi Iwaloye

  5. Department of Biochemistry, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria

    Taiwo Emmanuel Ologuntere

Authors
  1. Femi Olawale
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kolawole Olofinsan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Opeyemi Iwaloye
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Taiwo Emmanuel Ologuntere
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Femi Olawale.

Ethics declarations

Ethical approval and Informed consent

This article does not contain any studies involving animals performed by any of the authors. This article does not contain any studies involving human participants performed by any of the authors.

Conflict of interest

Olawale Femi has no conflict of interest. Olofinsan Kolawole has no conflict of interest. Opeyemi Iwaloye has no conflict of interest. Taiwo Emmanuel Ologuntere has no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 281 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Olawale, F., Olofinsan , K., Iwaloye, O. et al. Phytochemicals from Nigerian medicinal plants modulate therapeutically-relevant diabetes targets: insight from computational direction. ADV TRADIT MED (ADTM) 22, 723–737 (2022). https://doi.org/10.1007/s13596-021-00598-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13596-021-00598-z

Keywords

Search

Navigation