Antianaemic Potential of Flavonoids from Ajwa Date Fruits: An In Silico Study
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Abstract
Iron deficiency anemia (IDA) is a hematologic disease that can occur in all age groups. Globally, it is estimated that 29-43% of women of child bearing age (15 – 49 years) are affected by anaemia. A majority of those affected are pregnant women and adolescent girls. Erythropoietin (EPO) is currently being used as one of the biomarkers of anemia. This study aimed to predict the antianaemic potential of flavonoids extracted from Ajwa Date Fruit through molecular docking.
The in silico study was done using Autodock Vina software with Vega ZZ, PyMOL, and BIOVIA Discovery Studio programs to create visual profiles of EPO native ligand together with six test compounds; Flavocommelin, Complanatuside, Isoschaftoside, Kaempferol-3-O-gentiobioside, Kaempferol-3-O-rutinuside, and Spinosin. Pharmacokinetic predictions were done using the pkCSM approach. Post-docking analyses such as binding affinities and pharmacokinetic predictions showed that the flavonoid compounds have high binding free energy, similar to standard therapeutic agent (iron, Fe), and exhibited excellent pharmacokinetic profile. The flavonoid complanatuside (4-(2- Hydroxyethyl -1- piperazine ethanesulfonic acid) had the best binding affinity with docking score of -5.01 kcal/mol (371.11%), which was comparable to the docking score of the positive control ligand (Fe) (-4.37 kcal/mol). The root mean square deviation (RMSD) values for EPO were 0.710 Å, 0.300 Å, and 2.007 Å. Therefore, flavonoids from Ajwa date fruits especially complanatuside have the potential to be used as natural compounds for the treatment of iron deficiency anaemia.
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References
Onyeabo C, Achi NK, Ekeleme-Egedigwe CA, Ebere CU, Okoro CK. Haematological and biochemical studies on Justicia carnea leaves extract in phenylhydrazine induced-anemia in albino rats. Acta Sci Pol Technol Aliment. 2017; 16(2):217–230.
Pasricha SR and Drakesmith H. Iron deficiency anemia: problems in diagnosis and prevention at the population level. Hematol Oncol Clin North Am. 2016; 30(2):309-325.
Kiss JE and Vassallo RR. How do we manage iron deficiency after blood donation? Br J Haematol. 2018; 181(5):590–603.
Ekasanti I, Adi AC, Yono M, Isfandiari MA. Determinants of Anemia among Early Adolescent Girls in Kendari City. Amerta Nutr. 2020; 4(4):271–279.
World Health Organization. Anaemia in Women and Children: WHO Global Anaemia Estimates [Internet]. 2021st ed. Geneva, Switzerland: World Health Organization; 2021 [cited 2021 Sep 29]. Available from: https://www.who.int/data/gho/data/themes/topics/anaemia_in_ women_and_children
Riskesdas. Riskesdas DKI Jakarta 2018. 2018.
Khalid S, Ahmad A, Kaleem M. Antioxidant activity and phenolic contents of Ajwa date and their effect on lipo-protein profile. Funct Foods Health Dis. 2017; 7(6):396-410.
Hasanah AM, Kurniawan K, Fadholah A. Perbandingan Kadar Total Flavonoid Metode Infusa Dan Rendaman Buah Kurma Ajwa (Phoenix dactylifera L) Menggunakan Spektrofotometri Uv-Vis. J Ilmah Glob Farm. 2023; 2023:9–17.
Kaliawan K and Danardono P. Kuantifikasi Senyawa Flavonoid Dengan Lc-Ms/Ms Secara Simultan. Distilat: J Teknol Sep. 2023; 7(1):66–73.
Pasricha SR, Tye-Din J, Muckenthaler MU, Swinkels DW. Iron deficiency. Lancet. 2021; 397(10270):233-248.
Muckenthaler MU, Rivella S, Hentze MW, Galy B. A red carpet for iron metabolism. Cell. 2017; 168(3):344-361.
Daina A, Michielin O, Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017; 7:1–13.
Rahim F, Putra PP, Ismed F, Putra AE, Lucida H. Molecular Dynamics, Docking and Prediction of Absorption, Distribution, Metabolism and Excretion of Lycopene as Protein Inhibitor of Bcl2 and DNMT1. Trop J Nat Prod Res. 2023; 7(7):3439–3444.
Chen T, Shu X, Zhou H, Beckford FA, Misir M. Algorithm selection for protein–ligand docking: strategies and analysis on ACE. Sci Rep. 2023; 13(1):8219.
Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, Li Q, Shoemaker BA, Thiessen PA, Yu B, Zaslavsky L, Zhang J, Bolton EE. PubChem in 2021: New data content and improved web interfaces. Nucl Acids Res. 2021; 49(D1):D1388–D1395.
Suharti N, Sari MR, Dillasamola D, Putra PP. In Silico and In Vitro Study of The Ethanol Extract of The White Garland Lily (Hedychium coronarium J. Koenig) as a Tyrosinase Inhibitor. Trop J Nat Prod Res. 2023; 7(6):3125–3129.
Acúrcio RC, Leonardo-Sousa C, García-Sosa AT, Salvador JA, Florindo HF, Guedes RC. Structural insights and binding analysis for determining the molecular bases for programmed cell death protein ligand-1 inhibition. Med Chem Comm. 2019; 10(10):1810–1818.
Du X, Li Y, Xia YL, Ai SM, Liang J, Sang P, Ji XL, Liu SQ. Insights into protein–ligand interactions: Mechanisms, models, and methods. Int J Mol Sci. 2016; 17(2):1–34.
Inayati I, Arifin NH, Febriansah R, Indarto D, Suryawati B, Hartono H. Trans-Cinnamaldehyde Inhibitory Activity Against mrkA, treC, and luxS Genes in Biofilm-forming Klebsiella pneumoniae: An In Silico Study. Trop J Nat Prod Res. 2023; 7:4249–4255.
Johnson TA, McLeod MJ, Holyoak T. Utilization of Substrate Intrinsic Binding Energy for Conformational Change and Catalytic Function in Phosphoenolpyruvate Carboxykinase. Biochem. 2016; 55(3):575–587.
Mahanthesh MT, Ranjith D, Raghavendra Yaligar, Jyothi R, Narappa G and Ravi MV. Swiss ADME prediction of phytochemicals present in Butea monosperma (Lam.) Taub. J Pharmacogn Phytochem. 2020; 9(3):1799–1809.
Chagas CM, Moss S, Alisaraie L. Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five. Int J Pharmaceut. 2018; 549(1–2):133–149.
Shakil S. Molecular interaction of inhibitors with human brain butyrylcholinesterase. EXCLI J. 2021; 20:1597–1607.
Alves VM, Muratov E, Capuzzi SJ, Politi R, Low Y, Braga RC, Zakharov AV, Sedykh A, Mokshyna E, Farag S, Andrade CH, Kuz’min V, Fourches D, Tropsha A. Alarms about structural alerts. Green Chem. 2016; 18(16):4348–4360.
Mora JR, Marrero-Ponce Y, García-Jacas CR, Suarez Causado A. Ensemble Models Based on QuBiLS-MAS Features and Shallow Learning for the Prediction of Drug-Induced Liver Toxicity: Improving Deep Learning and Traditional Approaches. Chem Res Toxicol. 2020; 33(7):1855–1873.
Tsaioun K, Blaauboer BJ, Hartung T. Evidence-based absorption, distribution, metabolism, excretion (ADME) and its interplay with alternative toxicity methods. Altex. 2016; 33(4):343–358.
Mvondo JGM, Matondo A, Mawete DT, Bambi SMN, Mbala BM, Lohohola PO. In Silico ADME/T Properties of Quinine Derivatives using SwissADME and pkCSM Webservers. Int J Trop Dis Health. 2021; 42(11):1–12.
Wahyuningsih D, Purnomo Y, Tilaqza A. In Silico Study of Pulutan (Urena lobata) Leaf Extract as Anti Inflammation and their ADME Prediction. J Trop Pharm Chem. 2022; 6(1):30–37.