Artificial Intelligence and Computational Workflows for Prioritizing Ethnobotanical Leads in Sickle Cell Disease: A Critical Review of Hypothesis Generation and Translational Prerequisites
DOI:
https://doi.org/10.51412/psnnjp.2026.029Keywords:
Sickle cell disease, Ethnopharmacology, Molecular docking, Machine learning, Polypharmacology, Lead prioritizationAbstract
Background: Sickle cell disease (SCD) remains a major global health burden, particularly in subSaharan Africa and South Asia, where access to curative gene therapies is constrained by cost and infrastructure. While medicinal plants represent a vital source of therapeutic leads, identifying bioactive compounds and elucidating their mechanisms remains a bottleneck. In this critical integrative review, we evaluate how computational tools can prioritize plant-derived candidates and generate testable hypotheses for SCD therapeutics.
Methods: A structured literature search was conducted across PubMed, Scopus, Web of Science, Google Scholar, and ScienceDirect for articles published between January 2011 and June 2026. Studies applying machine learning, molecular docking, QSAR, graph neural networks (GNNs), or network pharmacology to plant-derived natural products targeting SCD endpoints were evaluated using a 6-domain risk-of-bias framework.
Results: Out of 412 identified records, 49 total studies were included in the synthesis. This comprises 15 primary computational studies (Tier 1), 18 empirical ethnobotanical/anti-sickling assay studies (Tier 2), and 16 contextual, methodological, and governance publications (Tier 3). Synthesized evidence demonstrates that hybrid pipelines combining GNNs or QSAR with molecular dynamics simulations outperform static docking in predicting hits against the β6 Val hydrophobic pocket and epigenetic γ-globin repressors. However, fewer than 30% of computationally predicted leads underwent prospective in vitro cross-validation.
Conclusion: Computational modeling serves as a powerful engine for lead prioritization and hypothesis generation rather than an accomplished clinical solution. Translating these computational leads into viable SCD therapeutics requires pairing in silico pipelines with prospective experimental validation, chromatographic quality control, and data sovereignty frameworks under the Nagoya Protocol.
References
1. Bou-Fakhredin R, De Franceschi L, Motta I, Cappellini MD, Taher AT (2022). Pharmacological induction of fetal haemoglobin in beta-thalassemia and sickle cell disease: An updated perspective. Pharmaceuticals, 15:753. https://doi.org/10.3390/ph15060753
2. Ayuba SA, Bashar F, Abbas AY (2025). Targeting fetal haemoglobin induction in sickle cell anaemia: Epigenetic and gene-modifying therapeutic strategies. International Journal of Epigenetics, 5:6. https://doi.org/392/ije.2025.29
3. Anupama P, Justin Y, Jonathan W, Alex P, Zachary K, Ashwin P (2025). In vitro and in vivo FOXO3-dependent induction of fetal haemoglobin. Blood, 146:2927–292. https://doi.org/10.1182/blood-2025-2927
4. Ahmed MH, Ghatge MS, Safo MK (2020). Hemoglobin: Structure, function and allostery. Subcellular Biochemistry, 94:345–382. https://doi.org/10.1007/978-3-030-41769-7_14
5. Hannemann A, Cytlak UM, Rees DC, Tewari S, Gibson JS (2014). Effects of 5-hydroxymethyl-2-furfural on the volume and membrane permeability of red blood cells from patients with sickle cell disease. The Journal of Physiology, 592(18):4039–4049. https://doi.org/10.1113/jphysiol.2014.277681
6. Ballreich J, Odouard IC, Socal MP (2025). The CMS sickle cell gene therapy access model. JAMA Pediatrics, 179:118–120. https://doi.org/10.1001/jamapediatrics.2024.553
7. Cancado R, Costa FF (2026). Drug development for sickle cell disease: Repeated setbacks, yet there remains an optimistic outlook for future breakthroughs. Hematology, Transfusion and Cell Therapy, 48:106251. https://doi.org/10.1016/j.htct.2025.106251
8. Alli LA, Nnodu OE (2020). Anti-sickling efficacy of methanolic extract of medicinal plants from Gwagwalada, Nigeria. West African Journal of Medicine, 37:790–795.
9. Kotue TC, Wirba LN, Jayamurthy P, Pieme AC, Kansci G, Fokou E (2019). HPLC profiling, in vitro antisickling and antioxidant activities of amino acids from black bean seeds used in the management of sickle cell disease in the West region of Cameroon. International Journal of Current Research, 11:5872–5880. https://doi.org/10.24941/ijcr35717.08.2019
10. Souleymane HD, Djibo AK, Seyni SH, Zakaria O, Botezatu AV, Dinica RM (2023). Phytochemical characterization and in vitro evaluation of the anti-sickle cell activity of aqueous and ethanolic extract of two medicinal plants from Niger: Flueggea virosa (Roxb. ex Willd.) Royle and Kigelia africana (Lam.) Benth. Plants, 12:3522. https://doi.org/10.3390/plants12203522
11. Peng YL, Zeng N, Yao QY, Peng CY, Sheng WB, Li B (2023). Review of the medicinal uses, phytochemistry and pharmacology of genus Flueggea. Current Chinese Science, 3:213–241.
12. Olivares-Vicente M, Barrajon-Catalan E, Herranz-Lopez M, Segura-Carretero A, Joven J, Encinar JJA, Micol V (2018). Plant-derived polyphenols in human health: Biological activity, metabolites and putative molecular targets. Current Drug Metabolism, 19:351–369. https://doi.org/10.2174/1389200219666180220095236
13. Ding S, Yang Y, Tan T, Wei Q, Shen Z, Liu Q, Song X, Wang Y, Nzilia C, Chow CWK (2025). Quantitative structure-activity relationship (QSAR) modelling for adsorption of organic compounds by activated carbon based on Freundlich adsorption isotherm. PLOS ONE, 20(12):e0338483. https://doi.org/10.1371/journal.pone.0338483
14. Agu PC, Nduneseokwu NC, Nwiziogo FC, Okafor MU, Alum EU, Egwu CO, Anidu IC, Ezinwa CA, Ibiam AU, Aja PM (2025). Historical and ethnopharmacological perspectives on African medicinal plants: From traditional remedies to computational drug discovery. Scientific Africa, 30:e02941. https://doi.org/10.1016/j.sciaf.2025.e02941
15. Pagare PP, Ghatge MS, Chen Q, Musayev F, Venitz J, Abdulmalik O, Zhang Y, Safo MK (2020). Exploration of structure-activity relationship of aromatic aldehydes bearing pyridinylmethoxy-methyl esters as novel antisickling agents. Journal of Medicinal Chemistry, 63(23):14724–14739. https://doi.org/10.1021/acs.jmedchem.0c01287
16. Gbolo BZ, Eltayb WA, Ngbolua KN, Shabana S, Semay I, Hamouda HI, Gerbaux P, Mohsen M, Kitete EM, Mpiana PT, Wang X, Duez P, Abdalla M (2026). Computational approach by molecular docking and molecular dynamics of compounds from two Congolese medicinal plants as potent antisickling agents. Pharmacological Research – Natural Products, 10:100516. https://doi.org/10.1016/j.prenap.2026.100516
17. Bharatti D, Nirhali S, Puri A, Mohite P, Singh S (2025). Development, molecular docking, and anti-anemia potential of polyherbal formulation. Biology, 14(8):1052. https://doi.org/10.3390/biology14081052
18. Praveen KSN, Charu S (2024). Structural dynamics of haemoglobin subunit beta in sickle cell disease: Insights from AlphaFold predictive models. Nanotechnology Perspectives, 20:2360–2370.
19. Luong K, Singh A (2024). Application of transformers in chemoinformatics. Journal of Chemical Informatics & Modeling, 10:2070. https://doi.org/10.1021/acs.jcim.3c2070
20. Talen MJ, Malik P, Vercellotti GM (2019). Therapeutic strategies for sickle cell disease: Towards a multi-agent approach. Nature Reviews Drug Discovery, 18:139–158. https://doi.org/10.1038/s41573-018-0003-2
21. Xu X, Ghatge MS, Huang B, Alghamdi A, Wang H, Pierce BD, Abdulmalik O, Zhang Y, Safo MK, Venitz J (2023). Quantitative assessment of the in vitro binding kinetics of antisickling aromatic aldehydes with haemoglobin A: A universal HPLC-UV/Vis method to quantify Schiff-base adduct formation. Journal of Pharmaceutical and Biomedical Analysis, 223:115152. https://doi.org/10.1016/j.pba.2022.115152
22. Das DR, Kumar D, Kumar P, Dash BP (2020). Molecular docking and its application in search of antisickling agent from Carica papaya. Journal of Applied Biology & Biotechnology, 8(1):105–116. https://doi.org/10.7324/JABB.2020.80117
23. Hamsa CB, Bhavani K, Muthukumar A, Srivastava N, Paarakh PM (2025). In silico docking studies of various compounds of Euphorbia hirta L. plant on ferritin, oxyhemoglobin, hepcidin, and transferrin receptors. Journal of Microbiology, Biotechnology and Food Sciences, 14(4):1–9. https://doi.org/10.55251/jmbfs.11047
24. Khare S, Chatterjee T (2026). Computational insights into the interactions of andrographolide derivative SRJ09 with histone deacetylase for the management of beta thalassemia. Journal of Exploratory Research in Pharmacology, 11(1):e00039. https://doi.org/10.14218/JERP.2025.00039
25. Zagrean-Tuza C, Igescu I, Lupan A, Silaghi-Dumitrescu R (2024). A study of the molecular interactions of haemoglobin with diverse classes of therapeutic agents. Inorganica Chimica Acta, 567:122053. https://doi.org/10.1016/j.ica.2024.122053
26. Burman MD, Bag S, Ghosal S, Karmakar S, Pramanik G, Chinnadurai RK, Bhowmik S (2023). Exploring the structural importance of the C3–C4 double bond in plant alkaloids harmine and harmaline on their binding interactions with haemoglobin. ACS Omega, 8(40):37054–37064. https://doi.org/10.1021/acsomega.3c04432
27. Olagunju MO, Loscwittz J, Olubiyi OO, Strodel B (2022). Multiscale MD simulations of wild-type and sickle haemoglobin aggregation. Proteins, 90:1811–1824. https://doi.org/10.1002/prot.26352
28. Mswahili ME, Jeong Y (2024). Transformer-based models for chemical SMILES representation: A comprehensive literature review. Heliyon, 10:e39038. https://doi.org/10.1016/j.heliyon.2024.e39038
29. Paerhati Y, Aikebaier A, Dilimulati D, Baishan A, Yusufujiang N, Qui X, Wusiman Y, Zhou W (2026). Rethinking nature's pharmacy: AI era and natural product drug discovery. Pharmaceuticals, 19:301. https://doi.org/10.3390/ph19020301
30. Alves LA, Maricato V, Alberto AV (2020). Graph neural networks as a potential tool in improving virtual screening programs. Frontiers in Chemistry, 9:2021. https://doi.org/10.3389/fchem.2021.787194
31. Machado TF, Neto FCB, Goncalves MS, Barbosa CG, Barreto ME (2024). Exploring machine learning algorithms in sickle cell disease patient data: A systematic review. PLOS ONE, 19:e0313315. https://doi.org/10.1371/journal.pone.0313315
32. Suryawanshi RM, Deepak P, Gilhotra RM (2026). AI in ethnopharmacology, the pharmaceutical industry, and its applications. Annales Pharmaceutiques Françaises, 84:161–174. https://doi.org/10.1016/j.pjharma.2025.11.011
33. Hanindhito B, Fathi A, Gourounas D, Trenev D, Gerslauer A, John LK (2025). Technology trends in computing hardware and their impacts on high-performance scientific computing part I: General-purpose processors and hardware accelerators. International Journal of High Performance & Computer Application, 39:45–58. https://doi.org/10.1177/1094342025134799
34. Estepp JH (2018). Voxelotor (GBT440), a first-in-class haemoglobin oxygen-affinity modulator, has promising and reassuring preclinical and clinical data. American Journal of Hematology, 93(3):326–329. https://doi.org/10.1002/ajh.25042
35. Yesudasan S, Wang X, Averrett RD (2018). Molecular dynamics simulations indicate that deoxyhemoglobin, oxyhemoglobin, carboxyhemoglobin, and glycated haemoglobin under compression and shear exhibit an anisotropic mechanical behaviour. Journal of Biomolecular Structural Dynamics, 36(6):1417–1429. https://doi.org/10.1080/07391102.2017.1323674
36. Gertsch J (2011). Botanical drugs, synergy, and network pharmacology: Forth and back to intelligent mixture. Planta Medica, 77(11):1086–1098. https://doi.org/10.1055/s-0030-1270904
37. Zhai Y, Liu L, Zhang F, Chen X, Wang H, Zhou J, Chai K, Liu J, Lei H, Lu P, Guo M, Gou J, Wu J (2025). Network pharmacology: A crucial approach in traditional Chinese medicine research. Chinese Medicine, 20:8. https://doi.org/10.1186/s13020-024-01056-z
38. Ameh SJ, Tarfa FD, Ebeshi BU (2012). Traditional herbal management of sickle cell anemia: Lessons from Nigeria. Anemia, 2012:607436. https://doi.org/10.1155/2012/607436
39. Javed D, Rai AK, TH A, Molakapuri ST, Ahmad A, Dhingra (2026). Efficacy of traditional medicine in the management of sickle cell disease: A scoping review of current evidence. Journal of Complementary and Integrative Medicine, 23(1):43–61. https://doi.org/10.1515/jcim-2025-0238
40. Ray M, Verma D, Ahirwar B (2026). A comprehensive review on medicinal plants for potential therapeutic applications in breast cancer and sickle cell anemia in women. International Journal of Green Pharmacy, 20(2):1–14.
41. Ahajumobi NE, Asika JC (2024). Afro medicinal plants: A promising remedy for sickle cell anemia. International Blood Research & Reviews, 15(1):26–37. https://doi.org/10.9734/ibrr/2024/v15i1332
42. Chandran U, Mehendale N, Patil S, Chaguturu R, Patwardhan B (2016). Network pharmacology. Innovative Approaches in Drug Discovery, 14:127–164. https://doi.org/10.1016/B978-0-12-801814-9.00005-2
43. Tian T, Wang P, Zhao D, Zeng J (2026). Network pharmacology and drug repurposing. In: Li H, Zheng M, Zhu F, Bai F (eds). Artificial Intelligence for Drug Design. Springer, Singapore. https://doi.org/10.1007/978-981-95-2525-6_30
44. Kurre MK, Patra S, Patra PK (2025). In vitro antisickling activities of Sorghum bicolor (L.) Moench. International Journal of Advanced Research, 13(3):326–332. https://doi.org/10.21474/IJAR01/20570
45. Sunday BY, Terkimbi SD, Ben OM, Bukke SPN, Charles II, Ninsiima HI, Afodun AM, Kibirige J, Latif SIA, Eze ED (2026). Systematic review on plant-based therapies for the management of sickle cell anemia. Anemia, 2026:9936958. https://doi.org/10.1155/anem/2026/9936958
46. Merecz-Sadowska A, Sadowski A, Zielinska-Blizniewska H, Zajdel K, Zajdel R (2025). Network pharmacology as a tool to investigate the antioxidant and anti-inflammatory potential of plant secondary metabolites: A review and perspectives. International Journal of Molecular Sciences, 26(14):6678. https://doi.org/10.3390/ijms26146678
47. Panossian A (2026). Network pharmacology and natural products in modern drug discovery: Emerging trends, challenges, and future direction. Pharmaceutics, 19(5):653. https://doi.org/10.3390/ph19050653
48. Lee H-S, Lee I-H, Park S-I, Lee D-Y (2020). Network pharmacology-based investigation of the system-level molecular mechanisms of the hematopoietic activity of Samul-Tang, a traditional Korean herbal formula. Evidence-Based Complementary and Alternative Medicine, 2020:9048089. https://doi.org/10.1155/2020/9048089
49. Dash BP, Archana Y, Satapathy N, Naik SK (2013). Search for antisickling agents from plants. Pharmacognosy Reviews, 7(13):53–60. https://doi.org/10.4103/0973-7847.112849
50. Kple TTKM, Akue JA, Golly JK, Fofie Y, Ahon MG, Kra MA, Sanogo I, Chiaye A, Yapo-Crezoit (2020). Phytochemical characterization of three plants and their antisickling activity in the management of sickle cell disease. Journal of Biosciences and Medicines, 8(6):1–11. https://doi.org/10.4236/jbm.2020.86010
51. Nurain IO, Bewaji CO, Johnson JS, Davenport RD, Zhang Y (2018). Potential of three ethnomedicinal plants as antisickling agents. Molecular Pharmaceutics, 14:172–182. https://doi.org/10.1021/acs.molpharmaceut.6b00767
52. Asibor YE, Oyebamiji AK, Latona DF (2024). Computational screening of phytochemicals present in some Nigerian medicinal plants against sickle cell disease. Scientific Reports, 14:26368. https://doi.org/10.1038/s41598-024-75078-w
53. Chele KH, Piater L, Van JJ, Tugizimana F (2025). Bridging ethnobotanical knowledge and multi-omics approaches for plant-derived natural product discovery. Metabolites, 15:362. https://doi.org/10.3390/metabo15060362
54. Olori EO, Olubiyi OO, Babalola CP (2023). Hoslundia opposita and other Nigerian plants inhibit sickle haemoglobin polymerization and prevent erythrocyte sickling: A virtual screening-guided identification of bioactive plants. International Journal of Rare Disease and Orphan Drugs, 6:1015. https://doi.org/10.47739/2576-0092/1015
55. Maturana-Perez LR, Marquez-Lazaro J, Contreras-Puentes N, Alviz-Amador AA, Marrugo-Padilla A (2024). Identification of proinflammatory pathways and bioactive polyphenols for the treatment of sickle cell anemia by in silico study and network pharmacology. Information Medicine Unlocked, 49:101534. https://doi.org/10.1016/j.imu.2024.101534
56. Gopalsamy A, Aulabaugh AE, Barakat A, Beaumont K, Cabral S, Canterbury DP (2021). PF-07059013: A noncovalent modulator of haemoglobin for treatment of sickle cell disease. Journal of Medicinal Chemistry, 64(1):326–342. https://doi.org/10.1021/acs.jmedchem.0c01518
57. Donkor AK, Pagare PP, Mughram M, Safo MK (2023). X-ray crystallography and sickle cell disease drug discovery—a tribute to Donald Abraham. Frontiers in Molecular Biosciences, 10:1136970. https://doi.org/10.3389/fmolb.2023.1136970
58. Ala C, Joshi RP, Gupta P, Ramalingam S, Sankaranarayanan M (2023). Discovery of potent DNMT1 inhibitors against sickle cell disease using structure-based virtual screening, MMGBSA and molecular dynamics simulation-based approaches. Journal of Biomolecular and Structural Dynamics, 21:234. https://doi.org/10.1080/073911102.2023.2199081
59. Onyegeme-Okerenta BM, Essien EB, Essin JJ (2019). Antisickling properties of aqueous extracts of Dennettia tripetala and Physalis angulata. Asian Journal of Biological Sciences, 12:772–778.
60. Razafindrakoto ZR, Tombozara N, Mahitasoa FJE, Solofoniaina M, Tatafasa ET, Andrianjara C, Ramanitrahasimbola D (2026). Biological screening of medicinal plants used by SCD patients in the eastern part of Madagascar for their anti-sickling and analgesic activities. South African Journal of Botany, 190:11–20. https://doi.org/10.1016/j.sajb.2025.12.027
61. Sambayi G, Mwakalukwa R, Ngassapa OD, Pieters L, Tuenter E (2026). Ethnopharmacological survey of medicinal plants traditionally used to manage sickle cell disease in Mwanza and Mara regions, Tanzania. Scientific Africa, 31:e03291. https://doi.org/10.1016/j.sciaf.2026.e03291
62. Yembeau NL, Nya PCB, Pieme CA, Tchouane KD, Fotsing CBK, Nkwikeu PJN, Feudjio AF, Telefo PB (2022). Ethnopharmacological study of the medicinal plants used in the treatment of sickle cell anemia in the West Region of Cameroon. Evidence-Based Complementary and Alternative Medicine, 2022:5098428. https://doi.org/10.1155/2022/5098428
63. Chambhare MR, Kadam NS, Doshi P, Kate SL, Nikule HA, Nikam TD (2025). Anti-sickling potential and bioactive metabolites from edible oil-yielding crop Guizotia abyssinica (L.f.) Cass. Notulae Scientia Biologicae, 17:1. https://doi.org/10.55779/nsb17112164
64. Shahrezaei A, Taherkhani S, Lili D, Garmaroodi GA, Nasirinezhad F (2026). Herbal medicine meets machine learning: A systematic review of AI-powered innovation in chronic inflammation management. Discover Applied Sciences, 8:111. https://doi.org/10.1007/s42452-025-08116-5
65. Tejesh K, Chaitali AC, Dakhale GN (2025). Network pharmacology: A systems-based paradigm for modern drug discovery. National Journal of Pharmacology and Therapeutics, 3(3):194–196. https://doi.org/10.4103/NJPT.NJPT_57_25
66. Muthuraj R, Chandrasekaran J (2026). Nature meets machine: The AI renaissance in natural product drug discovery. Natural Product Bioprospecting, 16:37. https://doi.org/10.1007/s13659-025-00589-6
67. Shumba DS (2025). Beyond oral tradition: Digitalizing indigenous environmental knowledge for climate resilience in Africa. In: Ramutsindela M (ed), Environments, Ecosystems, and Ecologies, in Diener AC and Hagen J (eds), Oxford Intersections: Borders. Oxford Academic, online edition. https://doi.org/10.1093/9780198945222.003.010
68. Kirboga KK, Aktas E, Kucuksille EU, Rudrapal M (2026). Structure-based virtual screening of plant-derived flavonoids as putative GLUT9 binders with antioxidant properties. Molecules, 31(4):593. https://doi.org/10.3390/molecules31040593
69. Olanipekun MK (2024). Ethnobotanical insight into sickle cell disease management: A comprehensive study of medicinal plants utilized in Ondo Local Government Area, Ondo State, Nigeria. Journal of Pharmacy and Biological Sciences, 19:5–14. https://doi.org/10.9790/3008-1902020514
70. Starlard-Davenport A, Gu Q, Pace BS (2022). Targeting genetic modifiers of HBG gene expression in sickle cell disease: The miRNA option. Molecular Diagnostics and Therapeutics, 26:497–509. https://doi.org/10.1007/s40291-022-00589-z
71. Wang X, Thein SL (2018). Switching from fetal to adult haemoglobin. Nature Genetics, 50:478–480. https://doi.org/10.1038/s41588-018-0094-z
72. Esrick EB, McConkey M, Lin K, Frisbee A, Ebert B (2016). Inactivation of HDAC1 or HDAC2 induces gamma globin expression without altering cell cycle or proliferation. American Journal of Hematology, 90(7):624–628. https://doi.org/10.1002/ajh.24019
73. Amani MB, Helene MM, Ange MM, Elodie NB, Rachel NA, Patrick MB, Salomon BA, Roland MD (2026). Evidence-based management of sickle cell disease: Ethnobotanical survey and laboratory validation of traditional herbal recipes. Molecules, 31(7):1192. https://doi.org/10.3390/molecules31071192
74. Bell V, Varzakas T, Psaltopoulou T, Fernandes T (2024). Sickle cell disease update: New treatments and challenging nutritional interventions. Nutrients, 16:258. https://doi.org/10.3390/nu16020258
75. Saunthararajah S (2019). Targeting sickle cell disease root-cause pathophysiology with small molecules. Haematologica, 104:1720–1730. https://doi.org/10.3324/haematol.2018.207530
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