Withanolide Scaffold in Drug Discovery: A Review of Structural Modifications, Structure-Activity Relationships, and Pharmacological Targets
DOI:
https://doi.org/10.59436/jsiane.v6i2.8.2583-2093Keywords:
withanolides; structure–activity relationships; covalent drug discovery; Michael acceptor; steroidal lactone; Withania somniferaAbstract
Withanolides are C-28 polyoxygenated steroidal lactones that are characterised by a pair of C2-C3 enones and an α,β-unsaturated d-lactone held in fixed space geometry by a rigid ergostane tetracyclic core. The architecture allows specific covalent interaction with nucleophilic cysteine targets in the protein of interest of mechanobiological interest and has been utilised in a polypharmacology profile of anticancer, anti-inflammatory, neuroprotective, and immunomodulatory activities. A pre-existing SAR dataset of significant chemical depth in more than 1,200 natural analogues spread out in 15 genera in the Solanaceae provides a basis that is further extended by emerging semi-synthetic literature. This review critically discusses the medicinal chemistry-based analysis of withanolide scaffold modification as structural changes at the A-ring enone, lactone ring, peripheral hydroxyl positions and C-17 side chain translate into defined biological outcomes at molecular targets of validated structure requirements that are defined as pharmacophoric elements. Cytotoxic, anti-inflammatory and neuroprotective phages, with their structural separability being a key feature, are is the new opportunities in chemoproteomics-mediated target discovery, biosynthetic engineering and targeted covalent drug design
References
Abdelsayed, M. (2025). AI-driven polypharmacology in small-molecule drug discovery. International Journal of Molecular Sciences, 26. https://doi.org/10.3390/ijms26146996
Ahmad, Z., Ganie, I. H., Firdaus, F., Ramakrishnan, M., Shahzad, A., & Ding, Y. (2024). Enhancing withanolide production in the Withania species: Advances in in vitro culture and synthetic biology approaches. Plants, 13. https://doi.org/10.3390/plants13152171
Alqahtani, M. S., Kazi, M., Alsenaidy, M. A., & Ahmad, M. Z. (2021). Advances in oral drug delivery. Frontiers in Pharmacology, 12. https://doi.org/10.3389/fphar.2021.618411
Anstine, D. M., & Isayev, O. (2023). Generative models as an emerging paradigm in the chemical sciences. Journal of the American Chemical Society, 145, 8736–8750. https://doi.org/10.1021/jacs.2c13467
Atanasov, A. G., Zotchev, S. B., Dirsch, V. M., & Supuran, C. T. (2021). Natural products in drug discovery: Advances and opportunities. Nature Reviews Drug Discovery, 20, 200–216. https://doi.org/10.1038/s41573-020-00114-z
Atteeq, M. (2022). Evaluating anticancer properties of Withaferin A—a potent phytochemical. Frontiers in Pharmacology, 13, 975320. https://doi.org/10.3389/fphar.2022.975320
Bailly, C. (2024). Covalent binding of withanolides to cysteines of protein targets. Biochemical Pharmacology, 116405. https://doi.org/10.1016/j.bcp.2024.116405
Bashir, A., Nabi, M., Tabassum, N., Afzal, S., & Ayoub, M. (2023). An updated review on phytochemistry and molecular targets of Withania somnifera (L.) Dunal (Ashwagandha). Frontiers in Pharmacology, 14, 1049334. https://doi.org/10.3389/fphar.2023.1049334
Békés, M., Langley, D. R., & Crews, C. M. (2022). PROTAC targeted protein degraders: The past is prologue. Nature Reviews Drug Discovery, 21, 181–200. https://doi.org/10.1038/s41573-021-00371-6
Bi, X., Wang, Y., Wang, J., & Liu, C. (2025). Machine learning for multi-target drug discovery: Challenges and opportunities in systems pharmacology. Pharmaceutics, 17. https://doi.org/10.3390/pharmaceutics17091186
Boike, L., Henning, N. J., & Nomura, D. K. (2022). Advances in covalent drug discovery. Nature Reviews Drug Discovery, 21, 881–898. https://doi.org/10.1038/s41573-022-00542-z
Bond, M. J., & Crews, C. M. (2021). Proteolysis targeting chimeras (PROTACs) come of age: Entering the third decade of targeted protein degradation. RSC Chemical Biology, 2, 725–742. https://doi.org/10.1039/d1cb00011j
Che, W., Wojitas, L., Shan, C., & Lopchuk, J. M. (2024). Divergent synthesis of complex withanolides enabled by a scalable route and late-stage functionalization. Science Advances, 10. https://doi.org/10.1126/sciadv.adp9375
Chehelgerdi, M., Chehelgerdi, M., Allela, O. Q. B., Pecho, R. D. C., Jayasankar, N., Rao, D. P., Thamaraikani, T., Vasanthan, M., Polák, V., Lakshmaiya, N., Saadh, M. J., Amajd, A., Abo-Zaid, M. A., Castillo-Acobo, R. Y., Ismail, A. H., Amin, A. H., & Akhavan-Sigari, R. (2023). Progressing nanotechnology to improve targeted cancer treatment: Overcoming hurdles in its clinical implementation. Molecular Cancer, 22. https://doi.org/10.1186/s12943-023-01865-0
Chen, F., Li, C., Cao, H., Zhang, H., Lu, C., Li, R., Zhu, Z., Chen, L., & Zhao, Y. (2022). Identification of adenylate kinase 5 as a protein target of ginsenosides in brain tissues using mass spectrometry-based DARTS and CETSA techniques. Journal of Agricultural and Food Chemistry. https://doi.org/10.1021/acs.jafc.1c07819
Cichońska, A., Ravikumar, B., & Rahman, R. (2024). AI for targeted polypharmacology: The next frontier in drug discovery. Current Opinion in Structural Biology, 84, 102771. https://doi.org/10.1016/j.sbi.2023.102771
Dale, B., Cheng, M., Park, K.-S., Kaniskan, H. Ü., Xiong, Y., & Jin, J. (2021). Advancing targeted protein degradation for cancer therapy. Nature Reviews Cancer, 21, 638–654. https://doi.org/10.1038/s41568-021-00365-x
Devabattula, G., Panda, B., Yadav, R., & Godugu, C. (2023). The potential pharmacological effects of natural product Withaferin A in cancer: Opportunities and challenges for clinical translation. Planta Medica. https://doi.org/10.1055/a-2289-9600
Doostmohammadi, A., Jooya, H., Ghorbanian, K., Gohari, S., & Dadashpour, M. (2024). Potentials and future perspectives of multi-target drugs in cancer treatment: The next generation anti-cancer agents. Cell Communication and Signaling, 22. https://doi.org/10.1186/s12964-024-01607-9
Eladl, O. (2025). Molecular glues and PROTACs in targeted protein degradation: Mechanisms, advances, and therapeutic potential. Biochemical Pharmacology, 117297. https://doi.org/10.1016/j.bcp.2025.117297
Gao, W., Luo, S., & Coley, C. W. (2025). Generative AI for navigating synthesizable chemical space. Proceedings of the National Academy of Sciences, 122. https://doi.org/10.1073/pnas.2415665122
George, A., Sidgwick, F. R., Watt, J. E., Martin, M. P., Trost, M., Marín-Rubio, J. L., & Dueñas, M. E. (2023). Comparison of quantitative mass spectrometric methods for drug target identification by thermal proteome profiling. Journal of Proteome Research, 22, 2629–2640. https://doi.org/10.1021/acs.jproteome.3c00111
Hakim, S., Choudhary, N., Malhotra, K., Peng, J., Bültemeier, A., Arafa, A., Friedhoff, R., Bauer, M., Eikenberg, J., Witte, C., Herde, M., Heretsch, P., Pucker, B., & Franke, J. (2025). Phylogenomics and metabolic engineering reveal a conserved gene cluster in Solanaceae plants for withanolide biosynthesis. Nature Communications, 16. https://doi.org/10.1038/s41467-025-61686-1
Hsia, O., Hinterndorfer, M., Cowan, A. D., Iso, K., Ishida, T., Sundaramoorthy, R., Nakasone, M. A., Imrichová, H., Schätz, C., Rukavina, A., Husnjak, K., Wegner, M., Correa-Sáez, A., Craigon, C., Casement, R., Maniaci, C., Testa, A., Kaulich, M., Dikić, I., … Ciulli, A. (2023). Targeted protein degradation via intramolecular bivalent glues. Nature, 627, 204–211. https://doi.org/10.1038/s41586-024-07089-6
Kensert, A., Desmet, G., & Cabooter, D. (2024). A hands-on tutorial on quantitative structure-activity relationships using fully expressive graph neural networks. Analytica Chimica Acta, 1331, 343046. https://doi.org/10.1016/j.aca.2024.343046
Kim, G. Y., Grams, R. J., & Hsu, K.-L. (2025). Advancing covalent ligand and drug discovery beyond cysteine. Chemical Reviews, 125, 6653–6684. https://doi.org/10.1021/acs.chemrev.5c00001
Koudelka, T., Bassot, C., & Piazza, I. (2025). Benchmarking of quantitative proteomics workflows for limited proteolysis mass spectrometry. Molecular and Cellular Proteomics, 24. https://doi.org/10.1016/j.mcpro.2025.100945
Lerose, V., Ponticelli, M., Benedetto, N., Carlucci, V., Lela, L., Tzvetkov, N. T., & Milella, L. (2024). Withania somnifera (L.) Dunal, a potential source of phytochemicals for treating neurodegenerative diseases: A systematic review. Plants, 13(6), 771. https://doi.org/10.3390/plants13060771
Li, K., & Crews, C. M. (2022). PROTACs: Past, present and future. Chemical Society Reviews. https://doi.org/10.1039/d2cs00193d
Li, Y., et al. (2022). Peruranolides A–D: New withanolide-type steroids from Physalis peruviana. Natural Product Research.
Li, Y., et al. (2025). Biosynthetic ring contraction in withanolide-type steroidal lactones. Organic Letters.
Mayer, R. J., & Ofial, A. R. (2021). Nucleophilic reactivities of glutathione and related thiols toward Michael acceptors. Angewandte Chemie International Edition, 60, 2966–2970. https://doi.org/10.1002/anie.202012347
Misakyan, M., Wijeratne, E. M. K., Issa, M., Xu, Y., Monteillier, A., Gunatilaka, A. A. L., & Cuendet, M. (2021). Structure-activity relationships of withanolides as antiproliferative agents for multiple myeloma: Comparison of activity in 2D models and a 3D coculture model. Journal of Natural Products, 84(8), 2321–2335. https://doi.org/10.1021/acs.jnatprod.1c00446
Miyashita, Y., Moriya, T., Kato, T., Kawasaki, M., Yasuda, S., Adachi, N., Suzuki, K., Ogasawara, S., Saito, T., Senda, T., & Murata, T. (2024). Improved higher resolution cryo-EM structures reveal the binding modes of hERG channel inhibitors. Structure. https://doi.org/10.1016/j.str.2024.08.021
Modi, S., Tiwari, A., Ghule, C., Pawar, S., Saste, G., Jagtap, S., Singh, R., Deshmukh, A., Girme, A., & Hingorani, L. (2022). Pharmacokinetic study of withanosides and withanolides from Withania somnifera using ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Molecules, 27(5), 1476. https://doi.org/10.3390/molecules27051476
Mons, E., Kim, R. Q., & Mulder, M. P. C. (2023). Technologies for direct detection of covalent protein–drug adducts. Pharmaceuticals, 16. https://doi.org/10.3390/ph16040547
Narayanan, S., & Nagegowda, D. A. (2024). Biosynthesis, transport, and accumulation of withanolides in Withania somnifera. Plant Cell Reports. https://doi.org/10.1007/s00299-024-03165-3
Peters-Clarke, T. M., Liang, Y., Mertz, K., Lee, K.-J., Westphall, M. S., Hinkle, J. D., McAlister, G. C., Syka, J. E. P., Kelly, R. T., & Coon, J. J. (2024). Boosting the sensitivity of quantitative single-cell proteomics with infrared-tandem mass tags. Journal of Proteome Research. https://doi.org/10.1021/acs.jproteome.4c00076
Petri, L., Gabizon, R., Ferenczy, G. G., Péczka, N., Egyed, A., Ábrányi-Balogh, P., Takács, T., & Keserű, G. M. (2025). Size-dependent target engagement of covalent probes. Journal of Medicinal Chemistry, 68, 6616–6632. https://doi.org/10.1021/acs.jmedchem.5c00017
Raza, A., Miles, J. J., Sime, F. B., Ross, B. P., Roberts, J. A., Popat, A., Kumeria, T., & Falconer, J. R. (2021). PLGA encapsulated γ-cyclodextrin–meropenem inclusion complex formulation for oral delivery. International Journal of Pharmaceutics, 120280. https://doi.org/10.1016/j.ijpharm.2021.120280
Reimer, B., Awoonor-Williams, E., Golosov, A., & Hornak, V. (2025). CovCysPredictor: Predicting selective covalently modifiable cysteines using protein structure and interpretable machine learning. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.4c01281
Ryszkiewicz, P., Malinowska, B., & Schlicker, E. (2025). Polypharmacology: New drugs in 2023–2024. Pharmacological Reports, 77, 543–560. https://doi.org/10.1007/s43440-025-00715-8
Sarabia-Vallejo, Á., Caja, M. M., Olives, A. I., Martín, M. A., & Menéndez, J. C. (2023). Cyclodextrin inclusion complexes for improved drug bioavailability and activity: Synthetic and analytical aspects. Pharmaceutics, 15. https://doi.org/10.3390/pharmaceutics15092345
Silva, G. W. D. S. E., Marques, A., & Sampaio, A. (2025). Anticancer effects of withanolides: In silico prediction of pharmacological properties. Molecules, 30, 2457. https://doi.org/10.3390/molecules30112457
Singh, A., Raza, A., Amin, S., Damodaran, C., & Sharma, A. (2022). Recent advances in the chemistry and therapeutic evaluation of naturally occurring and synthetic withanolides. Molecules, 27(3), 886. https://doi.org/10.3390/molecules27030886
Smith, E., Vishwakarma, D., Sun, S., Moorhouse, A. D., Tuveson, D. A., & Moses, J. E. (2025). Click chemistry for natural product-inspired covalent drug discovery. Drug Discovery Today, 104500. https://doi.org/10.1016/j.drudis.2025.104500
Song, J. (2025). Applications of the cellular thermal shift assay to drug discovery in natural products: A review. International Journal of Molecular Sciences, 26. https://doi.org/10.3390/ijms26093940
Stefan, S. M., & Rafehi, M. (2023). Medicinal polypharmacology: Exploration and exploitation of the polypharmacolome in modern drug development. Drug Development Research, 85. https://doi.org/10.1002/ddr.22125
Sun, D., Gao, W., Hu, H., & Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharmaceutica Sinica B, 12, 3049–3062. https://doi.org/10.1016/j.apsb.2022.02.002
Taddeo, V. A., Núñez, M. J., Beltrán, M., Castillo, U., Menjívar, J., Jiménez, I., Alcamí, J., Bedoya, L. M., & Bazzocchi, I. L. (2021). Withanolide-type steroids from Physalis nicandroides inhibit HIV transcription. Journal of Natural Products, 84, 2717–2726. https://doi.org/10.1021/acs.jnatprod.1c00637
Tewari, D., Chander, V., Dhyani, S., Sahu, S., Gupta, P., Patni, P., Kalick, L. S., & Bishayee, A. (2022). Withania somnifera (L.) Dunal: Phytochemistry, structure-activity relationship, and anticancer potential. Phytomedicine, 98, 153949. https://doi.org/10.1016/j.phymed.2022.153949
Tu, Y., Tan, L., Tao, H., & Li, Y. (2023). CETSA and thermal proteome profiling strategies for target identification and drug discovery of natural products. Phytomedicine, 116, 154862. https://doi.org/10.1016/j.phymed.2023.154862
Valdés-Albuernes, J. L., Díaz-Pico, E., Alfaro, S., & Caballero, J. (2024). Modeling of noncovalent inhibitors of the papain-like protease (PLpro) from SARS-CoV-2 considering the protein flexibility by using molecular dynamics and cross-docking. Frontiers in Molecular Biosciences, 11. https://doi.org/10.3389/fmolb.2024.1374364
Wang, Y.-F., Zhang, W.-D., et al. (2025). Withanolide-type steroids from Physalis angulata. Phytochemistry.
Wijeratne, E. M. K., Xu, Y., Liu, M., Inácio, M. C., Brooks, A. D., Tewary, P., Sayers, T. J., & Gunatilaka, A. A. L. (2021). Ring A/B-modified 17β-hydroxywithanolide analogues as antiproliferative agents for prostate cancer and potentiators of immunotherapy for renal carcinoma and melanoma. Journal of Natural Products. https://doi.org/10.1021/acs.jnatprod.1c00724
Wu, Z., Wang, J., Du, H., Jiang, D., Kang, Y., Li, D., Pan, P., Deng, Y., Cao, D., Hsieh, C.-Y., & Hou, T. (2023). Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking. Nature Communications, 14. https://doi.org/10.1038/s41467-023-38192-3
Yan, X., Qu, C., Li, Q., Zhu, L., Tong, H., Liu, H., Qin, O., & Yao, X. (2024). Multiscale calculations reveal new insights into the reaction mechanism between KRASG12C and α,β-unsaturated carbonyl of covalent inhibitors. Computational and Structural Biotechnology Journal, 23, 1408–1417. https://doi.org/10.1016/j.csbj.2024.03.027
Zhang, Q., Yuan, Y., Cao, S., Kang, N., & Qiu, F. (2024). Withanolides: Promising candidates for cancer therapy. Phytotherapy Research, 38, 1104–1158. https://doi.org/10.1002/ptr.8090
Zhao, Z., & Bourne, P. E. (2024). Exploring extended warheads toward developing cysteine-targeted covalent kinase inhibitors. Journal of Chemical Information and Modeling, 64, 9517–9527. https://doi.org/10.1021/acs.jcim.4c00890
Zhu, D., Li, S., Chen, C., Wang, S., Zhu, J., Kong, L., & Luo, J. (2021). Tubocapsenolide A targets C-terminal cysteine residues of HSP90 to exert the anti-tumor effect. Pharmacological Research, 105523. https://doi.org/10.1016/j.phrs.2021.105523
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Maharaj Singh Educational Research Development Society

This work is licensed under a Creative Commons Attribution 4.0 International License.



