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Research and Reviews : Journal of Computational Biology Original Research

Computational Investigation of Withania somnifera Compounds Targeting S. pombe SMN YG-Dimer in Spinal Muscular Atrophy: Insights from Molecular Docking Analysis

  1. Gayatri Tummalapenta Btech. Biotechnology, SRM University, KTR branch,

Abstract

Objectives: The primary objective of this study is to determine the potential of phytochemical constituents of Withania somnifera in treating spinal muscular atrophy, an autosomal recessive genetic neurodegenerative disorder, through computational techniques. To investigate the binding affinity of phytocompound to the target protein S. pombe SMN YG-Dimer through molecular docking. Besides, evaluating the pharmacological attributes of phytochemical constituents to assess their ability as an ideal prospect for developing therapeutic medication. The target protein S. pombe SMN YG-Dimer of PDB ID: 4RG5 was extracted and downloaded from the Protein Data Bank (PDB) database. Later, the phytocompounds were extracted and downloaded from the IMPPAT database. The Swiss ADME webserver was used for evaluating the pharmacological properties and pharmacokinetics of phytocompounds. Finally, molecular docking was achieved by the PyRx webserver.

Results: Molecular docking analysis revealed that withasomnine emerged as the most favorable phytocompound among other selected phytocompounds. Withasomnine demonstrated a significant binding affinity of -7.9 towards the target protein, indicating the need for further investigation. Moreover, withasomnine exhibited favorable pharmacological properties and pharmacokinetic profiles, positioning it as a promising candidate for drug development.

Conclusion: The phytocompound withasomnine with the highest binding affinity to the target protein indicates a promising prospect for developing a therapeutic medication for treating spinal muscular atrophy

Keywords

References (54)

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  28. Hahnen E, Schönling J, Rudnik-Schöneborn S, Zerres K, Wirth B. Hybrid survival motor neuron genes in patients with autosomal recessive spinal muscular atrophy: new insights into molecular mechanisms responsible for the disease. Am J Hum Genet. 1996;59(5):1057.
  29. National Institute of Neurological Disorders and Stroke. (2024). Spinal muscular atrophy [Online]. National Institute of Neurological Disorders and Stroke. Available from: https://www.ninds. gov/health-information/disorders/spinal-muscular-atrophy.
  30. Armengol VD, Darras BT, Abulaban AA, Alshehri A, Barisic N, Ben-Omran T, et al. Life-Saving Treatments for Spinal Muscular Atrophy. Neurology Clinical Practice. 2024;14(1). doi:10.1212/cpj.0000000000200224
  31. Levchenko M, Gou Y, Graef F, Hamelers A, Huang Z, Ide-Smith M, et al. Europe PMC in 2017. Nucleic Acids Research. 2017;46(D1):D1254-D1260. doi:10.1093/nar/gkx1005
  32. Rudnik-Schöneborn S, Zerres K. Spinal muscular atrophies. Inte Neurol Clin 2009;208–211.
  33. Hodgkinson VL, Oskoui M, Lounsberry J, M’Dahoma S, Butler E, Campbell C, et al. A National Spinal Muscular Atrophy Registry for Real-World Evidence. Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques. 2020;47(6):810-815. doi:10.1017/cjn.2020.111
  34. Park HB, Lee SM, Lee JS, Park MS, Park KI, Namgung R, Lee C. Survival analysis of spinal muscular atrophy type I. Korean J Pediatr. 2010;53(11):965. doi:3345/kjp.2010.53.11.965.
  35. Rubinstein WS, Maglott DR, Lee JM, Kattman BL, Malheiro AJ, Ovetsky M, et al. The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency. Nucleic Acids Research. 2012;41(D1):D925-D935. doi:10.1093/nar/gks1173
  36. D'Amico A, Mercuri E, Tiziano FD, Bertini E. Spinal muscular atrophy. Orphanet J Rare Dis. 2011;6:71. doi:1186/1750-1172-6-7.
  37. Keinath MC, Prior DE, Prior TW. Spinal Muscular Atrophy: Mutations, Testing, and Clinical Relevance. The Application of Clinical Genetics. 2021;Volume14:11-25. doi:10.2147/tacg.s239603
  38. Ogbonmide T, Rathore R, Rangrej SB, Hutchinson S, Lewis M, Ojilere S, Carvalho V, Kelly I. Gene therapy for spinal muscular atrophy (SMA): A review of current challenges and safety considerations for onasemnogene abeparvovec (Zolgensma). Cureus. 2023;15(3):e36197. doi:7759/cureus.36197.
  39. Porensky PN, Burghes AHM. Antisense Oligonucleotides for the Treatment of Spinal Muscular Atrophy. Human Gene Therapy. 2013;24(5):489-498. doi:10.1089/hum.2012.225
  40. Kakazu J, Walker NL, Babin KC, Trettin KA, Lee C, Sutker PB, et al. Risdiplam for the Use of Spinal Muscular Atrophy. Orthopedic Reviews. 2021;13(2). doi:10.52965/001c.25579
  41. Saleem S, Muhammad G, Hussain MA, Altaf M, Bukhari SNA. Withania somnifera L.: Insights into the phytochemical profile, therapeutic potential, clinical trials, and future prospective. Iran J Basic Med Sci 2020;23(12):1501–15 doi:10.22038/IJBMS.2020.44254.10378.
  42. Singh N, Bhalla M, De Jager P, Gilca M. An Overview on Ashwagandha: A Rasayana (Rejuvenator) of Ayurveda. African Journal of Traditional, Complementary and Alternative Medicines. 2011;8(5S). doi:10.4314/ajtcam.v8i5s.9
  43. Mikulska P, Malinowska M, Ignacyk M, Szustowski P, Nowak J, Pesta K, et al. Ashwagandha (Withania somnifera)—current research on the health-promoting activities: A narrative review. Pharmaceutics. 2023;15(4):1057. doi:3390/pharmaceutics15041057.
  44. Syed AA, Reza MI, Singh P, Thombre GK, Gayen JR. Withania somnifera in neurological disorders: ethnopharmacological evidence, mechanism of action and its progress in delivery s Curr Drug Metab. 2021;22(7):561–571.
  45. Singh M, Ramassamy C. In vitroscreening of neuroprotective activity of Indian medicinal plantWithania somnifera. Journal of Nutritional Science. 2017;6. doi:10.1017/jns.2017.48
  46. Shah Z, Raghavan A. Withania somnifera: a pre-clinical study on neuroregenerative therapy for stroke. Neural Regen Res. 2015;10(2):183. doi:4103/1673-5374.152362.
  47. Gupta M, Kaur G. Withania somnifera (L.) Dunal ameliorates neurodegeneration and cognitive impairments associated with systemic inflammation. BMC Complement Altern Med. 2019;19(1). doi:1186/s12906-019-2635-0.
  48. Laskowski RA, Jabłońska J, Pravda L, Vařeková RS, Thornton JM. PDBsum: Structural summaries of PDB entries. Protein Science. 2017;27(1):129-134. doi:10.1002/pro.3289
  49. Mohanraj K, Karthikeyan BS, Vivek-Ananth RP, Chand RPB, Aparna SR, Mangalapandi P, et al. IMPPAT: A curated database of Indian Medicinal Plants, Phytochemistry And Therapeutics. Scientific Reports. 2018;8(1). doi:10.1038/s41598-018-22631-z
  50. 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). doi:1038/srep42717.
  51. Benet LZ, Hosey CM, Ursu O, Oprea TI. BDDCS, the rule of 5 and drugability. Adv Drug Deliv Rev. 2016;101:89–98. doi:1016/j.addr.2016.05.007.
  52. Dayangaç-Erden D, Bora G, Ayhan P, Kocaefe Ç, Dalkara S, Yelekçi K, et al. Histone deacetylase inhibition activity and molecular docking of (E)‐resveratrol: Its therapeutic potential in spinal muscular atrophy. Chem Biol Drug Des. 2009;73(3):355–3
  53. Konar A, Gupta R, Shukla RK, Maloney B, Khanna VK, Wadhwa R, et al. M1 muscarinic receptor is a key target of neuroprotection, neuroregeneration, and memory recovery by i-Extract from Withania somnifera. Sci 2019;9(1):1–15.
  54. Meng X-Y, Zhang H-X, Mezei M, Cui M. Molecular docking: A powerful approach for structure-based drug discovery. Curr Comput Aided Drug Des. 2011;7(2):146–157. doi:2174/157340911795677602.
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