Natural products in neuroprotective therapies: Experimental and cheminformatics approaches to manage neurological disorders

Md. Mominur Rahman, Md. Abid Hossain, Kajima Rifat, Saila Kabir Maeesa, A. M. Abu Sayem Rahman, Mahamuda Akter Mim, Nasrin Sultana, Dipongkar Ray Sobuj, Israt Jahan Tamanna, Md. Rezaul Islam, Sharifa Sultana, Arifa Sultana, Rohit Sharma, Rajeev K. Singla

Article ID: 2140
Vol 7, Issue 1, 2024

VIEWS - 1272 (Abstract) 306 (PDF)

Abstract


Neurological disorders (NDs) such as Alzheimer’s disease (AD), Parkinson’s disease (PD), epilepsy, despondency, and dementia have been evidenced as a rising concern among diverse geographical regions. Brain-related diseases are currently the main concern because they increase mortality and morbidity in the elderly. Regardless of the continual efforts by modern scientists to develop a promising pharmacological or surgical management, the outcome has not been satisfactory. Also, due to synthetic drugs’ associated side effects, scientists have taken the initiative to consider using natural compounds as an alternative. Hence, they obtain pretty effective results by using natural compounds. Natural ingredients are synthesized from a variety of plant and animal sources. These natural ingredients cure brain diseases through a variety of mechanisms. For effective medication advancement, the molecules must go through preliminary clinical systems that require some investment and significant speculation. In this situation, cheminformatics is fundamental in diminishing time and venture. Cheminformatics methods play a significant role in these issues, including 3-dimensional quantitative structure-activity relationship 3D-(QSAR), virtual screening, docking, molecular dynamic studies, and quantum chemical studies. The vital purpose of this study is to disclose different types of NDs and the neuroprotective effect of several natural products for experimental and cheminformatics-based therapy. Natural products like green tea, flavonoids, and ginseng are discussed as effective neuroprotective products. However, more investigation is expected to comprehend the better utilization of regular items in future exploratory and cheminformatics-based treatment for NDs.


Keywords


neurological disorders; docking; molecular dynamic studies; cheminformatics; mortality; drug discovery

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References


1. Aizaz M, Lubna, Ahmad W, et al. Exploring the potential of halotolerant bacteria from coastal regions to mitigate salinity stress in wheat: physiological, molecular, and biochemical insights. Frontiers in Plant Science 2023. doi: 10.3389/fpls.2023.1224731.

2. Gerique A. An introduction to ethnoecology and ethnobotany. Theory and Methods—Integrative assessment and planning methods for sustainable agroforestry in humid and semiarid regions. Available online: https://www.researchgate.net/publication/239591352_An_Introduction_to_ethnoecology_and_ethnobotany_Theory_and_Methods_-_Integrative_assessment_and_planning_methods_for_sustainable_agroforestry_in_humid_and_semiarid_regions. (accessed on 10 March 2023).

3. Karthika C, Hari B, Mano V, et al. Curcumin as a great contributor for the treatment and mitigation of colorectal cancer. Experimental Gerontology 2021; 152: 111438. doi: 10.1016/j.exger.2021.111438.

4. Kabir T, Tabassum N, Uddin S, et al. Therapeutic potential of polyphenols in the management of diabetic neuropathy. Evidence-Based Complementary and Alternative Medicine 2021; 2021: 9940169. doi: 10.1155/2021/9940169

5. Avram S, Mernea M, Mihailescu D, Duda-Seiman D. Advanced QSAR methods evaluated polycyclic aromatic compounds duality as drugs and inductors in psychiatric disorders. Current Organic Chemistry 2013; 17(23): 2880–2890. doi: 10.2174/13852728113179990132

6. Avram S, Milac AL, Mihailescu D. 3D-QSAR study indicates an enhancing effect of membrane ions on psychiatric drugs targeting serotonin receptor 5-HT1A. Molecular BioSystems 2012; 8(5): 1418. doi: 10.1039/c2mb00005a

7. Walia V, Kaushik D, Mittal V, et al. Delineation of neuroprotective effects and possible benefits of antioxidantstherapy for the treatment of Alzheimer’s Diseases by targeting mitochondrial-derived reactive oxygen species: Bench to bedside. Molecular Neurobiology 2021; 59(1): 657–680. doi: 10.1007/s12035-021-02617-1

8. Ouabbou S, He Y, Butler K, et al. Inflammation in mental disorders: Is the microbiota the missing link? Neuroscience Bulletin 2020; 36(9): 1071–1084. doi: 10.1007/s12264-020-00535-1

9. Gober R, Ardalan M, Shiadeh SMJ, et al. Microglia activation in postmortem brains with schizophrenia demonstrates distinct morphological changes between brain regions. Brain Pathology 2021; 32(1): 13003. doi: 10.1111/bpa.13003

10. Hurşitoğlu O, Orhan FÖ, Kurutaş EB, et al. Diagnostic performance of increased malondialdehyde level and oxidative stress in patients with schizophrenia. Arch Neuropsychiatry Turkish Neuropsychiatric Society 2021; 58(3): 184. doi: 10.29399/npa.27372

11. Brown AS, Derkits EJ. Prenatal infection and schizophrenia: A review of epidemiologic and translational studies. American Journal of Psychiatry 2010; 167(3): 261–280. doi: 10.1176/appi.ajp.2009.09030361

12. Rahman MH, Akter R, Bhattacharya T, et al. Resveratrol and neuroprotection: Impact and its therapeutic potential in Alzheimer’s Disease. Frontiers in Pharmacology 2020; 11: 619024. doi: 10.3389/fphar.2020.619024

13. Ghose AK, Herbertz T, Hudkins RL, et al. Knowledge-based, Central Nervous System (CNS) lead selection and lead optimization for CNS drug discovery. ACS Chemical Neuroscience 2011; 3(1): 50–68. doi: 10.1021/cn200100h

14. Sharma VK, Singh TG, Garg N, et al. Dysbiosis and Alzheimer’S Disease: A role for chronic stress? Biomolecules 2021; 11(5): 678. doi: 10.3390/biom11050678

15. Hsu CW, Lee Y, Lee CY, Lin PY. Neurotoxicity and nephrotoxicity caused by combined use of lithium and risperidone: A case report and literature review. BMC Pharmacology and Toxicology 2016; 17(1): 59. doi: 10.1186/s40360-016-0101-x

16. Nikolic K, Mavridis L, Djikic T, et al. Drug design for CNS diseases: Polypharmacological profiling of compounds using cheminformatic, 3D-QSAR and virtual screening methodologies. Frontiers in Neuroscience 2016; 10: 265. doi: 10.3389/fnins.2016.00265

17. Crane EA, Gademann K. Capturing biological activity in natural product fragments by chemical synthesis. Angewandte Chemie International Edition 2016; 55(12): 3882–3902. doi: 10.1002/anie.201505863

18. Bhattacharya T, Dey PS, Akter R, et al. Effect of natural leaf extracts as phytomedicine in curing geriatrics. Experimental Gerontology 2021; 150: 111352. doi: 10.1016/j.exger.2021.111352

19. Akter R, Chowdhury MAR, Rahman MH. Flavonoids and polyphenolic compounds as potential talented agents for the treatment of alzheimer’s disease with their antioxidant activities. Current Pharmaceutical Design 2021; 27(3): 345–356. doi: 10.2174/1381612826666201102102810

20. Tagde P, Tagde S, Tagde P, et al. Nutraceuticals and herbs in reducing the risk and improving the treatment of covid-19 by targeting sars-cov-2. Biomedicines 2021; 9(9): 1266. doi: 10.3390/biomedicines9091266

21. Kabir MT, Rahman MH, Akter R, et al. Potential role of curcumin and its nanoformulations to treat various types of cancers. Biomolecules 2021; 11(3): 392. doi: 10.3390/biom11030392

22. Xu J, Hagler A. Chemoinformatics and drug discovery. Molecules 2002; 7(8): 566–600. doi: 10.3390/70800566

23. Ferreira LL, Andricopulo AD. From chemoinformatics to deep learning: An open road to drug discovery. Future Medicinal Chemistry 2019; 11(5): 371–374. doi: 10.4155/fmc-2018-0449

24. Damale M, Harke S, Kalam Khan F, et al. Recent Advances in multidimensional QSAR (4D-6D): A critical review. Mini-Reviews in Medicinal Chemistry 2014; 14(1): 35–55. doi: 10.2174/13895575113136660104

25. Avram S, Mernea M, Bagci E, et al. Advanced structure-activity relationships applied to Mentha spicata L. subsp. spicata essential oil compounds as AChE and NMDA ligands, in comparison with Donepezil, Galantamine and Memantine—New approach in brain disorders pharmacology. CNS & Neurological Disorders—Drug Targets 2017; 16(7): 800–811. doi: 10.2174/1871527316666170113115004

26. Shinde RS, Deshmukh A, Navale VA. Cheminformatics tools useful for research scholar, research supervisor, research and developments. International Journal of Research and Analytical Reviews 2018; 5(4): 153–156.

27. Avram S, Mernea M, Limban C, et al. Potential therapeutic approaches to Alzheimer’s disease by bioinformatics, cheminformatics and predicted adme-tox tools. Current Neuropharmacology 2020; 18(8): 696–719. doi: 10.2174/1570159x18666191230120053

28. Peter SC, Dhanjal JK, Malik V, et al. Quantitative structure-activity relationship (QSAR): Modeling approaches to biological applications. In: Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics. Elsevier; 2018; pp. 661–676.

29. Andrade CH, Pasqualoto KFM, Ferreira EI, et al. 4D-QSAR: Perspectives in drug design. Molecules 2010; 15(5): 3281–3294. doi: 10.3390/molecules15053281

30. Avram S, Milac AL, Carta F, et al. More effective dithiocarbamate derivatives inhibiting carbonic anhydrases, generated by QSAR and computational design. Journal of Enzyme Inhibition and Medicinal Chemistry 2012; 28(2): 350–359. doi: 10.3109/14756366.2012.727410

31. Cherkasov A, Muratov EN, Fourches D, et al. QSAR modeling: Where have you been? Where are you going to? Journal of Medicinal Chemistry 2014; 57(12): 4977–5010. doi: 10.1021/jm4004285

32. Cramer RD. The inevitable QSAR renaissance. Journal of Computer-Aided Molecular Design 2011; 26(1): 35–38. doi: 10.1007/s10822-011-9495-0

33. Shoichet BK. Virtual screening of chemical libraries. Nature 2004; 432: 862–865. doi: 10.1038/nature03197

34. Lavecchia A, Giovanni C. Virtual screening strategies in drug discovery: A critical review. Current Medicinal Chemistry 2013; 20(23): 2839–2860. doi: 10.2174/09298673113209990001

35. Lenselink EB, Dijke N Ten, Bongers B, et al. Beyond the hype: Deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set. Journal of Cheminformatics. 2017; 9(1): 45. doi: 10.1186/s13321-017-0232-0

36. Yadav R, Selvaraj C, Aarthy M, et al. Investigating into the molecular interactions of flavonoids targeting NS2B-NS3 protease from ZIKA virus through in-silico approaches. Journal of Biomolecular Structure and Dynamics 2020; 39(1): 272–284. doi: 10.1080/07391102.2019.1709546

37. Deng C, Yan H, Wang J, et al. Current scenario on non-nucleoside reverse transcriptase inhibitors (2018-present). Arabian Journal of Chemistry 2022; 15(12): 104378. doi: 10.1016/j.arabjc.2022.104378

38. Nanor E, Agbesi VK, Wu WP, et al. Featurization of drug compounds and target proteins for drug-target interaction prediction. International Journal of Scientific and Research Publications 2020; 10(2): 9813. doi: 10.29322/ijsrp.10.02.2020.p9813

39. Firdaus Begam B, Satheesh Kumar J. A study on cheminformatics and its applications on modern drug discovery. Procedia Engineering 2012; 38: 1264–1275. doi: 10.1016/j.proeng.2012.06.156

40. Dobson CM. Chemical space and biology. Nature 2004; 432(7019): 824–828. doi: 10.1038/nature03192

41. Rahman SA, Bashton M, Holliday GL, et al. Small Molecule Subgraph Detector (SMSD) toolkit. Journal of Cheminformatics 2009; 1(1): 12. doi: 10.1186/1758-2946-1-12

42. Lakshmi V, Kannan VS, Boopathy R. Identification of potential bivalent inhibitors from natural compounds for acetylcholinesterase through in silico screening using multiple pharmacophores. Journal of Molecular Graphics and Modelling 2013; 40: 72–79. doi: 10.1016/j.jmgm.2012.12.008

43. Dixon SL, Smondyrev AM, Rao SN. Phase: A novel approach to pharmacophore modeling and 3D database searching. Chemical Biology & Drug Design 2006; 67(5): 370–372. doi: 10.1111/j.1747-0285.2006.00384.x

44. Leemans E, Mahasenan KV, Kumarasiri M, et al. Three-dimensional QSAR analysis and design of new 1,2,4-oxadiazole antibacterials. Bioorganic & Medicinal Chemistry Letters 2016; 26(3): 1011–1015. doi: 10.1016/j.bmcl.2015.12.041

45. Li YP, Weng X, Ning FX, et al. 3D-QSAR studies of azaoxoisoaporphine, oxoaporphine, and oxoisoaporphine derivatives as anti-AChE and anti-AD agents by the CoMFA method. Journal of Molecular Graphics and Modelling 2013; 41: 61–67. doi: 10.1016/j.jmgm.2013.02.003

46. Wold S, Ruhe A, Wold H, et al. The collinearity problem in linear regression. The Partial Least Squares (PLS) approach to generalized inverses. SIAM Journal on Scientific and Statistical Computing 1984; 5(3): 735–743. doi: 10.1137/0905052

47. Gonzalez-Diaz H, Prado-Prado F, Ubeira F. Predicting antimicrobial drugs and targets with the MARCH-INSIDE approach. Current Topics in Medicinal Chemistry 2008; 8(18): 1676–1690. doi: 10.2174/156802608786786543

48. Prado-Prado F, Garcia-Mera X, Escobar M, et al. 3D MI-DRAGON: New model for the reconstruction of US FDA drug- target network and theoretical-experimental studies of inhibitors of rasagiline derivatives for AChE. Current Topics in Medicinal Chemistry 2012; 12(16): 1843–1865. doi: 10.2174/1568026611209061843

49. Zanni R, Garcia-Domenech R, Galvez-Llompart M, et al. Alzheimer: A decade of drug design. Why molecular topology can be an extra edge? Current Neuropharmacology 2018; 16(6): 849–864. doi: 10.2174/1570159x15666171129102042

50. Nikolic K, Agbaba D, Stark H. Pharmacophore modeling, drug design and virtual screening on multi-targeting procognitive agents approaching histaminergic pathways. Journal of the Taiwan Institute of Chemical Engineers 2015; 46: 15–29. doi: 10.1016/j.jtice.2014.09.017

51. Durán Á, Zamora I, Pastor M. Suitability of GRIND-based principal properties for the description of molecular similarity and ligand-based virtual screening. Journal of Chemical Information and Modeling 2009; 49(9): 2129–2138. doi: 10.1021/ci900228x

52. Bautista-Aguilera OM, Esteban G, Bolea I, et al. Design, synthesis, pharmacological evaluation, QSAR analysis, molecular modeling and ADMET of novel donepezil-indolyl hybrids as multipotent cholinesterase/monoamine oxidase inhibitors for the potential treatment of Alzheimer’s disease. European Journal of Medicinal Chemistry 2014; 75: 82–95. doi: 10.1016/j.ejmech.2013.12.028

53. Daidone F, Montioli R, Paiardini A, et al. Identification by virtual screening and in vitro testing of human DOPA decarboxylase inhibitors. PLoS One 2012; 7(2): e31610. doi: 10.1371/journal.pone.0031610

54. Ul-Haq Z, Wilson AK. Frontiers in Computational Chemistry: Volume 6. Bentham Science Publishers; 2022.

55. Geldenhuys WJ, Kuzenko SR, Simmons MA. Virtual screening to identify novel antagonists for the G protein-coupled NK3 receptor. Journal of Medicinal Chemistry 2010; 53(22): 8080–8088. doi: 10.1021/jm1010012

56. Lešnik S, Štular T, Brus B, et al. LiSiCA: a software for ligand-based virtual screening and its application for the discovery of butyrylcholinesterase inhibitors. Journal of Chemical Information and Modeling 2015; 55(8): 1521–1528. doi: 10.1021/acs.jcim.5b00136

57. Dai W, Guo D. A ligand-based virtual screening method using direct quantification of generalization ability. Molecules 2019; 24(13): 2414. doi: 10.3390/molecules24132414

58. Sirci F, Istyastono EP, Vischer HF, et al. Virtual fragment screening: Discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints. Journal of Chemical Information and Modeling 2012; 52(12): 3308–3324. doi: 10.1021/ci3004094

59. Gibbons GS, Chakraborty A, Grigsby SM, et al. Identification of DOT1L inhibitors by structure-based virtual screening adapted from a nucleoside-focused library. European Journal of Medicinal Chemistry 2020; 189: 112023. doi: 10.1016/j.ejmech.2019.112023

60. Dobi K, Flachner B, Pukáncsik M, et al. Combination of pharmacophore matching, 2D similarity search, and in vitro biological assays in the selection of potential 5-HT6 antagonists from large commercial repositories. Chemical Biology & Drug Design 2015; 86(4): 864–880. doi: 10.1111/cbdd.12563

61. Scotti L, Mendonca Junior FJB, Ishiki HM, et al. Docking studies for multi-target drugs. Current Drug Targets 2017; 18(5): 592–604.

62. Lengauer T, Rarey M. Computational methods for biomolecular docking. Current Opinion in Structural Biology 1996; 6(3): 402–406. doi: 10.1016/s0959-440x(96)80061-3

63. Kitchen DB, Decornez H, Furr JR, et al. Docking and scoring in virtual screening for drug discovery: Methods and applications. Nature Reviews Drug Discovery 2004; 3(11): 935–949. doi: 10.1038/nrd1549

64. Kong B, Wang E, Li Z, et al. Study on the feature of electromagnetic radiation under coal oxidation and temperature rise based on multifractal theory. Fractals 2019; 27(3): 1950038. doi: 10.1142/s0218348x19500385

65. Kitchen DB, Decornez H, Furr JR, et al. Docking and scoring in virtual screening for drug discovery: Methods and applications. Nature Reviews Drug Discovery 2004; 3(11): 935–949. doi: 10.1038/nrd1549

66. Roy S, Kumar A, Baig MH, et al. Virtual screening, ADMET profiling, molecular docking and dynamics approaches to search for potent selective natural molecules based inhibitors against metallothionein-III to study Alzheimer’s disease. Methods 2015; 83: 105–110. doi: 10.1016/j.ymeth.2015.04.021

67. Bautista-Aguilera OM, Samadi A, Chioua M, et al. N-methyl-N-((1-methyl-5-(3-(1-(2-methylbenzyl)piperidin-4-yl)propoxy)-1H-indol-2-yl)methyl)prop-2-yn-1-amine, a new cholinesterase and monoamine oxidase dual inhibitor. Journal of Medicinal Chemistry 2014; 57(24): 10455–10463. doi: 10.1021/jm501501a

68. Yelekçi K, Büyüktürk B, Kayrak N. In silico identification of novel and selective monoamine oxidase B inhibitors. Journal of Neural Transmission 2013; 120(6): 853–858. doi: 10.1007/s00702-012-0954-0

69. Evranos-Aksöz B, Baysal İ, Yabanoğlu-Çiftçi S, et al. Synthesis and screening of human monoamine oxidase—A inhibitor effect of new 2-pyrazoline and hydrazone derivatives. Archiv der Pharmazie 2015; 348(10): 743–756. doi: 10.1002/ardp.201500212

70. Park H, Eom JW, Kim YH. Consensus scoring approach to identify the inhibitors of AMP-activated protein kinase α2 with virtual screening. Journal of Chemical Information and Modeling 2014; 54(7): 2139–2146. doi: 10.1021/ci500214e

71. Goldman BB, Wipke WT. QSD quadratic shape descriptors. 2. Molecular docking using quadratic shape descriptors (QSDock). Proteins: Structure, Function, and Genetics 2000; 38(1): 79–94. doi: 10.1002/(sici)1097-0134(20000101)38: 1<79: : aid-prot9>3.0.co, 2-u

72. Meng EC, Shoichet BK, Kuntz ID. Automated docking with grid‐based energy evaluation. Journal of Computational Chemistry 1992; 13(4): 505–524. doi: 10.1002/jcc.540130412

73. Morris GM, Goodsell DS, Halliday RS, et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry 2014; 19(14): 1639–1662. doi: 10.1002/(sici)1096-987x(19981115)19: 14<1639: : aid-jcc10>3.0.co, 2-b

74. Feig M, Onufriev A, Lee MS, et al. Performance comparison of generalized born and poisson methods in the calculation of electrostatic solvation energies for protein structures. Journal of Computational Chemistry 2004; 25(2): 265–284. doi: 10.1002/jcc.10378

75. Katsnelson A, De Strooper B, Zoghbi HY. Neurodegeneration: From cellular concepts to clinical applications. Science Translational Medicine 2016; 8(364): 364ps18. doi: 10.1126/scitranslmed.aal2074

76. Ekor M. The growing use of herbal medicines: Issues relating to adverse reactions and challenges in monitoring safety. Frontiers in Neurology 2014; 4: 177. doi: 10.3389/fphar.2013.00177

77. Bandaranayake WM. Quality Control, screening, toxicity, and regulation of herbal drugs. In: Modern Phytomedicine: Turning Medicinal Plants into Drugs. Wiley-VCH Verlag; 2006; pp. 25–57.

78. Di Paolo M, Papi L, Gori F, et al. Natural products in neurodegenerative diseases: A great promise but an ethical challenge. International Journal of Molecular Sciences 2019; 20(20): 5170. doi: 10.3390/ijms20205170

79. Rahman MH, Bajgai J, Fadriquela A, et al. Redox effects of molecular hydrogen and its therapeutic efficacy in the treatment of neurodegenerative diseases. Processes 2021; 9(2): 308. doi: 10.3390/pr9020308

80. Rahman MH, Akter R, Kamal MA. Prospective function of different antioxidant containing natural products in the treatment of neurodegenerative disease. CNS & Neurological Disorders—Drug Targets 2021; 20(8): 694–703. doi: 10.2174/1871527319666200722153611

81. Parvez MK. Natural or plant products for the treatment of neurological disorders: Current knowledge. Current Drug Metabolism 2018; 19(5): 424–428. doi: 10.2174/1389200218666170710190249

82. Dadhania VP, Trivedi PP, Vikram A, Tripathi DN. Nutraceuticals against neurodegeneration: A mechanistic insight. Current Neuropharmacology 2016; 14(6): 627–640. doi: 10.2174/1570159X14666160104142223

83. Rasool M, Malik A, Qureshi MS, et al. Recent updates in the treatment of neurodegenerative disorders using natural compounds. Evidence-Based Complementary and Alternative Medicine 2014; 2014: 1–7. doi: 10.1155/2014/979730

84. Leonoudakis D, Rane A, Angeli S, et al. Anti-inflammatory and neuroprotective role of natural product securinine in activated glial cells: implications for Parkinson’s disease. Mediators of Inflammation 2017; 2017: 1–11. doi: 10.1155/2017/8302636

85. Paolo MD, Papi L, Gori F, et al. Natural Products in Neurodegenerative Diseases: A Great Promise but an Ethical Challenge. International Journal of Molecular Sciences 2019; 20(20): 5170. doi: 10.3390/ijms20205170

86. Starkov AA, Beal FM. Portal to Alzheimer’s disease. Nature Medicine 2008; 14(10): 1020–1021. doi: 10.1038/nm1008-1020

87. Venkatesan R, Ji E, Kim SY. Phytochemicals that regulate neurodegenerative disease by targeting neurotrophins: A comprehensive review. BioMed Research International 2015; 2015: 1–22. doi: 10.1155/2015/814068

88. Singh A, Deshpande P, Gogia N. Exploring the efficacy of natural products in alleviating Alzheimer’s disease. Neural Regeneration Research 2019; 14(8): 1321. doi: 10.4103/1673-5374.253509

89. Wollen KA. Alzheimer’s disease: The pros and cons of pharmaceutical, nutritional, botanical, and stimulatory therapies, with a discussion of treatment strategies from the perspective of patients and practitioners. Alternative Medicine Review 2010; 15(3): 223–244.

90. Chahal R, Nanda A, Akkol EK, et al. Ageratum conyzoides L. And its secondary metabolites in the management of different fungal pathogens. Molecules 2021; 26(10): 2933. doi: 10.3390/molecules26102933

91. Rahman MA, Rahman MH, Hossain MS, et al. Molecular insights into the multifunctional role of natural compounds: Autophagy modulation and cancer prevention. Biomedicines 2020; 8(11): 517. doi: 10.3390/biomedicines8110517

92. Deshpande P, Gogia N, Singh A. Exploring the efficacy of natural products in alleviating Alzheimer’s disease. Neural Regeneration Research 2019; 14(8): 1321–1329. doi: 10.4103/1673-5374.253509

93. Sarkar A, Gogia N, Glenn N, et al. A soy protein Lunasin can ameliorate amyloid-beta 42 mediated neurodegeneration in Drosophila eye. Scientific Reports 2018; 8(1): 13545. doi: 10.1038/s41598-018-31787-7

94. Hoppe J, Coradini K, Frozza R, et al. Free and nanoencapsulated curcumin suppress β-amyloid-induced cognitive impairments in rats: Involvement of BDNF and Akt/GSK-3β signaling pathway. Neurobiology of Learning and Memory 2013; 106: 134–144. doi: 10.1016/j.nlm.2013.08.001

95. Doggui S, Belkacemi A, Paka GD, et al. Curcumin protects neuronal-like cells against acrolein by restoring Akt and redox signaling pathways. Molecular Nutrition & Food Research 2013; 57(9): 1660–1670. doi: 10.1002/mnfr.201300130

96. Auti ST, Kulkarni YA. A systematic review on the role of natural products in modulating the pathways in alzheimer’s disease. International Journal for Vitamin and Nutrition Research 2017; 87(1–2): 99–116. doi: 10.1024/0300-9831/a000405

97. Zangara A. The psychopharmacology of huperzine A: An alkaloid with cognitive enhancing and neuroprotective properties of interest in the treatment of Alzheimer’s disease. Pharmacology Biochemistry and Behavior 2003; 75(3): 675–686. doi: 10.1016/s0091-3057(03)00111-4

98. Kim JI, Jeon SG, Kim KA, et al. Platycodon grandiflorus root extract improves learning and memory by enhancing synaptogenesis in mice hippocampus. Nutrients 2017; 9(7): 794. doi: 10.3390/nu9070794

99. Uddin MS, Kabir MT, Rahman MH, et al. Exploring the multifunctional neuroprotective promise of rasagiline derivatives for multi-dysfunctional Alzheimer’s disease. Current Pharmaceutical Design 2020; 26(37): 4690–4698. doi: 10.2174/1381612826666200406075044

100. Bagli E, Goussia A, Moschos MM, et al. Natural compounds and neuroprotection: Mechanisms of action and novel delivery systems. In Vivo 2016; 30(5): 535–547.

101. Zhao J, Li K, Wang Y, et al. Enhanced anti-amnestic effect of donepezil by Ginkgo biloba extract (EGb 761) via further improvement in pro-cholinergic and antioxidative activities. Journal of Ethnopharmacology 2021; 269: 113711. doi: 10.1016/j.jep.2020.113711

102. Devinsky O, Marsh E, Friedman D, et al. Cannabidiol in patients with treatment-resistant epilepsy: An open-label interventional trial. The Lancet Neurology 2016; 15(3): 270–278. doi: 10.1016/s1474-4422(15)00379-8

103. Russo EB. The case for the entourage effect and conventional breeding of clinical cannabis: No “Strain,” no gain. Frontiers in Plant Science 2019; 9: 1969. doi: 10.3389/fpls.2018.01969

104. Brouwer MC, Thwaites GE, Tunkel AR, et al. Dilemmas in the diagnosis of acute community-acquired bacterial meningitis. The Lancet 2012; 380(9854): 1684–1692. doi: 10.1016/s0140-6736(12)61185-4

105. Kim SR, Shin YS, Kim JH, et al. Differences in type composition of symptom clusters as predictors of quality of life in patients with meningioma and glioma. World Neurosurgery 2017; 98: 50–59. doi: 10.1016/j.wneu.2016.10.085

106. Koushki M, Amiri‐Dashatan N, Ahmadi N, et al. Resveratrol: A miraculous natural compound for diseases treatment. Food Science & Nutrition 2018; 6(8): 2473–2490. doi: 10.1002/fsn3.855

107. Gatson JW, Liu MM, Abdelfattah K, et al. Resveratrol decreases inflammation in the brain of mice with mild traumatic brain injury. Journal of Trauma and Acute Care Surgery 2013; 74(2): 470–475. doi: 10.1097/ta.0b013e31827e1f51

108. Maté J, Periago PM, Palop A. When nanoemulsified, d-limonene reduces Listeria monocytogenes heat resistance about one hundred times. Food Control 2016; 59: 824–828. doi: 10.1016/j.foodcont.2015.07.020

109. Ars M, Jras P. A new scenario of bioprospecting of Hymenoptera venoms through proteomic approach. The Journal of Venomous Animals and Toxins including Tropical Diseases 2011; 17(4): 364–377. doi: 10.1590/s1678-91992011000400003

110. Kim HJ, Jeon BS. Is acupuncture efficacious therapy in Parkinson’s disease? Journal of the Neurological Sciences 2014; 341(1–2): 1–7. doi: 10.1016/j.jns.2014.04.016

111. Yang EJ, Jiang JH, Lee SM, et al. Bee venom attenuates neuroinflammatory events and extends survival in amyotrophic lateral sclerosis models. Journal of Neuroinflammation 2010; 7(1): 69. doi: 10.1186/1742-2094-7-69

112. Castro HJ, Mendez-Inocencio JI, Omidvar B. A phase I study of the safety of honeybee venom extract as a possible treatment for patients with progressive forms of multiple sclerosis. 2005; 26(6): 470–476.

113. Jung SY, Lee KW, Choi SM, et al. Bee venom protects against rotenone-induced cell death in NSC34 motor neuron cells. Toxins 2015; 7(9): 3715–3726. doi: 10.3390/toxins7093715

114. Zivkovic AR, Sedlaczek O, von Haken R, et al. Muscarinic M1 receptors modulate endotoxemia-induced loss of synaptic plasticity. Acta Neuropathologica Communications 2015; 3(1): 67. doi: 10.1186/s40478-015-0245-8

115. Baudier J, Mochly-Rosen D, Newton A, et al. Comparison of S100b protein with calmodulin: Interactions with melittin and microtubule-associated τ proteins and inhibition of phosphorylation of τ proteins by protein kinase C†. Biochemistry 1987; 26(10): 2886–2893. doi: 10.1021/bi00384a033

116. Tohkin M, Yagami T, Matsubara T. Mastoparan, a peptide toxin from wasp venom, stimulates glycogenolysis mediated by an increase of the cytosolic free Ca2+ concentration but not by an increase of cAMP in rat hepatocytes. FEBS Letters 1990; 260(2): 179–182. doi: 10.1016/0014-5793(90)80098-4

117. Polanski J. Chemoinformatics. Comprehensive Chemometrics 2009; 4: 459–506. doi: 10.1016/b978-044452701-1.00006-5

118. Parzen E. On estimation of a probability density function and mode. The Annals of Mathematical Statistics 1962; 33(3): 1065–1076. doi: 10.1214/aoms/1177704472

119. Elabar S. Review on multitarget drug design based on computational strategies for the treatment of Alzheimer’s disease. AlQalam Journal of Medical and Applied Sciences 2021; 4(2): 181–190.

120. AZO Life Sciences. How is chemoinformatics used in drug discovery? Available online: https://www.azolifesciences.com/article/How-is-Chemoinformatics-Used-in-Drug-Discovery.aspx (accessed on 10 March 2023).

121. Cummings J, Lee G, Zhong K, et al. Alzheimer’s disease drug development pipeline: 2021. Alzheimer’s Dementia. Translational Research & Clinical Interventions 2021; 7(1): e12179. doi: 10.1002/trc2.12179

122. Alzheimer’s Association. What is Alzheimer’s disease? Available online: https://www.alz.org/alzheimers-dementia/what-is-alzheimers (accessed on 10 March 2023).

123. National Institute on Aging. Alzheimer’s disease fact sheet. Available online: https://www.nia.nih.gov/health/alzheimers-disease-fact-sheet (accessed on 10 March 2023).

124. Cummings J, Lee G, Zhong K, et al. Alzheimer’s disease drug development pipeline: 2021. Alzheimer’s & Dementia: Translational Research & Clinical Interventions 2021; 7(1): 12179. doi: 10.1002/trc2.12179

125. WHO. Dementia. Available online: https://www.who.int/news-room/fact-sheets/detail/dementia (acceesed on 10 March 2023).

126. Fortalezas S, Tavares L, Pimpão R, et al. Antioxidant properties and neuroprotective capacity of strawberry tree fruit (Arbutus unedo). Nutrients 2010; 2(2): 214–229. doi: 10.3390/nu2020214

127. Essa MM, Vijayan RK, Castellano-Gonzalez G, et al. Neuroprotective effect of natural products against Alzheimer’s disease. Neurochemical Research 2012; 37(9): 1829–1842. doi: 10.1007/s11064-012-0799-9

128. Wang J, Ho L, Zhao W, et al. Grape-derived polyphenolics prevent Aβ oligomerization and attenuate cognitive deterioration in a mouse model of Alzheimer’s disease. Journal of Neuroscience 2008; 28(25): 6388–6392. doi: 10.1523/jneurosci.0364-08.2008

129. ScienceDirect. Grape seed extract—An overview. Available online: https://www.sciencedirect.com/topics/medicine-and-dentistry/grape-seed-extract (accessed on 10 March 2023).

130. Zhang J, Mori A, Chen Q, et al. Fermented papaya preparation attenuates β-amyloid precursor protein: β-amyloid-mediated copper neurotoxicity in β-amyloid precursor protein and β-amyloid precursor protein Swedish mutation overexpressing SH-SY5Y cells. Neuroscience 2006; 143(1): 63–72. doi: 10.1016/j.neuroscience.2006.07.023

131. Barbagallo M, Marotta F, Dominguez LJ. Oxidative stress in patients with Alzheimer’s disease: Effect of extracts of fermented papaya powder. Mediators of Inflammation 2015; 2015: 1–6. doi: 10.1155/2015/624801.

132. Weinreb O, Mandel S, Amit T, et al. Neurological mechanisms of green tea polyphenols in Alzheimer’s and Parkinson’s diseases. The Journal of Nutritional Biochemistry 2004; 15(9): 506–516. doi: 10.1016/j.jnutbio.2004.05.002

133. Zhu Y, Wendler CC, Shi O, et al. Diazoxide promotes oligodendrocyte differentiation in neonatal brain in normoxia and chronic sublethal hypoxia. Brain Research 2014; 1586: 64–72. doi: 10.1016/j.brainres.2014.08.046

134. Basith S, Cui M, Macalino SJY, et al. Exploring G protein-coupled receptors (GPCRs) ligand space via cheminformatics approaches: Impact on rational drug design. Frontiers in Pharmacology 2018; 9: 128. doi: 10.3389/fphar.2018.00128

135. Davie CA. A review of Parkinson’s disease. British Medical Bulletin 2008; 86(1): 109–127. doi: 10.1093/bmb/ldn013

136. Dickson DW. Parkinson’s disease and parkinsonism: Neuropathology. Cold Spring Harbor Perspectives in Medicine 2012; 2(8): a009258. doi: 10.1101/cshperspect.a009258

137. Bose A, Beal MF. Mitochondrial dysfunction in Parkinson’s disease. Journal of Neurochemistry 2016; 139(S1): 216–231. doi: 10.1111/jnc.13731

138. Foley PB, Hare DJ, Double KL. A brief history of brain iron accumulation in Parkinson disease and related disorders. Journal of Neural Transmission 2022; 129(5–6): 505–520. doi: 10.1007/s00702-022-02505-5

139. Qu Y, Li J, Qin Q, et al. A systematic review and meta-analysis of inflammatory biomarkers in Parkinson’s disease. NPJ Parkinson’s Disease 2023; 9(1): 18. doi: 10.1038/s41531-023-00449-5

140. Repetto MG, Domínguez RO, Marschoff ER, et al. Free radicals, oxidative stress and oxidative damage in Parkinson’s disease. In: Dushanova J (editor). Mechanisms in Parkinson’s Disease—Models and Treatments. IntechOpen; 2012; pp. 57–58.

141. Solayman M, Islam M, Alam F, et al. Natural products combating neurodegeneration: Parkinson’s disease. Current Drug Metabolism 2017; 18(1): 50–61. doi: 10.2174/1389200217666160709204826

142. Novak V, Rogelj B, Antioxidants V, et al. Therapeutic potential of polyphenols in amyotrophic lateral sclerosis and frontotemporal dementia. Antioxidants 2021; 10(8): 1328. doi: 10.3390/antiox10081328

143. Mansuri ML, Parihar P, Solanki I, et al. Flavonoids in modulation of cell survival signalling pathways. Genes & Nutrition 2014; 9(3): 400. doi: 10.1007/s12263-014-0400-z

144. Dawson TM, Dawson VL. Molecular pathways of neurodegeneration in Parkinson’s disease. Science 2003; 302(5646): 819–822. doi: 10.1126/science.1087753

145. Ma Z, Liu H, Wu B. Structure-based drug design of catechol-O-methyltransferase inhibitors for CNS disorders. British Journal of Clinical Pharmacology 2014; 77(3): 410–420. doi: 10.1111/bcp.12169

146. Lemańska K, van der Woude H, Szymusiak H, et al. The effect of catechol O-methylation on radical scavenging characteristics of quercetin and luteolin—A mechanistic insight. Free Radical Research 2004; 38(6): 639–647. doi: 10.1080/10715760410001694062

147. Nagappan P, Krishnamurthy V. Structural prediction and comparative molecular docking studies of hesperidin and l-dopa on α-synuclein, MAO-B, COMT and UCHL-1 inhibitors. International Journal of Pharmaceutical and Clinical Research 2015; 7(3): 221–225.

148. Schultz E. Catechol-O-methyltransferase and aromatic L-amino acid decarboxylase activities in human gastrointestinal tissues. Life Sciences 1991; 49(10): 721–725. doi: 10.1016/0024-3205(91)90104-j

149. Parsons MP, Raymond LA. Huntington disease. In: Zigmond MJ, Rowland LP, Coyle JT (editors). Neurobiology of Brain Disorders—Biological Basis of Neurological and Psychiatric Disorders. Academic Press; 2015. pp. 303–320.

150. Gatto EM, Rojas NG, Persi G, et al. Huntington disease: Advances in the understanding of its mechanisms. Clinical Parkinsonism & Related Disorders 2020; 3: 100056. doi: 10.1016/j.prdoa.2020.100056

151. Hamilton PJ, Lim CJ, Nestler EJ, et al. Neuroepigenetic editing. Methods in Molecular Biology 2018; 1767: 113–136. doi: 10.1007/978-1-4939-7774-1_5

152. Lee JM, Wheeler VC, Chao MJ, et al. Identification of genetic factors that modify clinical onset of Huntington’s disease. Cell 2015; 162(3): 516–526. doi: 10.1016/j.cell.2015.07.003

153. Colpo GD, Furr Stimming E, Teixeira AL. Stem cells in animal models of Huntington disease: A systematic review. Molecular and Cellular Neuroscience 2019; 95: 43–50. doi: 10.1016/j.mcn.2019.01.006

154. Komatsu H. Innovative therapeutic approaches for Huntington’s disease: From nucleic acids to GPCR-targeting small molecules. Frontiers in Cellular Neuroscience 2021; 15: 785703. doi: 10.3389/fncel.2021.785703

155. Godino L, Turchetti D, Jackson L, et al. Impact of presymptomatic genetic testing on young adults: A systematic review. European Journal of Human Genetics 2015; 24(4): 496–503. doi: 10.1038/ejhg.2015.153

156. Pham HTN, Tran HN, Nguyenet PT, et al. Bacopa monnieri (L.) Wettst. Extract improves memory performance via promotion of neurogenesis in the hippocampal dentate gyrus of adolescent mice. International Journal of Molecular Science 2020; 21(9): 3365. doi: 10.3390/ijms21093365

157. Purusothaman D, Chalichem NSS, Bethapudi B, et al. Bacopa monnieri for cognitive health—A review of molecular mechanisms of action. In: Nutraceuticals in Brain Health and Beyond. Academic Press; 2021; pp. 15–30.

158. Lorca C, Mulet M, Arévalo-Caro C, et al. Plant-derived nootropics and human cognition: A systematic review. Critical Reviews in Food Science and Nutrition 2022; 63(22): 5521–5545. doi: 10.1080/10408398.2021.2021137

159. Sukumaran NP, Amalraj A, Gopi S. Neuropharmacological and cognitive effects of Bacopa monnieri (L.) Wettst—A review on its mechanistic aspects. Complementary Therapies in Medicine 2019; 44: 68–82. doi: 10.1016/j.ctim.2019.03.016

160. Fatima U, Roy S, Ahmad S, et al. Pharmacological attributes of Bacopa monnieri extract: Current updates and clinical manifestation. Frontiers in Nutrition 2022; 9: 972379. doi: 10.3389/fnut.2022.972379

161. Basheer A, Agarwal A, Mishra B, et al. Use of Bacopa monnieri in the Treatment of Dementia due to Alzheimer disease: Systematic review of randomized controlled trials. Interactive Journal of Medical Research 2022; 11(2): e38542. doi: 10.2196/38542

162. Qi LW, Wang CZ, Yuan CS. Ginsenosides from American ginseng: Chemical and pharmacological diversity. Phytochemistry 2011; 72(8): 689–699. doi: 10.1016/j.phytochem.2011.02.012

163. Yang X, Chu SF, Wang ZZ, et al. Ginsenoside Rg1 exerts neuroprotective effects in 3-nitropronpionic acid-induced mouse model of Huntington’s disease via suppressing MAPKs and NF-κB pathways in the striatum. Acta Pharmacologica Sinica 2021; 42(9): 1409–1421. doi: 10.1038/s41401-020-00558-4

164. Huang X, Li N, Pu Y, et al. Neuroprotective effects of ginseng phytochemicals: Recent perspectives. Molecules 2019; 24(16): 2939. doi: 10.3390/molecules24162939

165. Schäfer T, Kriege N, Humbeck L, et al. Scaffold hunter: A comprehensive visual analytics framework for drug discovery. Journal of Cheminformatics 2017; 9(1): 28. doi: 10.1186/s13321-017-0213-3

166. Ahmad I, Kumar D, Patel H. Computational investigation of phytochemicals from Withania somnifera (Indian ginseng/ashwagandha) as plausible inhibitors of GluN2B-containing NMDA receptors. Journal of Biomolecular Structure and Dynamics 2021; 40(17): 7991–8003. doi: 10.1080/07391102.2021.1905553

167. Zakaryan H, Arabyan E, Oo A, et al. Flavonoids: Promising natural compounds against viral infections. Archives of Virology 2017; 162(9): 2539–2551. doi: 10.1007/s00705-017-3417-y

168. Niu Y, Chen J, Fan Y, et al. Effect of flavonoids from Lycium barbarum leaves on the oxidation of myofibrillar proteins in minced mutton during chilled storage. Journal of Food Science 2021; 86(5): 1766–1777. doi: 10.1111/1750-3841.15728

169. Ishola AA, Oyinloye BE, Ajiboye BO, et al. Molecular docking studies of flavonoids from Andrographis paniculata as potential acetylcholinesterase, butyrylcholinesterase and monoamine oxidase inhibitors towards the treatment of neurodegenerative diseases. Biointerface Research in Applied Chemistry 2020; 11(3): 9871–9879. doi: 10.33263/briac113.98719879

170. Yang H, Chen D, Cui QC, et al. Celastrol, a triterpene extracted from the Chinese “Thunder of God Vine,” is a potent proteasome inhibitor and suppresses human prostate cancer growth in nude mice. Cancer Research 2006; 66(9): 4758–4765. doi: 10.1158/0008-5472.can-05-4529

171. Lin MW, Lin CC, Chen YH, et al. Celastrol inhibits dopaminergic neuronal death of Parkinson’s disease through activating mitophagy. Antioxidants 2019; 9(1): 37. doi: 10.3390/antiox9010037

172. Cleren C, Calingasan NY, Chen J, et al. Celastrol protects against MPTP- and 3-nitropropionic acid-induced neurotoxicity. Journal of Neurochemistry 2005; 94(4): 995–1004. doi: 10.1111/j.1471-4159.2005.03253.x

173. Ansar AFM, Souza IS, Chiang KJ, Haiman Z. Effects of multiple sclerosis on locomotor pattern generation. Available online: https://isn.ucsd.edu/courses/beng260/2017/reports/2017_Group8.pdf (accessed on 11 March 2023).

174. Filippini G, Lasserson TJ, Dwan K, et al. Cannabis and cannabinoids for people with multiple sclerosis. Cochrane Cochrane Database of Systematic Reviews 2019; 2019(10): CD013444. doi: 10.1002/14651858.CD013444

175. Cree BAC, Bennett JL, Kim HJ, et al. Inebilizumab for the treatment of neuromyelitis optica spectrum disorder (N-MOmentum): A double-blind, randomised placebo-controlled phase 2/3 trial. The Lancet 2019; 394(10206): 1352–1363. doi: 10.1016/s0140-6736(19)31817-3

176. Nabavi S, Daglia M, D’Antona G, et al. Natural compounds used as therapies targeting to amyotrophic lateral sclerosis. Current Pharmaceutical Biotechnology 2015; 16(3): 211–218. doi: 10.2174/1389201016666150118132224

177. Singh B, Kaur P, Gopichand, et al. Biology and chemistry of Ginkgo biloba. Fitoterapia 2008; 79(6): 401–418. doi: 10.1016/j.fitote.2008.05.007

178. Singh SK, Srivastav S, Castellani RJ, et al. Neuroprotective and antioxidant effect of ginkgo biloba extract against AD and other neurological disorders. Neurotherapeutics 2019; 16(3): 666–674. doi: 10.1007/s13311-019-00767-8

179. Zheng Y, Xie Y, Qi M, et al. Ginkgo biloba extract is comparable with donepezil in improving functional recovery in Alzheimer’s disease: Results from a multilevel characterized study based on clinical features and resting-state functional magnetic resonance imaging. Frontiers in Pharmacology 2021; 12: 721216. doi: 10.3389/fphar.2021.721216

180. Britannica. ginseng. Available online: https://www.britannica.com/plant/ginseng (accessed on 11 March 2023).

181. Zhao A, Liu N, Yao M, et al. A review of neuroprotective effects and mechanisms of ginsenosides from Panax ginseng in treating ischemic stroke. Frontiers in Pharmacology 2022; 13: 946752. doi: 10.3389/fphar.2022.946752

182. Jang WY, Hwang JY, Cho JY. Ginsenosides from Panax ginseng as key modulators of NF-κB signaling are powerful anti-inflammatory and anticancer agents. International Journal of Molecular Sciences 2023; 24(7): 6119. doi: 10.3390/ijms24076119

183. Morshed MN, Ahn JC, Mathiyalagan R, et al. Antioxidant activity of Panax ginseng to regulate ROS in various chronic diseases. Applied Sciences 2023; 13(5): 2893. doi: 10.3390/app13052893

184. Polkowski K, Mazurek AP. BIological properties of genistein. A review of in vitro and in vivo data. Acta Poloniae Pharmaceutica 2000; 57(2): 135–155.

185. Gan M, Ma J, Chen J, et al. miR-222 is involved in the amelioration effect of genistein on dexamethasone-induced skeletal muscle atrophy. Nutrients 2022; 14(9): 1861. doi: 10.3390/nu14091861

186. Rastogi S. Rehabilitative potential of Ayurveda for neurological deficits caused by traumatic spinal cord injury. Journal of Ayurveda and Integrative Medicine 2014; 5(1): 56. doi: 10.4103/0975-9476.128868

187. Zucchella C, Sinforiani E, Tamburin S, et al. The multidisciplinary approach to Alzheimer’s disease and dementia. A narrative review of non-pharmacological treatment. Frontiers in Neurology 2018; 9: 1508. doi: 10.3389/fneur.2018.01058

188. Cragg GM, Grothaus PG, Newman DJ. Impact of natural products on developing new anti-cancer agents. Chemical Reviews 2009; 109(7): 3012–3043. doi: 10.1021/cr900019j

189. Aboulwafa MM, Youssef FS, Gad HA, et al. A comprehensive insight on the health benefits and phytoconstituents of camellia sinensis and recent approaches for its quality control. Antioxidants (Basel) 2019; 8(10): 455. doi: 10.3390/antiox8100455

190. Kellogg JJ, Paine MF, McCune JS, et al. Selection and characterization of botanical natural products for research studies: a NaPDI center recommended approach. Natural Product Reports 2019; 36(8): 1196–1221. doi: 10.1039/c8np00065d

191. NCCIH. Natural doesn’t necessarily mean safer, or better. Available online: https://www.nccih.nih.gov/health/know-science/natural-doesnt-mean-better (accessed on 15 March 2023).

192. Whitcup SM. Clinical trials in neuroprotection. Progress in Brain Research 2008; 173: 323–335. doi: 10.1016/S0079-6123(08)01123-0

193. Prasad S, Srivastava A, Singh N, Singh H. Present and future challenges in therapeutic designing using computational approaches. In: Computational Approaches for Novel Therapeutic and Diagnostic Designing to Mitigate SARS-CoV2 Infection. Elsevier; 2022. pp. 489–505.




DOI: https://doi.org/10.24294/ace.v7i1.2140

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