The Potential Mechanism of Eriodictyol in Treating Alzheimer's Disease: A Study on Computer-assisted Investigational Strategies

Page: [2086 - 2107] Pages: 22

  • * (Excluding Mailing and Handling)

Abstract

Background: At present, drug development for treating Alzheimer’s disease (AD) is still highly challenging. Eriodictyol (ERD) has shown great potential in treating AD, but its molecular mechanism is unknown.

Objective: We aimed to explore the potential targets and mechanisms of ERD in the treatment of AD through network pharmacology, molecular docking, and molecular dynamics simulations.

Methods: ERD-related targets were predicted based on the CTD, SEA, PharmMapper, Swiss TargetPrediction, and ETCM databases, and AD-related targets were predicted through the TTD, OMIM, DrugBank, GeneCards, Disgenet, and PharmGKB databases. Protein-protein interaction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomics analyses (KEGG) were used to analyse the potential targets and key pathways of the anti-AD effect of ERD. Subsequently, potential DEGs affected by AD were analysed using the AlzData database, and their relationships with ERD were evaluated through molecular docking and molecular dynamics simulations.

Results: A total of 198 ERD-related targets, 3716 AD-related targets, and 122 intersecting targets were identified. GO annotation analysis revealed 1497 biological processes, 78 cellular components, and 132 molecular functions of 15 core targets. KEGG enrichment analysis identified 168 signalling pathways. We ultimately identified 9 DEGs associated with AD through analysis of the AlzData data. Molecular docking results showed good affinity between the selected targets and ERD, with PTGS2, HSP90AA1, and BCL2. The interactions were confirmed by molecular dynamics simulations.

Conclusion: ERD exerts anti-AD effects through multiple targets, pathways, and levels, providing a theoretical foundation and valuable reference for the development of ERD as a natural anti-AD drug.

[1]
Serrano-Pozo A, Growdon JH. Is Alzheimer’s disease risk modifiable? J Alzheimers Dis 2019; 67(3): 795-819.
[http://dx.doi.org/10.3233/JAD181028] [PMID: 30776012]
[2]
Scheltens P, De Strooper B, Kivipelto M, et al. Alzheimer’s disease. Lancet 2021; 397(10284): 1577-90.
[http://dx.doi.org/10.1016/S0140-6736(20)32205-4] [PMID: 33667416]
[3]
Cummings J, Lee G, Nahed P, et al. Alzheimer’s disease drug development pipeline: 2022. Alzheimers Dement 2022; 8(1): e12295.
[4]
Simunkova M, Barbierikova Z, Jomova K, et al. Antioxidant vs. prooxidant properties of the flavonoid, kaempferol, in the presence of Cu(II) ions: A ROS-scavenging activity, fenton reaction and DNA damage study. Int J Mol Sci 2021; 22(4): 1619.
[http://dx.doi.org/10.3390/ijms22041619] [PMID: 33562744]
[5]
Treatment for Alzheimer’s disease: Time to get ready. Lancet Neurol 2023; 22(6): 455.
[http://dx.doi.org/10.1016/S1474-4422(23)00167-9] [PMID: 37210085]
[6]
Cummings J, Osse AML. Anti-amyloid monoclonal antibodies for the treatment of Alzheimer’s disease. BioDrugs 2024; 38: 5-22.
[7]
Yuan Y, Zhai Y, Chen J, Xu X, Wang H. Kaempferol ameliorates oxygen-glucose deprivation/reoxygenation-induced neuronal ferroptosis by activating Nrf2/SLC7A11/GPX4 axis. Biomolecules 2021; 11(7): 923.
[http://dx.doi.org/10.3390/biom11070923] [PMID: 34206421]
[8]
Lv F, Du Q, Li L, et al. Eriodictyol inhibits glioblastoma migration and invasion by reversing EMT via downregulation of the P38 MAPK/GSK-3β/ZEB1 pathway. Eur J Pharmacol 2021; 900: 174069.
[http://dx.doi.org/10.1016/j.ejphar.2021.174069] [PMID: 33811837]
[9]
Buranasudja V, Muangnoi C, Sanookpan K, Halim H, Sritularak B, Rojsitthisak P. Eriodictyol attenuates H2O2-induced oxidative damage in human dermal fibroblasts through enhanced capacity of antioxidant machinery. Nutrients 2022; 14(12): 2553.
[http://dx.doi.org/10.3390/nu14122553] [PMID: 35745283]
[10]
Li L, Li WJ, Zheng XR, et al. Eriodictyol ameliorates cognitive dysfunction in APP/PS1 mice by inhibiting ferroptosis via vitamin D receptor-mediated Nrf2 activation. Mol Med 2022; 28(1): 11.
[http://dx.doi.org/10.1186/s10020-022-00442-3] [PMID: 35093024]
[11]
Zhao L, Zhang H, Li N, et al. Network pharmacology, a promising approach to reveal the pharmacology mechanism of Chinese medicine formula. J Ethnopharmacol 2023; 309: 116306.
[http://dx.doi.org/10.1016/j.jep.2023.116306] [PMID: 36858276]
[12]
Nogales C, Mamdouh ZM, List M, Kiel C, Casas AI, Schmidt HHHW. Network pharmacology: Curing causal mechanisms instead of treating symptoms. Trends Pharmacol Sci 2022; 43(2): 136-50.
[http://dx.doi.org/10.1016/j.tips.2021.11.004] [PMID: 34895945]
[13]
Komura H, Watanabe R, Mizuguchi K. The trends and future prospective of in silico models from the viewpoint of ADME evaluation in drug discovery. Pharmaceutics 2023; 15(11): 2619.
[http://dx.doi.org/10.3390/pharmaceutics15112619] [PMID: 38004597]
[14]
Weininger D. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 1988; 28(1): 31-6.
[http://dx.doi.org/10.1021/ci00057a005]
[15]
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): 42717.
[http://dx.doi.org/10.1038/srep42717] [PMID: 28256516]
[16]
Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ. Comparative Toxicogenomics Database (CTD): Update 2023. Nucleic Acids Res 2023; 51(D1): D1257-62.
[http://dx.doi.org/10.1093/nar/gkac833] [PMID: 36169237]
[17]
Wang X, Shen Y, Wang S, et al. PharmMapper 2017 update: A web server for potential drug target identification with a comprehensive target pharmacophore database. Nucleic Acids Res 2017; 45(W1): W356-60.
[http://dx.doi.org/10.1093/nar/gkx374] [PMID: 28472422]
[18]
Xu HY, Zhang YQ, Liu ZM, et al. ETCM: An encyclopaedia of traditional Chinese medicine. Nucleic Acids Res 2019; 47(D1): D976-82.
[http://dx.doi.org/10.1093/nar/gky987] [PMID: 30365030]
[19]
Zhang J, Durham J, Cong Q. Revolutionizing protein-protein interaction prediction with deep learning. Curr Opin Struct Biol 2024; 85: 102775.
[http://dx.doi.org/10.1016/j.sbi.2024.102775] [PMID: 38330793]
[20]
Shannon P, Markiel A, Ozier O, et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res 2003; 13(11): 2498-504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[21]
Stelzer G, Plaschkes I, Oz-Levi D, et al. VarElect: The phenotype-based variation prioritizer of the GeneCards Suite. BMC Genomics 2016; 17 (Suppl. 2): 444.
[22]
Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019; 10(1): 1523.
[http://dx.doi.org/10.1038/s41467-019-09234-6] [PMID: 30944313]
[23]
Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28(1): 27-30.
[http://dx.doi.org/10.1093/nar/28.1.27] [PMID: 10592173]
[24]
Gene Ontology Consortium. Gene ontology consortium: Going forward. Nucleic Acids Res 2015; 43(Database issue): D1049-56.
[PMID: 25428369]
[25]
The Gene Ontology Consortium. The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Res 2019; 47(D1): D330-8.
[http://dx.doi.org/10.1093/nar/gky1055] [PMID: 30395331]
[26]
Xu M, Zhang DF, Luo R, et al. A systematic integrated analysis of brain expression profiles reveals YAP1 and other prioritized hub genes as important upstream regulators in Alzheimer’s disease. Alzheimers Dement 2018; 14(2): 215-29.
[http://dx.doi.org/10.1016/j.jalz.2017.08.012] [PMID: 28923553]
[27]
Keil JM, Qalieh A, Kwan KY. Brain transcriptome databases: A user’s guide. J Neurosci 2018; 38(10): 2399-412.
[http://dx.doi.org/10.1523/JNEUROSCI.1930-17.2018] [PMID: 29437890]
[28]
Saikia S, Bordoloi M. Molecular docking: Challenges, advances and its use in drug discovery perspective. Curr Drug Targets 2019; 20(5): 501-21.
[http://dx.doi.org/10.2174/1389450119666181022153016] [PMID: 30360733]
[29]
Seeliger D, de Groot BL. Ligand docking and binding site analysis with PyMOL and Autodock/Vina. J Comput Aided Mol Des 2010; 24(5): 417-22.
[http://dx.doi.org/10.1007/s10822-010-9352-6] [PMID: 20401516]
[30]
Hospital A, Goñi JR, Orozco M, Gelpí JL. Molecular dynamics simulations: Advances and applications. Adv Appl Bioinform Chem 2015; 8: 37-47.
[PMID: 26604800]
[31]
Karplus M, McCammon JA. Molecular dynamics simulations of biomolecules. Nat Struct Biol 2002; 9(9): 646-52.
[http://dx.doi.org/10.1038/nsb0902-646] [PMID: 12198485]
[32]
Wu X, Xu LY, Li EM, Dong G. Application of molecular dynamics simulation in biomedicine. Chem Biol Drug Des 2022; 99(5): 789-800.
[http://dx.doi.org/10.1111/cbdd.14038] [PMID: 35293126]
[33]
Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC. GROMACS: Fast, flexible, and free. J Comput Chem 2005; 26(16): 1701-18.
[http://dx.doi.org/10.1002/jcc.20291] [PMID: 16211538]
[34]
Pronk S, Páll S, Schulz R, et al. GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 2013; 29(7): 845-54.
[http://dx.doi.org/10.1093/bioinformatics/btt055] [PMID: 23407358]
[35]
Weber OC, Uversky VN. How accurate are your simulations? Effects of confined aqueous volume and AMBER FF99SB and CHARMM22/CMAP force field parameters on structural ensembles of intrinsically disordered proteins: Amyloid-β42 in water. Intrinsically Disord Proteins 2017; 5(1): e1377813.
[http://dx.doi.org/10.1080/21690707.2017.1377813] [PMID: 30250773]
[36]
Boonstra S, Onck PR, van der Giessen E. CHARMM TIP3P water model suppresses peptide folding by solvating the unfolded state. J Phys Chem B 2016; 120(15): 3692-8.
[http://dx.doi.org/10.1021/acs.jpcb.6b01316] [PMID: 27031562]
[37]
Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings1. Adv Drug Deliv Rev 2001; 46(1-3): 3-26. PII of original article: S0169- 409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3-25.1.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0] [PMID: 11259830]
[38]
Middleton G, Piñón LG, Wyatt S, Davies AM. Bcl-2 accelerates the maturation of early sensory neurons. J Neurosci 1998; 18(9): 3344-50.
[http://dx.doi.org/10.1523/JNEUROSCI.18-09-03344.1998] [PMID: 9547242]
[39]
Liu G, Li Z, Li Z, Hao C, Liu Y. Molecular dynamics simulation and in vitro digestion to examine the impact of theaflavin on the digestibility and structural properties of myosin. Int J Biol Macromol 2023; 247: 125836.
[http://dx.doi.org/10.1016/j.ijbiomac.2023.125836] [PMID: 37455005]
[40]
Pitera JW. Expected distributions of root-mean-square positional deviations in proteins. J Phys Chem B 2014; 118(24): 6526-30.
[http://dx.doi.org/10.1021/jp412776d] [PMID: 24655018]
[41]
Kalirajan R, Rishabh K, Srikanth J, Niharika M, Preeya N, Rezaul I. Molecular docking, MM-GBSA, and molecular dynamics approach: 5-MeO-DMT analogues as potential antidepressants. Arch Razi Inst 2023; 78(5): 1603-14.
[PMID: 38590677]
[42]
Kumar BK, Faheem , Sekhar KVGC, et al. Pharmacophore based virtual screening, molecular docking, molecular dynamics and MM-GBSA approach for identification of prospective SARS-CoV-2 inhibitor from natural product databases. J Biomol Struct Dyn 2022; 40(3): 1363-86.
[http://dx.doi.org/10.1080/07391102.2020.1824814] [PMID: 32981461]
[43]
Baidya ATK, Kumar A, Kumar R, Darreh-Shori T. Allosteric binding sites of Aβ peptides on the acetylcholine synthesizing enzyme ChAT as deduced by in silico molecular modeling. Int J Mol Sci 2022; 23(11): 6073.
[http://dx.doi.org/10.3390/ijms23116073] [PMID: 35682752]
[44]
Li H, Weng Q, Gong S, et al. Kaempferol prevents acetaminophen-induced liver injury by suppressing hepatocyte ferroptosis via Nrf2 pathway activation. Food Funct 2023; 14(4): 1884-96.
[http://dx.doi.org/10.1039/D2FO02716J] [PMID: 36723004]
[45]
Deng Z, Hassan S, Rafiq M, et al. Pharmacological activity of eriodictyol: The major natural polyphenolic flavanone. Evid Based Complementary Altern Med 2020; 2020: 6681352.
[46]
Ren JX, Sun X, Yan XL, Guo ZN, Yang Y. Ferroptosis in neurological diseases. Front Cell Neurosci 2020; 14: 218.
[http://dx.doi.org/10.3389/fncel.2020.00218] [PMID: 32754017]
[47]
Xie Y, Hou W, Song X, et al. Ferroptosis: Process and function. Cell Death Differ 2016; 23(3): 369-79.
[http://dx.doi.org/10.1038/cdd.2015.158] [PMID: 26794443]
[48]
Lane DJR, Ayton S, Bush AI. Iron and Alzheimer’s disease: An update on emerging mechanisms. J Alzheimers Dis 2018; 64(s1): S379-95.
[http://dx.doi.org/10.3233/JAD-179944] [PMID: 29865061]
[49]
Guo P, Zeng M, Wang S, et al. Eriodictyol and homoeriodictyol improve memory impairment in Aβ25-35-induced mice by inhibiting the NLRP3 inflammasome. Molecules 2022; 27(8): 2488.
[http://dx.doi.org/10.3390/molecules27082488] [PMID: 35458684]
[50]
Guo JW, Guan PP, Ding WY, et al. Erythrocyte membrane-encapsulated celecoxib improves the cognitive decline of Alzheimer’s disease by concurrently inducing neurogenesis and reducing apoptosis in APP/PS1 transgenic mice. Biomaterials 2017; 145: 106-27.
[http://dx.doi.org/10.1016/j.biomaterials.2017.07.023] [PMID: 28865290]
[51]
Ma SL, Tang NLS, Zhang YP, et al. Association of prostaglandin-endoperoxide synthase 2 (PTGS2) polymorphisms and Alzheimer’s disease in Chinese. Neurobiol Aging 2008; 29(6): 856-60.
[http://dx.doi.org/10.1016/j.neurobiolaging.2006.12.011] [PMID: 17234302]
[52]
He P, Yan S, Zheng J, et al. Eriodictyol attenuates LPS-induced neuroinflammation, amyloidogenesis, and cognitive impairments via the inhibition of NF-κB in male C57BL/6J mice and BV2 microglial cells. J Agric Food Chem 2018; 66(39): 10205-14.
[http://dx.doi.org/10.1021/acs.jafc.8b03731] [PMID: 30208700]
[53]
Xiang Z, Ho L, Yemul S, et al. Cyclooxygenase-2 promotes amyloid plaque deposition in a mouse model of Alzheimer’s disease neuropathology. Gene Expr 2002; 10(5): 271-8.
[http://dx.doi.org/10.3727/000000002783992352] [PMID: 12450219]
[54]
Brust AK, Ulbrich HK, Seigel GM, Pfeiffer N, Grus FH. Effects of cyclooxygenase inhibitors on apoptotic neuroretinal cells. Biomark Insights 2008; 3: BMI.S692.
[http://dx.doi.org/10.4137/BMI.S692] [PMID: 19578520]
[55]
Zhou Z, Lu C, Meng S, et al. Silencing of PTGS2 exerts promoting effects on angiogenesis endothelial progenitor cells in mice with ischemic stroke via repression of the NF‐κB signaling pathway. J Cell Physiol 2019; 234(12): 23448-60.
[http://dx.doi.org/10.1002/jcp.28914] [PMID: 31222746]
[56]
Siddiqui WA, Ahad A, Ahsan H. The mystery of BCL2 family: Bcl-2 proteins and apoptosis: An update. Arch Toxicol 2015; 89(3): 289-317.
[http://dx.doi.org/10.1007/s00204-014-1448-7] [PMID: 25618543]
[57]
Peña-Blanco A, García-Sáez AJ. Bax, Bak and beyond - mitochondrial performance in apoptosis. FEBS J 2018; 285(3): 416-31.
[http://dx.doi.org/10.1111/febs.14186] [PMID: 28755482]
[58]
Salakou S, Kardamakis D, Tsamandas AC, et al. Increased Bax/Bcl-2 ratio up-regulates caspase-3 and increases apoptosis in the thymus of patients with myasthenia gravis. In Vivo 2007; 21(1): 123-32.
[PMID: 17354625]
[59]
Martinou JC, Dubois-Dauphin M, Staple JK, et al. Overexpression of BCL-2 in transgenic mice protects neurons from naturally occurring cell death and experimental ischemia. Neuron 1994; 13(4): 1017-30.
[http://dx.doi.org/10.1016/0896-6273(94)90266-6] [PMID: 7946326]
[60]
Li Z, Xiao G, Wang H, He S, Zhu Y. A preparation of Ginkgo biloba L. leaves extract inhibits the apoptosis of hippocampal neurons in post-stroke mice via regulating the expression of Bax/Bcl-2 and Caspase-3. J Ethnopharmacol 2021; 280: 114481.
[http://dx.doi.org/10.1016/j.jep.2021.114481] [PMID: 34343651]
[61]
He LL, Wang YC, Ai YT, et al. Qiangji decoction alleviates neurodegenerative changes and hippocampal neuron apoptosis induced by D-Galactose via regulating AMPK/SIRT1/NF-κB signaling pathway. Front Pharmacol 2021; 12: 735812.
[http://dx.doi.org/10.3389/fphar.2021.735812] [PMID: 34630111]
[62]
Qian X, Liu X, Chen S, Tang H. Integrating peripheral blood and brain transcriptomics to identify immunological features associated with Alzheimer’s disease in mild cognitive impairment patients. Front Immunol 2022; 13: 986346.
[http://dx.doi.org/10.3389/fimmu.2022.986346] [PMID: 36159817]
[63]
van Oosten-Hawle P. Organismal roles of Hsp90. Biomolecules 2023; 13(2): 251.
[http://dx.doi.org/10.3390/biom13020251] [PMID: 36830620]
[64]
Hoter A, El-Sabban M, Naim H. The HSP90 family: Structure, regulation, function, and implications in health and disease. Int J Mol Sci 2018; 19(9): 2560.
[http://dx.doi.org/10.3390/ijms19092560] [PMID: 30158430]
[65]
Dou F, Netzer WJ. Chaperones increase association of tau protein with microtubules. Proc Natl Acad Sci USA 2003; 100(2): 721-6.
[66]
Long HZ, Cheng Y, Zhou ZW, Luo HY, Wen DD, Gao LC. PI3K/AKT signal pathway: A target of natural products in the prevention and treatment of Alzheimer’s disease and Parkinson’s disease. Front Pharmacol 2021; 12: 648636.
[http://dx.doi.org/10.3389/fphar.2021.648636] [PMID: 33935751]
[67]
Zheng X, Wu X, Wen Q, et al. Eriodictyol alleviated LPS/D-GalN-induced acute liver injury by inhibiting oxidative stress and cell apoptosis via PI3K/AKT signaling pathway. Nutrients 2023; 15(20): 4349.
[http://dx.doi.org/10.3390/nu15204349] [PMID: 37892424]
[68]
Tiwari S, Atluri V, Kaushik A, Yndart A, Nair M. Alzheimer’s disease: Pathogenesis, diagnostics, and therapeutics. Int J Nanomed 2019; 14: 5541-54.
[http://dx.doi.org/10.2147/IJN.S200490] [PMID: 31410002]
[69]
Jing X, Shi H, Zhu X, et al. Eriodictyol attenuates β-Amyloid 25-35 peptide-induced oxidative cell death in primary cultured neurons by activation of Nrf2. Neurochem Res 2015; 40(7): 1463-71.
[http://dx.doi.org/10.1007/s11064-015-1616-z] [PMID: 25994859]
[70]
Leng F, Edison P. Neuroinflammation and microglial activation in Alzheimer disease: Where do we go from here? Nat Rev Neurol 2021; 17(3): 157-72.
[http://dx.doi.org/10.1038/s41582-020-00435-y] [PMID: 33318676]
[71]
Oliveira TG, Di Paolo G. Phospholipase D in brain function and Alzheimer’s disease. Biochim Biophys Acta Mol Cell Biol Lipids 2010; 1801(8): 799-805.
[http://dx.doi.org/10.1016/j.bbalip.2010.04.004] [PMID: 20399893]
[72]
Bravo FV, Da Silva J, Chan RB, Di Paolo G, Teixeira-Castro A, Oliveira TG. Phospholipase D functional ablation has a protective effect in an Alzheimer’s disease Caenorhabditis elegans model. Sci Rep 2018; 8(1): 3540.
[http://dx.doi.org/10.1038/s41598-018-21918-5] [PMID: 29476137]
[73]
McDermott MI, Wang Y, Wakelam MJO, Bankaitis VA. Mammalian phospholipase D: Function, and therapeutics. Prog Lipid Res 2020; 78: 101018.
[http://dx.doi.org/10.1016/j.plipres.2019.101018] [PMID: 31830503]
[74]
Kobayashi M, McCartney DG, Kanfer JN. Developmental changes and regional distribution of phospholipase D and base exchange enzyme activities in rat brain. Neurochem Res 1988; 13(8): 771-6.
[http://dx.doi.org/10.1007/BF00971601] [PMID: 3173625]
[75]
Bourne KZ, Natarajan C, Perez CXM, Tumurbaatar B, Taglialatela G, Krishnan B. Suppressing aberrant phospholipase D1 signaling in 3xTg Alzheimer’s disease mouse model promotes synaptic resilience. Sci Rep 2019; 9(1): 18342.
[http://dx.doi.org/10.1038/s41598-019-54974-6] [PMID: 31797996]