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Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Research Article

Effects of Compound in Hedyotis diffusa Willd against Acute Myeloid Leukemia: An In Silico and In Vitro Study

Author(s): Chunyi Lyu, Xuewei Yin, Zonghong Li, Teng Wang and Ruirong Xu*

Volume 21, Issue 16, 2024

Published on: 15 April, 2024

Page: [3526 - 3541] Pages: 16

DOI: 10.2174/0115701808287616240321080922

Price: $65

Abstract

Background: Hedyotis diffusa Willd (HDW) is an herb that has been used empirically for treating cancer, and its antileukemic effect has been confirmed by laboratory evidence. This study aimed to explore the underlying mechanism by which HDW and its active compound exert effects on acute myeloid leukemia (AML) through in silico analyses combined with experimental validation.

Methods: The targets of the compounds were collected from the database and intersected with AML targets. Based on these data, a protein-protein interaction (PPI) network and compound-target (C-T) network were constructed, and KEGG enrichment analysis was performed. Topological analysis of the C-T network and PPI network was performed to screen for hub compounds and targets. Molecular dynamics simulations were conducted to test the binding mode and strength between the targets and the compounds at the molecular level. Cell viability, flow cytometry, ELISA, and Q-PCR were further used to evaluate the in silico results.

Results: A total of 86 targets of 12 screened active compounds of HDW against AML were identified. According to topological analysis, tumor protein p53 (TP53) and signal transducer and activator of transcription 3 (STAT3) exhibited the highest degree of centrality (DC) in the PPI networks of HDW targets. Quercetin had a higher affinity for TP53 than for STAT3. Molecular dynamics simulations confirmed that the TP53-quercetin docked complex was stable with respect to the original TP53-ligand complex. The targets of HDW and quercetin against AML were significantly enriched in multiple biological processes, including the p53 signaling pathway and apoptosis. The results from the in vitro experiment confirmed that quercetin triggers apoptosis in the human AML cell line KG-1 through the p53 pathway protein.

Conclusion: This study outlines the multi-compound, multi-target, and multi-pathway mechanism by which HDW affects AML based on an in silico predictive model and further validates the antileukemic mechanism of the screened active compound in an in vitro model. This study provides a perspective for studying the antileukemic mechanism of HDW for further research.

Keywords: Hedyotis diffusa Willd, leukemia, quercetin, TP53, in silico, in vitro, STAT3, protein-protein interaction.

Graphical Abstract
[1]
Niu, Y.; Meng, Q.X. Chemical and preclinical studies on Hedyotis diffusa with anticancer potential. J. Asian Nat. Prod. Res., 2013, 15(5), 550-565.
[http://dx.doi.org/10.1080/10286020.2013.781589] [PMID: 23600735]
[2]
Wang, C.Y.; Wang, T.C.; Liang, W.M.; Hung, C.H.; Chiou, J.S.; Chen, C.J.; Tsai, F.J.; Huang, S.T.; Chang, T.Y.; Lin, T.H.; Liao, C.C.; Huang, S.M.; Li, T.M.; Lin, Y.J. Effect of chinese herbal medicine therapy on overall and cancer related mortality in patients with advanced nasopharyngeal carcinoma in Taiwan. Front. Pharmacol., 2021, 11, 607413.
[http://dx.doi.org/10.3389/fphar.2020.607413] [PMID: 33708119]
[3]
Yeh, Y.C.; Chen, H.Y.; Yang, S.H.; Lin, Y.H.; Chiu, J.H.; Lin, Y.H.; Chen, J.L. Hedyotis diffusa Combined with Scutellaria barbata are the core treatment of chinese herbal medicine used for breast cancer patients: A population-based study. Evid. Based Complement. Alternat. Med., 2014, 2014, 1-9.
[http://dx.doi.org/10.1155/2014/202378] [PMID: 24734104]
[4]
Chao, T.H.; Fu, P.K.; Chang, C.H.; Chang, S.N.; Chiahung Mao, F.; Lin, C.H. Prescription patterns of Chinese herbal products for post-surgery colon cancer patients in Taiwan. J. Ethnopharmacol., 2014, 155(1), 702-708.
[http://dx.doi.org/10.1016/j.jep.2014.06.012] [PMID: 24945402]
[5]
Han, X.; Zhang, X.; Wang, Q.; Wang, L.; Yu, S. Antitumor potential of Hedyotis diffusa Willd: A systematic review of bioactive constituents and underlying molecular mechanisms. Biomed. Pharmacother., 2020, 130, 110735.
[http://dx.doi.org/10.1016/j.biopha.2020.110735] [PMID: 34321173]
[6]
Pan, L.; Feng, F.; Wu, J.; Fan, S.; Han, J.; Wang, S.; Yang, L.; Liu, W.; Wang, C.; Xu, K. Demethylzeylasteral targets lactate by inhibiting histone lactylation to suppress the tumorigenicity of liver cancer stem cells. Pharmacol. Res., 2022, 181, 106270.
[http://dx.doi.org/10.1016/j.phrs.2022.106270] [PMID: 35605812]
[7]
Wei, S.; Sun, T.; Du, J.; Zhang, B.; Xiang, D.; Li, W. Xanthohumol, a prenylated flavonoid from Hops, exerts anticancer effects against gastric cancer in-vitro. Oncol. Rep., 2018, 40(6), 3213-3222.
[http://dx.doi.org/10.3892/or.2018.6723] [PMID: 30272303]
[8]
Gao, T.H.; Liao, W.; Lin, L.T.; Zhu, Z.P.; Lu, M.G.; Fu, C.M.; Xie, T. Curcumae rhizoma and its major constituents against hepatobiliary disease: Pharmacotherapeutic properties and potential clinical applications. Phytomedicine, 2022, 102, 154090.
[http://dx.doi.org/10.1016/j.phymed.2022.154090] [PMID: 35580439]
[9]
Lin, C.C.; Kuo, C.L.; Lee, M.H.; Hsu, S.C.; Huang, A.C.; Tang, N.Y.; Lin, J.P.; Yang, J.S.; Lu, C.C.; Chiang, J.H.; Chueh, F.S.; Chung, J.G. Extract of Hedyotis diffusa Willd influences murine leukemia WEHI-3 cells in vivo as well as promoting T- and B-cell proliferation in leukemic mice. In Vivo, 2011, 25(4), 633-640.
[PMID: 21709007]
[10]
Kuo, Y.J.; Yang, J.S.; Lu, C.C.; Chiang, S.; Lin, J.G.; Chung, J.G. Ethanol extract of Hedyotis diffusa willd upregulates G0/G1 phase arrest and induces apoptosis in human leukemia cells by modulating caspase cascade signaling and altering associated genes expression was assayed by cDNA microarray. Environ. Toxicol., 2015, 30(10), 1162-1177.
[http://dx.doi.org/10.1002/tox.21989] [PMID: 24677778]
[11]
Ru, J.; Li, P.; Wang, J.; Zhou, W.; Li, B.; Huang, C.; Li, P.; Guo, Z.; Tao, W.; Yang, Y.; Xu, X.; Li, Y.; Wang, Y.; Yang, L. TCMSP: A database of systems pharmacology for drug discovery from herbal medicines. J. Cheminform., 2014, 6(1), 13.
[http://dx.doi.org/10.1186/1758-2946-6-13] [PMID: 24735618]
[12]
Pires, D.E.V.; Blundell, T.L.; Ascher, D.B. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. J. Med. Chem., 2015, 58(9), 4066-4072.
[http://dx.doi.org/10.1021/acs.jmedchem.5b00104] [PMID: 25860834]
[13]
Kim, S.; Chen, J.; Cheng, T.; Gindulyte, A.; He, J.; He, S.; Li, Q.; Shoemaker, B.A.; Thiessen, P.A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E.E. PubChem 2023 update. Nucleic Acids Res., 2023, 51(D1), D1373-D1380.
[http://dx.doi.org/10.1093/nar/gkac956] [PMID: 36305812]
[14]
Gfeller, D.; Grosdidier, A.; Wirth, M.; Daina, A.; Michielin, O.; Zoete, V. SwissTargetPrediction: A web server for target prediction of bioactive small molecules. Nucleic Acids Res., 2014, 42, W32-W38.
[http://dx.doi.org/10.1093/nar/gku293] [PMID: 24792161]
[15]
Xu, H.Y.; Zhang, Y.Q.; Liu, Z.M.; Chen, T.; Lv, C.Y.; Tang, S.H.; Zhang, X.B.; Zhang, W.; Li, Z.Y.; Zhou, R.R.; Yang, H.J.; Wang, X.J.; Huang, L.Q. ETCM: An encyclopaedia of traditional Chinese medicine. Nucleic Acids Res., 2019, 47(D1), D976-D982.
[http://dx.doi.org/10.1093/nar/gky987] [PMID: 30365030]
[16]
Wishart, D.S.; Feunang, Y.D.; Guo, A.C.; Lo, E.J.; Marcu, A.; Grant, J.R.; Sajed, T.; Johnson, D.; Li, C.; Sayeeda, Z.; Assempour, N.; Iynkkaran, I.; Liu, Y.; Maciejewski, A.; Gale, N.; Wilson, A.; Chin, L.; Cummings, R.; Le, D.; Pon, A.; Knox, C.; Wilson, M. DrugBank 5.0: A major update to the DrugBank database for 2018. Nucleic Acids Res., 2018, 46(D1), D1074-D1082.
[http://dx.doi.org/10.1093/nar/gkx1037] [PMID: 29126136]
[17]
Wang, X.; Shen, Y.; Wang, S.; Li, S.; Zhang, W.; Liu, X.; Lai, L.; Pei, J.; Li, H. PharmMapper 2017 update: A web server for potential drug target identification with a comprehensive target pharmacophore database. Nucleic Acids Res., 2017, 45(W1), W356-W360.
[http://dx.doi.org/10.1093/nar/gkx374] [PMID: 28472422]
[18]
Zhou, Y.; Zhang, Y.; Lian, X.; Li, F.; Wang, C.; Zhu, F.; Qiu, Y.; Chen, Y. Therapeutic target database update 2022: Facilitating drug discovery with enriched comparative data of targeted agents. Nucleic Acids Res., 2022, 50(D1), D1398-D1407.
[http://dx.doi.org/10.1093/nar/gkab953] [PMID: 34718717]
[19]
Davis, A.P.; Grondin, C.J.; Johnson, R.J.; Sciaky, D.; Wiegers, J.; Wiegers, T.C.; Mattingly, C.J. Comparative Toxicogenomics Database (CTD): Update 2021. Nucleic Acids Res., 2021, 49(D1), D1138-D1143.
[http://dx.doi.org/10.1093/nar/gkaa891] [PMID: 33068428]
[20]
UniProt: A worldwide hub of protein knowledge. Nucleic Acids Res., 2019, 47(D1), D506-D515.
[http://dx.doi.org/10.1093/nar/gky1049] [PMID: 30395287]
[21]
Rappaport, N.; Twik, M.; Plaschkes, I.; Nudel, R.; Iny Stein, T.; Levitt, J.; Gershoni, M.; Morrey, C.P.; Safran, M.; Lancet, D. MalaCards: An amalgamated human disease compendium with diverse clinical and genetic annotation and structured search. Nucleic Acids Res., 2017, 45(D1), D877-D887.
[http://dx.doi.org/10.1093/nar/gkw1012] [PMID: 27899610]
[22]
Tang, Z.; Li, C.; Kang, B.; Gao, G.; Li, C.; Zhang, Z. GEPIA: A web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res., 2017, 45(W1), W98-W102.
[http://dx.doi.org/10.1093/nar/gkx247] [PMID: 28407145]
[23]
Szklarczyk, D.; Gable, A.L.; Nastou, K.C.; Lyon, D.; Kirsch, R.; Pyysalo, S.; Doncheva, N.T.; Legeay, M.; Fang, T.; Bork, P.; Jensen, L.J.; von Mering, C. The STRING database in 2021: Customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res., 2021, 49(D1), D605-D612.
[http://dx.doi.org/10.1093/nar/gkaa1074] [PMID: 33237311]
[24]
Franz, M.; Rodriguez, H.; Lopes, C.; Zuberi, K.; Montojo, J.; Bader, G.D.; Morris, Q. GeneMANIA update 2018. Nucleic Acids Res., 2018, 46(W1), W60-W64.
[http://dx.doi.org/10.1093/nar/gky311] [PMID: 29912392]
[25]
Xu, X.; Zhu, C.; Wang, Q.; Zhu, X.; Zhou, Y. Identifying vital nodes in complex networks by adjacency information entropy. Sci. Rep., 2020, 10(1), 2691.
[http://dx.doi.org/10.1038/s41598-020-59616-w] [PMID: 32060330]
[26]
Ghosh, S.; Mukherjee, S.; Sengupta, N.; Roy, A.; Dey, D.; Chakraborty, S.; Chattopadhyay, D.; Banerjee, A.; Basu, A. Network analysis reveals common host protein/s modulating pathogenesis of neurotropic viruses. Sci. Rep., 2016, 6(1), 32593.
[http://dx.doi.org/10.1038/srep32593] [PMID: 27581498]
[27]
Tang, Y.; Li, M.; Wang, J.; Pan, Y.; Wu, F.X. CytoNCA: A cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Biosystems, 2015, 127, 67-72.
[http://dx.doi.org/10.1016/j.biosystems.2014.11.005] [PMID: 25451770]
[28]
Jin, Z.; Sato, Y.; Kawashima, M.; Kanehisa, M. KEGG tools for classification and analysis of viral proteins. Protein Sci., 2023, 32(12), e4820.
[http://dx.doi.org/10.1002/pro.4820] [PMID: 37881892]
[29]
Bu, D.; Luo, H.; Huo, P.; Wang, Z.; Zhang, S.; He, Z.; Wu, Y.; Zhao, L.; Liu, J.; Guo, J.; Fang, S.; Cao, W.; Yi, L.; Zhao, Y.; Kong, L. KOBAS-i: Intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Res., 2021, 49(W1), W317-W325.
[http://dx.doi.org/10.1093/nar/gkab447] [PMID: 34086934]
[30]
Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The protein data bank. Nucleic Acids Res., 2000, 28(1), 235-242.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID: 10592235]
[31]
Laskowski, R.A.; Swindells, M.B. LigPlot+: Multiple ligand-protein interaction diagrams for drug discovery. J. Chem. Inf. Model., 2011, 51(10), 2778-2786.
[http://dx.doi.org/10.1021/ci200227u] [PMID: 21919503]
[32]
Ganbold, M.; Barker, J.; Ma, R.; Jones, L.; Carew, M. Cytotoxicity and bioavailability studies on a decoction of Oldenlandia diffusa and its fractions separated by HPLC. J. Ethnopharmacol., 2010, 131(2), 396-403.
[http://dx.doi.org/10.1016/j.jep.2010.07.014] [PMID: 20633624]
[33]
Ali, R.; Tabrez, S.; Rahman, F.; Alouffi, A.S.; Alshehri, B.M.; Alshammari, F.A.; Alaidarous, M.A.; Banawas, S.; Dukhyil, A.A.B.; Rub, A. Antileishmanial evaluation of bark methanolic extract of Acacia nilotica: In vitro and in silico studies. ACS Omega, 2021, 6(12), 8548-8560.
[http://dx.doi.org/10.1021/acsomega.1c00366] [PMID: 33817515]
[34]
Zhu, D.C.; Pan, R.B.; Wang, Q. Research on the mechanisms of inhibiting effects of the Aqueous Extract of Hedyotis diffusa Willd on CEM cells. LISHIZHEN MEDICINE AND MATERIA MEDICA RESEARCH., 2014, 25(4), 827-829.
[35]
Ivanova, L.; Tammiku-Taul, J.; García-Sosa, A.T.; Sidorova, Y.; Saarma, M.; Karelson, M. Molecular dynamics simulations of the interactions between glial cell line-derived neurotrophic factor family receptor GFRα1 and small-molecule ligands. ACS Omega, 2018, 3(9), 11407-11414.
[http://dx.doi.org/10.1021/acsomega.8b01524] [PMID: 30320260]
[36]
Cheung, H.Y.; Cheung, S.H.; Law, M.L.; Lai, W.P. Simultaneous determination of key bioactive components in Hedyotis diffusa by capillary electrophoresis. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 2006, 834(1-2), 195-198.
[http://dx.doi.org/10.1016/j.jchromb.2006.02.007] [PMID: 16516568]
[37]
Kiraz, Y.; Adan, A.; Kartal Yandim, M.; Baran, Y. Major apoptotic mechanisms and genes involved in apoptosis. Tumour Biol., 2016, 37(7), 8471-8486.
[http://dx.doi.org/10.1007/s13277-016-5035-9] [PMID: 27059734]
[38]
Prokocimer, M.; Molchadsky, A.; Rotter, V. Dysfunctional diversity of p53 proteins in adult acute myeloid leukemia: Projections on diagnostic workup and therapy. Blood, 2017, 130(6), 699-712.
[http://dx.doi.org/10.1182/blood-2017-02-763086] [PMID: 28607134]
[39]
Fleischmann, M.; Schnetzke, U.; Hochhaus, A.; Scholl, S. Management of acute myeloid leukemia: Current treatment options and future perspectives. Cancers (Basel), 2021, 13(22), 5722.
[http://dx.doi.org/10.3390/cancers13225722] [PMID: 34830877]

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