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Current Computer-Aided Drug Design

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ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

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Research Article

Identification of Small Inhibitors for Human Metadherin, an Oncoprotein, through in silico Approach

Author(s): Arif Ali Khattak, Ayaz Ahmad*, Haider Ali Khattak and Muhammad Zafar Irshad Khan*

Volume 19, Issue 4, 2023

Published on: 30 January, 2023

Page: [278 - 287] Pages: 10

DOI: 10.2174/1573409919666230110112356

Price: $65

Abstract

Aims: Cancer is a disease that takes lives of thousands of people each year. There are more than 100 different types of cancers known to man. This fatal disease is one of the leading causes of death today.

Background: Astrocyte elevated gene-1(AEG-1)/Metadherin (MTDH) activates multiple oncogenic signaling pathways and leads to different types of cancers. MTDH interacting with staphylococcal nuclease domain containing 1(SND1) supports the survival and growth of mammary epithelial cells under oncogenic conditions.

Objective: Silencing MTDH or SND1 individually or disrupting their interaction compromises the tumorigenic potential of tumor-initiating cells. The aim of our present study was to investigate novel interactions of staphylococcal nuclease domain containing 1 (SND1) binding domain of AEG-1/MTDH with different lead compounds through molecular docking approach using MOE software.

Methods: Molecular docking was done by docking the ChemBridge database against important residues of MTDH involved in interaction with SND1. After docking the whole ChemBridge database, the top 200 interactive compounds were selected based on docking scores. After applying Lipinski’s rule, all the remaining chosen compounds were studied on the basis of binding affinity, binding energy, docking score and protein-ligand interactions. Finally, 10 compounds showing multiple interactions with different amino acid residues were selected as the top interacting compounds.

Results: Three compounds were selected for simulation studies after testing these compounds using topkat toxicity and ADMET studies. The simulation study indicated that compound 32538601 is a lead compound for inhibiting MTDH-SND1 complex formation.

Conclusion: These novels, potent inhibitors of MTDH-SND1 complex can ultimately help us in controlling cancer up to some extent.

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[1]
Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin 2011; 61(2): 69-90.
[http://dx.doi.org/10.3322/caac.20107] [PMID: 21296855]
[2]
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021; 71(3): 209-49.
[http://dx.doi.org/10.3322/caac.21660] [PMID: 33538338]
[3]
Organization WH. National cancer control programmes: Policies and managerial guidelines. World Health Organization 2002.
[4]
Schneider KA. Counseling about cancer: Strategies for genetic counseling. John Wiley & Sons 2011.
[http://dx.doi.org/10.1002/9781118119921]
[5]
Bahls C, Fogarty M. Reining in a killer disease. Scientist 2002; 16(11): 16-8.
[6]
Gibbs WW. Untangling the roots of cancer. Sci Am 2003; 289(1): 56-65.
[http://dx.doi.org/10.1038/scientificamerican0703-56] [PMID: 12840947]
[7]
Kling J. Put the blame on methylation. Scientist 2003; 17(12): 27-8.
[8]
McCook A. Lifting the Screen. Sci Am 2002; 286(6): 16-7.
[http://dx.doi.org/10.1038/scientificamerican0602-16]
[9]
Vats TS, Emami A. Oncogenes: Present status. Indian J Pediatr 1993; 60(2): 193-201.
[http://dx.doi.org/10.1007/BF02822176] [PMID: 8244494]
[10]
Bell JC. Oncogenes. Cancer Lett 1988; 40(1): 1-5.
[http://dx.doi.org/10.1016/0304-3835(88)90255-8] [PMID: 3285992]
[11]
Su Z, Kang D, Chen Y, et al. Identification and cloning of human astrocyte genes displaying elevated expression after infection with HIV-1 or exposure to HIV-1 envelope glycoprotein by rapid subtraction hybridization, RaSH. Oncogene 2002; 21(22): 3592-602.
[http://dx.doi.org/10.1038/sj.onc.1205445] [PMID: 12032861]
[12]
Su Z, Chen Y, Kang D, et al. Customized rapid subtraction hybridization (RaSH) gene microarrays identify overlapping expression changes in human fetal astrocytes resulting from human immunodeficiency virus-1 infection or tumor necrosis factor-α treatment. Gene 2003; 306: 67-78.
[http://dx.doi.org/10.1016/S0378-1119(03)00404-9] [PMID: 12657468]
[13]
Kang D, Su Z, Sarkar D, Emdad L, Volsky DJ, Fisher PB. Cloning and characterization of HIV-1-inducible astrocyte elevated gene-1, AEG-1. Gene 2005; 353(1): 8-15.
[http://dx.doi.org/10.1016/j.gene.2005.04.006] [PMID: 15927426]
[14]
Brown DM, Ruoslahti E. Metadherin, a cell surface protein in breast tumors that mediates lung metastasis. Cancer Cell 2004; 5(4): 365-74.
[http://dx.doi.org/10.1016/S1535-6108(04)00079-0] [PMID: 15093543]
[15]
Sutherland HGE, Lam YW, Briers S, Lamond AI, Bickmore WA. 3D3/lyric: A novel transmembrane protein of the endoplasmic reticulum and nuclear envelope, which is also present in the nucleolus. Exp Cell Res 2004; 294(1): 94-105.
[http://dx.doi.org/10.1016/j.yexcr.2003.11.020] [PMID: 14980505]
[16]
Emdad L, Sarkar D, Su ZZ, et al. Astrocyte elevated gene-1: Recent insights into a novel gene involved in tumor progression, metastasis and neurodegeneration. Pharmacol Ther 2007; 114(2): 155-70.
[http://dx.doi.org/10.1016/j.pharmthera.2007.01.010] [PMID: 17397930]
[17]
Thirkettle HJ, Girling J, Warren AY, et al. LYRIC/AEG-1 is targeted to different subcellular compartments by ubiquitinylation and intrinsic nuclear localization signals. Clin Cancer Res 2009; 15(9): 3003-13.
[http://dx.doi.org/10.1158/1078-0432.CCR-08-2046] [PMID: 19383828]
[18]
Yoo BK, Emdad L, Lee SG, et al. Astrocyte elevated gene-1 (AEG-1): A multifunctional regulator of normal and abnormal physiology. Pharmacol Ther 2011; 130(1): 1-8.
[http://dx.doi.org/10.1016/j.pharmthera.2011.01.008] [PMID: 21256156]
[19]
Yoo BK, Santhekadur PK, Gredler R, et al. Increased RNA-induced silencing complex (RISC) activity contributes to hepatocellular carcinoma. Hepatology 2011; 53(5): 1538-48.
[http://dx.doi.org/10.1002/hep.24216] [PMID: 21520169]
[20]
Santhekadur PK, Kumar DP. RISC assembly and post-transcriptional gene regulation in hepatocellular carcinoma. Genes Dis 2020; 7(2): 199-204.
[http://dx.doi.org/10.1016/j.gendis.2019.09.009] [PMID: 32215289]
[21]
Shen M, Wei Y, Kim H, et al. Small-molecule inhibitors that disrupt the MTDH-SND1 complex suppress breast cancer progression and metastasis. Nat Can 2021; 3(1): 43-59.
[http://dx.doi.org/10.1038/s43018-021-00279-5] [PMID: 35121987]
[22]
Tan H, Zhu G, She L, et al. MiR-98 inhibits malignant progression via targeting MTDH in squamous cell carcinoma of the head and neck. Am J Cancer Res 2017; 7(12): 2554-65.
[PMID: 29312808]
[23]
Kapetanovic IM. Computer-aided drug discovery and development (CADDD): In silico chemico-biological approach. Chem Biol Interact 2008; 171(2): 165-76.
[http://dx.doi.org/10.1016/j.cbi.2006.12.006] [PMID: 17229415]
[24]
Wang B, Ekins S. Computer applications in pharmaceutical research and development. John Wiley & Sons 2006.
[25]
Hann MM, Oprea TI. Pursuing the leadlikeness concept in pharmaceutical research. Curr Opin Chem Biol 2004; 8(3): 255-63.
[http://dx.doi.org/10.1016/j.cbpa.2004.04.003] [PMID: 15183323]
[26]
Jain AN. Surflex: Fully automatic flexible molecular docking using a molecular similarity-based search engine. J Med Chem 2003; 46(4): 499-511.
[http://dx.doi.org/10.1021/jm020406h] [PMID: 12570372]
[27]
Jain AN. Virtual screening in lead discovery and optimization. Curr Opin Drug Discov Devel 2004; 7(4): 396-403.
[PMID: 15338948]
[28]
Kumar N, Hendriks BS, Janes KA, de Graaf D, Lauffenburger DA. Applying computational modeling to drug discovery and development. Drug Discov Today 2006; 11(17-18): 806-11.
[http://dx.doi.org/10.1016/j.drudis.2006.07.010] [PMID: 16935748]
[29]
Oprea TI, Matter H. Integrating virtual screening in lead discovery. Curr Opin Chem Biol 2004; 8(4): 349-58.
[http://dx.doi.org/10.1016/j.cbpa.2004.06.008] [PMID: 15288243]
[30]
Roche O, Guba W. Computational chemistry as an integral component of lead generation. Mini Rev Med Chem 2005; 5(7): 677-83.
[http://dx.doi.org/10.2174/1389557054368826] [PMID: 16026314]
[31]
Stahl M, Guba W, Kansy M. Integrating molecular design resources within modern drug discovery research: The Roche experience. Drug Discov Today 2006; 11(7-8): 326-33.
[http://dx.doi.org/10.1016/j.drudis.2006.02.008] [PMID: 16580974]
[32]
Stoermer M. Current status of virtual screening as analysed by target class. Med Chem 2006; 2(1): 89-112.
[http://dx.doi.org/10.2174/157340606775197750] [PMID: 16787359]
[33]
Jones G, Willett P. Docking small-molecule ligands into active sites. Curr Opin Biotechnol 1995; 6(6): 652-6.
[http://dx.doi.org/10.1016/0958-1669(95)80107-3] [PMID: 8527835]
[34]
Kuntz ID, Meng EC, Shoichet BK. Structure-based molecular design. Acc Chem Res 1994; 27(5): 117-23.
[http://dx.doi.org/10.1021/ar00041a001]
[35]
Lengauer T, Rarey M. Computational methods for biomolecular docking. Curr Opin Struct Biol 1996; 6(3): 402-6.
[http://dx.doi.org/10.1016/S0959-440X(96)80061-3] [PMID: 8804827]
[36]
Lybrand TP. Ligand-protein docking and rational drug design. Curr Opin Struct Biol 1995; 5(2): 224-8.
[http://dx.doi.org/10.1016/0959-440X(95)80080-8] [PMID: 7648325]
[37]
Rosenfeld R, Vajda S, DeLisi C. Flexible docking and design. Annu Rev Biophys Biomol Struct 1995; 24(1): 677-700.
[http://dx.doi.org/10.1146/annurev.bb.24.060195.003333] [PMID: 7663131]
[38]
Scholz C, Knorr S, Hamacher K, Schmidt B. DOCKTITE-a highly versatile step-by-step workflow for covalent docking and virtual screening in the molecular operating environment. J Chem Inf Model 2015; 55(2): 398-406.
[http://dx.doi.org/10.1021/ci500681r] [PMID: 25541749]
[39]
Labute P. The generalized born/volume integral implicit solvent model: Estimation of the free energy of hydration using London dispersion instead of atomic surface area. J Comput Chem 2008; 29(10): 1693-8.
[http://dx.doi.org/10.1002/jcc.20933] [PMID: 18307169]
[40]
Wadood A, Riaz M, Uddin R, ul-Haq Z. In silico identification and evaluation of leads for the simultaneous inhibition of protease and helicase activities of HCV NS3/4A protease using complex based pharmacophore mapping and virtual screening. PLoS One 2014; 9(2): e89109.
[http://dx.doi.org/10.1371/journal.pone.0089109] [PMID: 24551230]
[41]
Ponnan P, Gupta S, Chopra M, et al. 2D-QSAR, docking studies, and in silico ADMET prediction of polyphenolic acetates as substrates for protein acetyltransferase function of glutamine synthetase of Mycobacterium tuberculosis. International Scholarly Research Notices 2013.
[42]
Gaur R, Cheema HS, Kumar Y, et al. In vitro antimalarial activity and molecular modeling studies of novel artemisinin derivatives. RSC Advances 2015; 5(59): 47959-74.
[http://dx.doi.org/10.1039/C5RA07697H]
[43]
Desmond molecular dynamics system DE Shaw research. New York 2017.
[44]
Emdad L, Das SK, Dasgupta S, Hu B, Sarkar D, Fisher PB. AEG-1/MTDH/LYRIC: Signaling pathways, downstream genes, interacting proteins, and regulation of tumor angiogenesis. Adv Cancer Res 2013; 120: 75-111.
[http://dx.doi.org/10.1016/B978-0-12-401676-7.00003-6] [PMID: 23889988]
[45]
Wan L, Kang Y. Pleiotropic roles of AEG-1/MTDH/LYRIC in breast cancer. Adv Cancer Res 2013; 120: 113-34.
[http://dx.doi.org/10.1016/B978-0-12-401676-7.00004-8] [PMID: 23889989]
[46]
Wan L, Lu X, Yuan S, et al. MTDH-SND1 interaction is crucial for expansion and activity of tumor-initiating cells in diverse oncogene- and carcinogen-induced mammary tumors. Cancer Cell 2014; 26(1): 92-105.
[http://dx.doi.org/10.1016/j.ccr.2014.04.027] [PMID: 24981741]
[47]
Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 2012; 64: 4-17.
[http://dx.doi.org/10.1016/j.addr.2012.09.019] [PMID: 11259830]

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