Abstract
Globally, breast cancer is one of the major cancers in females. The incident rates are increasing in recent years, particularly in developed countries. However, the lowest survival rates are found in less developed countries, because of the lack of specific symptoms at an early stage, inadequate diagnostic equipment, and lesser treatment facilities. Therefore, the development of a new cancer therapeutic approach remains the most challenging area in the medical field. Naturally derived products play a significant role in the discovery of novel drugs. It can be a potential treatment option for cancers. In this study, 3D (three-dimensional) structures of breast tumor cell proteins like p53 (a cellular cancer antigen), NF-kB (nuclear factor kappa B)-p105 subunits, and addressin, also known as MAdCAM-1 (mucosal addressin cell adhesion molecule 1) were generated, and their binding affinity with glycyrrhizin was determined through local docking. The proteins were constructed by SWISS-MODEL, and their physiochemical characters were assessed by ExPASy’s ProtParam Proteomics server. After that, they were validated by PROCHECK, ERRAT, and Verify 3D programs. Lastly, the protein structures were docked successfully with glycyrrhizin using BSP-SLIM server. The binding energy between glycyrrhizin and p53, NF-kB-p105 subunits, and MAdCAM-1 were − 4.040, −5.127, and − 5.251 kcal/mol, respectively. The MAdCAM-1 had the strongest bond with glycyrrhizin, due to its lowest binding energy. Glycyrrhizin can be a potential drug candidate for cancer treatment. Thus, this protein model can further be validated in laboratory experiments to study its mechanisms of action.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akhtar MS, Swamy MK (eds) (2018) Anticancer plants: properties and application. Springer International, Singapore
Ali MS, Altaf M, Al-Lohedan HA (2017) Green synthesis of biogenic silver nanoparticles using Solanum tuberosum extract and their interaction with human serum albumin: Evidence of “corona” formation through a multi-spectroscopic and molecular docking analysis. J Photochem Photobiol B Biol 173:108–119
Ashwini S, Varkey SP, Shantaram M (2017) In Silico docking of polyphenolic compounds against Caspase 3-HeLa cell line protein. Int J Drug Dev Res 9:28–32
Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, Kiefer F, Cassarino TG, Bertoni M, Bordoli L, Schwede T (2014) SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res W1:W252–W258
Capua CJ, Hopson NP, Stewart CMM, Johnston GR, Neill KLO, Schaalje GB, Lee CM, Booth GM (2010) Cytotoxicity of Atriplex confertifolia. J Toxicol 1155:1–7
Chen H, Yao K, Nadas J, Bode AM, Malakhova M, Oi N, Li H, Lubet RA, Dong Z (2012) Prediction of molecular targets of cancer preventing flavonoid compounds using computational methods. PLoS One 7(5):e38261
Chiang AP, Butte AJ (2009) Systematic evaluation of drug-disease relationships to identify leads for novel drug uses. Clin Pharmacol Ther 86:507–510
Colovos C, Yeates TO (1993) Verification of protein structures: patterns of non-bonded atomic interactions. Protein Sci 2:1511–1519
Costantini S, Colonna G, Facchiano AM (2008) ESBRI: a web server for evaluating salt bridges in proteins. Bioinformation 3:137–138
De AK, De M (2019) Functional and therapeutic applications of some important spices. In: Watson RR, Singh RB, Takahashi T (eds) The role of functional food security in global health. Academic Press, USA, pp 499–510
Delano WL (2001) The PyMOL molecular graphics system. http://www.pymol.org. Assessed on 15 July 2017
Eisenberg D, Luthy R, Bowie JU (1997) VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol 277:396–404
Elengoe A, Hamdan S (2018) Computational approach towards exploring interaction of target protein-phytocompounds in drug development for breast cancer. In: Akhtar MS, Swamy MK (eds) Anticancer plants: mechanisms and molecular interactions. Springer International, Singapore, pp 131–141
Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. In: Walker JM (ed) The proteomics protocols handbook. Humana Press, pp 571–607
George S, Bhalerao SV, Lidstone EA, Ahmad IS, Abbasi A, Cunningham BT, Watkin KL (2010) Cytotoxicity screening of Bangladeshi medicinal plant extracts on pancreatic cancer cells. BMC Complement Altern Med 10:1472–6882
Geourjon C, Deleage G (1995) SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Comput Appl Biosci 11:681–684
Green DR, Kroemer G (2004) The pathophysiology of mitochondrial cell death. Science 305:626–629
Hui SL, Yang Z (2012) BSP-SLIM: A blind low-resolution ligand-protein docking approach using theoretically predicted protein structures. Proteins 80:93–110
Jayaprakash P, Jayaprakashi K, Ashok K, Rajesh S (2018) In silico molecular docking of alginic acid and fucoidan compound present in S. Wightii against apoptotic proteins (caspase-3, caspase-9 and β -actin). Int J Biol Pharmacy Allied Sci 78(8):1551–1565
Jayaram B (2014) Active site prediction server. http://www.scfbio-iitd.res.in/dock/ActiveSite.jsp. Assessed on 10 July 2017
Khan MK, Ansari IA, Khan MS, Arif JM (2013) Dietary phytochemicals as potent chemotherapeutic agents against breast cancer: inhibition of NF-κB pathway via molecular interactions in rel homology domain of its precursor protein p105. Pharmacogn Mag (33):51
Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereo chemical quality of protein structures. J Appl Crystallogr 26:283–291
Meng XY, Zhang HX, Mezei M, Cui M (2011) Molecular docking: a powerful approach for structure-based drug discovery. Curr Comput Aided Drug Des 7:146–157
Newman DJ, Cragg GM (2012) Natural products as sources of new drugs over the 30 years from 1981–2010. J Nat Prod 75:311–335
Prabi LG (1998) Color protein sequence analysis. https://npsaprabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_color.html. Assessed 1 July 2017
Pushpalatha R, Selvamuthukumar S, Kilimozhi D (2017) Comparative in silico docking analysis of curcumin and resveratrol on breast cancer proteins and their synergistic effect on MCF-7 cell line. J Young Pharmacists 9(4):480
Ramos-Tovar E, Muriel P (2019) Phytotherapy for the liver. In: Watson RR, Preedy VR (eds) Dietary interventions in liver disease. Academic Press, USA, pp 101–121. https://doi.org/10.1016/B978-0-12-814466-4.00009-4
Ravichandra VD, Ramesh C, Swamy MK, Purushotham B, Rudramurthy GR (2018) Anticancer plants: chemistry, pharmacology and potential applications. In: Akhtar MS, Swamy MK (eds) Anticancer plants: properties and applications, vol 1. Springer International, Singapore, pp 485–515
Roy S, Maheshwari N, Chauhan R, Sen NK, Sharma A (2011) Structure prediction and functional characterization of secondary metabolite proteins of Ocimum. Bioinformation 6:315–319
Roy N, Davis S, Narayanankutty A, Nazeem P, Babu T, Abida P, Valsala P, Raghavamenon AC (2016) Garlic phytocompounds possess anticancer activity by specifically targeting breast cancer biomarkers-an in silico study. Asian Pac J Cancer Prev 17(6):2883–2888
Santosh S, Rajagopalan MD, Pallavi BA, Rudramurthy GR, Rajashekar V, Sridhar KA, Swamy MK (2018) Cancer therapies: current scenario, management, and safety aspects. In: Akhtar MS, Swamy MK (eds) Anticancer plants: clinical trials and nanotechnology. Springer, Singapore, pp 1–25
Swamy MK, Arumugam G, Kaur R, Ghasemzadeh A, Yusoff MM, Sinniah UR (2017) GC-MS based metabolite profiling, antioxidant and antimicrobial properties of different solvent extracts of Malaysian Plectranthus amboinicus Leaves. Evid Based Compl Altern Med 2017:10. https://doi.org/10.1155/2017/1517683
Wallner B, Elofsson A (2003) Can correct protein models be identified? Protein Sci 12:1073–1086
WHO (2013) Global Health Estimates. http://www.who.int/cancer/detection/breastcancer/en/index1.html. Assessed on 21 May 2017
Wiederstein M, Sippl M (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407–W410
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Supramaniam, G., Elengoe, A. (2020). In Silico Molecular Docking of Glycyrrhizin and Breast Cancer Cell Line Proteins. In: Swamy, M. (eds) Plant-derived Bioactives. Springer, Singapore. https://doi.org/10.1007/978-981-15-2361-8_26
Download citation
DOI: https://doi.org/10.1007/978-981-15-2361-8_26
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-2360-1
Online ISBN: 978-981-15-2361-8
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)