In silico design of two novel fusion proteins, p28-IL-24 and p28-M4, targeted to breast cancer cells
Abstract
Background and purpose: An anticancer peptide P28, has shown to be cytolethal on various cancer cells including breast cancer. Moreover, p28 can be also used as a targeting moiety in the structure of fusion proteins. IL-24 (or its truncated form, M4) is a cytokine with anticancer activity against a wide range of tumor cells. We aimed at production of a fusion protein consisted of p28 and either IL-24 or M4 to target breast cancer. However, selection of a proper linker to join the two moieties without intervening each other’s function is a key factor in the construction of fusion proteins. In the present study, the impact of different linkers on construction of the two chimeric proteins (p28-IL-24 and p28-M4) was assessed in silico.
Experimental approach: After selection of some linkers with different lengths and characteristics, a small library of the chimeric proteins was created and assessed. Furthermore, following selection of the most suitable linker, the three-dimensional structures and dynamic behavior of both fusion proteins were evaluated by homology modeling and molecular dynamic simulation, respectively.
Findings / Results: Based on the results, a rigid linker having the peptide sequences of AEAAAKEAAAKA showed highest freedom of action for both moieties.
Conclusion and implications: Between the p28-IL-24 and p28-M4 fusion proteins, the former showed better stability as well as solubility and might show stronger anticancer effects in vitro and in vivo, because its peptide moieties showed to exert their activities freely.
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Shafiee F, Aucoin MG, Jahanian-Najafabadi A. Targeted diphtheria toxin-based therapy: a review article. Front Microbiol. 2019;10:2340-2362.
DOI: 10.3389/fmicb.2019.02340.
Thun MJ, DeLancey JO, Center MM, Jemal A, Ward EM. The global burden of cancer: priorities for prevention. Carcinogenesis. 2010;31(1):100-110. DOI: 10.1093/carcin/bgp263.
Torre LA, Siegel RL, Ward EM, Jemal A. Global cancer incidence and mortality rates and trends-an update. Cancer Epidemiol Biomarkers Prev. 2016;25(1):16-27.
DOI: 10.1158/1055-9965.EPI-15-0578.
Saini RK, Chouhan R, Bagri LP, Bajpai AK. Strategies of targeting tumors and cancers. J Can Res Updates. 2012;1(1):129-152.
DOI: 10.6000/1929-2279.2012.01.01.19.
Dong X, Mumper RJ. Nanomedicinal strategies to treat multidrug-resistant tumors: current progress. Nanomedicine (Lond). 2010;5(4):597-615.
DOI: 10.2217/nnm.10.35.
Chakraborty S, Rahman T. The difficulties in cancer treatment. Ecancermedicalscience. 2012;6:ed16,1-6. DOI: 10.3332/ecancer.2012.ed16.
Craik DJ, Fairlie DP, Liras S, Price D. The future of peptide‐based drugs. Chem Biol Drug Des. 2013;81(1):136-147.
DOI: 10.1111/cbdd.12055.
Thundimadathil J. Cancer treatment using peptides: current therapies and future prospects. J Amino Acids. 2012; 2012:967347-967359.
DOI: 10.1155/2012/967347.
Punj V, Bhattacharyya S, Saint-Dic D, Vasu C, Cunningham EA, Graves J, et al. Bacterial cupredoxin azurin as an inducer of apoptosis and regression in human breast cancer. Oncogene. 2004;23(13):2367-2378.
DOI: 10.1038/sj.onc.1207376.
Yamada T, Fialho AM, Punj V, Bratescu L, Gupta TK, Chakrabarty AM. Internalization of bacterial redox protein azurin in mammalian cells: entry domain and specificity. Cell Microbiol. 2005;7(10):1418-1431.
DOI: 10.1111/j.1462-5822.2005.00567.x.
Soleimani M, Sadeghi HM, Jahanian-Najafabadi A. A Bi-functional targeted P28-NRC chimeric protein with enhanced cytotoxic effects on breast cancer cell lines. Iran J Pharm Res. 2019;18(2):735-744.
DOI: 10.22037/ijpr.2019.2392.
Yamada T, Das Gupta TK, Beattie CW. p28-Mediated activation of p53 in G2-M phase of the cell cycle enhances the efficacy of DNA damaging and antimitotic chemotherapy. Cancer Res. 2016;76(8):2354-2365.
DOI: 10.1158/0008-5472.CAN-15-2355.
Persaud L, De Jesus D, Brannigan O, Richiez-Paredes M, Huaman J, Alvarado G, et al. Mechanism of action and applications of interleukin 24 in immunotherapy. Int J Mol Sci. 2016;17(6):869-881.
DOI: 10.3390/ijms17060869.
Pourhadi M, Jamalzade F, Jahanian-Najafabadi A, Shafiee F. Expression, purification, and cytotoxic evaluation of IL24-BR2 fusion protein. Res Pharm Sci. 2019;14(4):320-328.
DOI: 10.4103/1735-5362.263556.
Schindler C, Levy DE, Decker T. JAK-STAT signaling: from interferons to cytokines. J Biol Chem. 2007;282(28):20059-20063.
DOI: 10.1074/jbc.R700016200.
Sauane M, Gopalkrishnan RV, Sarkar D, Su ZZ, Lebedeva IV, Dent P, et al. MDA-7/IL-24: novel cancer growth suppressing and apoptosis inducing cytokine. Cytokine Growth Factor Rev. 2003;14(1):35-51.
DOI: 10.1016/s1359-6101(02)00074-6.
Dent P, Yacoub A, Hamed HA, Park MA, Dash R, Bhutia SK, et al. The development of MDA-7/IL-24 as a cancer therapeutic. Pharmacol Ther. 2010;128(2):375-384. DOI: 10.1016/j.pharmthera.2010.08.001.
Fisher P, Gupta P. MDA-7 protein variants having antiproliferative activity. Google Patents WO/2006/060680, 2006.
Dash R, Bhutia SK, Azab B, Su ZZ, Quinn BA, Kegelmen TP, et al. Mda-7/IL-24: a unique member of the IL-10 gene family promoting cancer-targeted toxicity. Cytokine Growth Factor Rev. 2010;21(5):381-391.
DOI: 10.1016/j.cytogfr.2010.08.004.
Chen X, Zaro JL, Shen WC. Fusion protein linkers: property, design and functionality. Adv Drug Deliv Rev. 2013;65(10):1357-1369. DOI: 10.1016/j.addr .2012.09.039.
Soleimani M, Mahnam K, Mirmohammad-Sadeghi H, Sadeghi-Aliabadi H, Jahanian-Najafabadi A. Theoretical design of a new chimeric protein for the treatment of breast cancer. Res Pharm Sci. 2016;11(3):187-199.
Karplus M, Kuriyan J. Molecular dynamics and protein function. Proc Natl Acad Sci U S A. 2005;102(19):6679-6685.
DOI: 10.1073/pnas.0408930102.
Mahnam K, Saffar B, Mobini-Dehkordi M, Fassihi A, Mohammadi A. Design of a novel metal binding peptide by molecular dynamics simulation to sequester Cu and Zn ions. Res Pharm Sci. 2014;9(1):69-82.
Wadood A, Ahmed N, Shah L, Ahmad A, Hassan H, Shams S. In-silico drug design: an approach which revolutionarised the drug discovery process. OA drug design & delivery. 2013;1(1):3-7.
DOI: 10.13172/2054-4057-1-1-1119.
Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J Mol Graph. 1996;14(1):33-38. DOI: 10.1016/0263-7855(96)00018-5.
Eswar N, Webb B, Marti‐Renom MA, Madhusudhan MS, Eramian D, Shen MY, et al. Comparative protein structure modeling using Modeller. Curr Protoc Bioinformatics. 2006;Chapter 5:Unit-5.6.(1-47). DOI: 10.1002/0471250953.bi0506s15.
Eswar N, Eramian D, Webb B, Shen MY, Sali A. Protein Structure Modeling with MODELLER. In: Kobe B, Guss M, Huber T, editors. Structural Proteomics. Methods in Molecular Biology™, Vol 426. Humana Press; 2008. pp. 145-159.
DOI: 10.1007/978-1-60327-058-8-8.
Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35:407-410.
DOI: 10.1093/nar/gkm290.
Hooft RWW, Sander C, Vriend G. Objectively judging the quality of a protein structure from a Ramachandran plot. Bioinformatics. 1997;13(4):425-430.
DOI: 10.1093/bioinformatics/ 13.4.425.
Pronk S, Páll S, Schulz R, Larsson P, Bjelkmar P, Apostolov R, et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics. 2013;29(7):845-854.
DOI: 10.1093/bioinformatics/btt055.
Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJ. GROMACS: fast, flexible, and free. J Comput Chem. 2005;26(16):1701-1718. DOI: 10.1002/jcc.20291.
Yu K, Liu C, Kim BG, Lee DY. Synthetic fusion protein design and applications. Biotechnol Adv. 2015;33(1):155-164.
DOI: 10.1016/j.biotechadv.2014.11.005.
Rizk M, Antranikian G, Elleuche S. End-to-end gene fusions and their impact on the production of multifunctional biomass degrading enzymes. Biochem Biophys Res Commun. 2012;428(1):1-5. DOI: 10.1016/j.bbrc.2012.09.142.
Zhao HL, Yao XQ, Xue C, Wang Y, Xiong XH, Liu ZM. Increasing the homogeneity, stability and activity of human serum albumin and interferon-α2b fusion protein by linker engineering. Protein Expr Purif. 2008;61(1):73-77.
DOI: 10.1016/j.pep.2008.04.013.
DasGupta D, Kaushik R, Jayaram B. From Ramachandran maps to tertiary structures of proteins. J Phys Chem B. 2015;119(34):11136-11145.
DOI: 10.1021/acs.jpcb.5b02999.
Shamriz S, Ofoghi H, Moazami N. Effect of linker length and residues on the structure and stability of a fusion protein with malaria vaccine application. Comput Biol Med. 2016;76:24-29.
DOI: 10.1016/j.compbiomed.2016.06.015.
Fahimi H, Sadeghizadeh M, Mohammadipour M. In silico analysis of an envelope domain III-based multivalent fusion protein as a potential dengue vaccine candidate. Clin Exp Vaccine Res. 2016;5(1):41-49.
DOI: 10.7774/cevr.2016.5.1.41.
Ahmad A, Javed MR, Rao AQ, Khan MAU, Ahad A, Salah UD, et al. In-silico determination of insecticidal potential of Vip3Aa-Cry1Ac fusion protein against Lepidopteran targets using molecular docking. Front Plant Sci. 2015;6:1081-1088.
DOI: 10.3389/fpls.2015.01081.
Hospital A, Goñi JR, Orozco M, Gelpí JL. Molecular dynamics simulations: advances and applications. Adv Appl Bioinform Chem. 2015;8:37-47.
DOI: 10.2147/AABC.S70333.
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