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Designing a new bispecific tandem single-chain variable fragment antibody against tumor necrosis factor-α and interleukin-23 using in silico studies for the treatment of rheumatoid arthritis

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Abstract

Rheumatoid arthritis disease is a chronic auto-immune inflammatory disease that mainly causes synovial joint inflammation and cartilage destruction. The tumor necrosis factor-α (TNF-α) is a pivotal cytokine that plays an important role in rheumatoid arthritis. The treatments focusing on a single cytokine inhibition are clinically able to produce meaningful responses in only about half of the treated patients due to multiple cytokines involved in this disease. In the present study, a bispecific tandem single-chain variable fragment was designed in order to suppress both human tumor necrosis factor-α and interleukin-23 (IL23) as a potential therapeutic drug candidate for this disease. To do so, at first, eight bispecific tandem single-chain variable fragment models were built against tumor necrosis factor-α and interleukin-23 cytokines with different domain orders by the homology modeling, and then 50 ns molecular dynamics simulation was performed for each one and then structural properties were exploited. The MD simulation results indicate the fact that the domains’ order strongly affects tandem single-chain variable fragment properties, and in overall, the fragment VLAIL23+Linker+VHAIL23+linker+VLATNF+Linker +VHATNF +His6 (VL and VH are light and heavy chain variable fragments and AIL23 and ATNF are anti-interleukin 23 and anti-tumor necrosis factor-α, respectively, and His6 is the six histidine) not only separated antibody domains accurately but also had better stability and solvation free energy. Therefore, this structure can be considered as an effective potential drug for rheumatoid arthritis. It is expected that the findings of this research could shed a light on the treatment approaches of the rheumatoid arthritis disease.

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Abbreviations

scFv:

Single-chain variable fragment (VL+Linker+VH)

taFv:

Tandem scFv (scFv+ML+scFv)

ML :

Middle linker connecting the two scFv

RA:

Rheumatoid arthritis

TNF-α:

Tumor necrosis factor-α

ATNF:

Anti-tumor necrosis factor-α

IL-23:

Interleukin-23

IL-23R:

Interleukin-23 receptor

AIL23:

Anti-interleukin-23

MD:

Molecular dynamics

RMSD:

Root mean square deviation

Rg:

Radius of gyration

SASA:

Solvent accessible surface area

CDR:

Complementarity determining region

BsAbs:

Bispecific antibodies

References

  1. Fischer JA, Hueber AJ, Wilson S, Galm M, Baum W, Kitson C et al (2015) Combined inhibition of tumor necrosis factor alpha and interleukin-17 as a therapeutic opportunity in rheumatoid arthritis: development and characterization of a novel bispecific antibody. Arthritis Rheum 67(1):51–62

    Article  CAS  Google Scholar 

  2. Silacci M, Lembke W, Woods R, Attinger-Toller I, Baenziger-Tobler N, Batey S et al (2015) Discovery and characterization of COVA322, a clinical-stage bispecific TNF/IL-17A inhibitor for the treatment of inflammatory diseases. mAbs 8(1):141–149

    Article  PubMed  PubMed Central  Google Scholar 

  3. McInnes IB, Buckley CD, Isaacs JD (2015) Cytokines in rheumatoid arthritis - shaping the immunological landscape. Nat Rev Rheumatol 12(1):63–68

    Article  PubMed  Google Scholar 

  4. Liu M, Xie M, Jiang S, Liu G, Li L, Liu D et al (2014) A novel bispecific antibody targeting tumor necrosis factor alpha and ED-B fibronectin effectively inhibits the progression of established collagen-induce arthritis. J Biotechnol 186:1–12

    Article  PubMed  Google Scholar 

  5. Rubbert-Roth A, Atzeni F, Masala IF, Caporali R, Montecucco C, Sarzi-Puttini P TNF inhibitors in rheumatoid arthritis and spondyloarthritis: are they the same? Autoimmun Rev 17(1):24–28

  6. Liu Z, Song L, Wang Y, Xu P, Guo X, Yang J et al (2018) A novel fusion protein attenuates collagen-induced arthritis by targeting interleukin 17A and tumor necrosis factor alpha. Int J Pharm 547(1–2):72–82

    Article  PubMed  CAS  Google Scholar 

  7. Sherlock JP, Taylor PC, Buckley CD (2015) The biology of IL-23 and IL-17 and their therapeutic targeting in rheumatic diseases. LWW:71–75

  8. Yang J, Sundrud MS, Skepner J, Yamagata T (2014) Targeting Th17 cells in autoimmune diseases. Trends Pharmacol Sci 35(10):493–500

    Article  PubMed  CAS  Google Scholar 

  9. Mateen S, Zafar A, Moin S, Khan AQ, Zubair S (2016) Understanding the role of cytokines in the pathogenesis of rheumatoid arthritis. Clin Chim Acta 455:161–171

    Article  PubMed  CAS  Google Scholar 

  10. Croxford AL, Kulig P, Becher B (2014) IL-12-and IL-23 in health and disease. Cytokine Growth Factor Rev 25(4):415–421

    Article  PubMed  CAS  Google Scholar 

  11. Wendling D (2008) Interleukin 23: a key cytokine in chronic inflammatory disease. Joint Bone Spine 75(5):517–519

    Article  PubMed  CAS  Google Scholar 

  12. Ratsimandresy RA, Duvallet E, Assier E, Semerano L, Delavallee L, Bessis N et al (2011) Active immunization against IL-23p19 improves experimental arthritis. Vaccine. 29(50):9329–9336

    Article  PubMed  CAS  Google Scholar 

  13. Guo YY, Wang NZ, Zhao S, Hou LX, Xu YB, Zhang N (2013) Increased interleukin-23 is associated with increased disease activity in patients with rheumatoid arthritis. 850–854

  14. Dalila AS, Mohd Said MS, Shaharir SS, Asrul AW, Low SF, Shamsul AS et al (2014 Jul) Interleukin-23 and its correlation with disease activity, joint damage, and functional disability in rheumatoid arthritis. Kaohsiung J Med Sci 30(7):337–342

    Article  PubMed  Google Scholar 

  15. Al Fadl EMA, Fattouh M, Allam AA (2013) High IL-23 level is a marker of disease activity in rheumatoid arthritis. Egypt J Immunol:85–92

  16. Thakur A, Huang M, Lum LG (2018) Bispecific antibody based therapeutics: strengths and challenges. Blood Rev 32(4):339–347

    Article  PubMed  CAS  Google Scholar 

  17. Spiess C, Zhai Q, Carter PJ (2015) Alternative molecular formats and therapeutic applications for bispecific antibodies. Mol Immunol 67(2 Pt A):95–106

    Article  PubMed  CAS  Google Scholar 

  18. Chan AC, Carter PJ (2010 May) Therapeutic antibodies for autoimmunity and inflammation. Nat Rev Immunol 10(5):301–316

    Article  PubMed  CAS  Google Scholar 

  19. Kontermann RE. Bispecific antibodies: springer 2011

    Book  Google Scholar 

  20. Chen X, Zaro JL, Shen WC (2013) Fusion protein linkers: property, design and functionality. Adv Drug Deliv Rev 65(10):1357–1369

    Article  PubMed  CAS  Google Scholar 

  21. Sela-Culang I, Kunik V, Ofran Y (2013) The structural basis of antibody-antigen recognition. Front Immunol 4:302

    Article  PubMed  PubMed Central  Google Scholar 

  22. Brzustewicz E, Bryl E (2015) The role of cytokines in the pathogenesis of rheumatoid arthritis--practical and potential application of cytokines as biomarkers and targets of personalized therapy. Cytokine. 76(2):527–536

    Article  PubMed  CAS  Google Scholar 

  23. 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 11(3):187–199

  24. Li Q, Ren G, Xu L, Wang Q, Qi J, Wang W et al (2014) Therapeutic efficacy of three bispecific antibodies on collagen-induced arthritis mouse model. Int Immunopharmacol 21(1):119–127

    Article  PubMed  Google Scholar 

  25. Qi J, Kan F, Ye X, Guo M, Zhang Y, Ren G et al (2012) A bispecific antibody against IL-1beta and IL-17A is beneficial for experimental rheumatoid arthritis. Int Immunopharmacol 14(4):770–778

    Article  PubMed  CAS  Google Scholar 

  26. Robert R, Juglair L, Lim EX, Ang C, Wang CJH, Ebert G et al A fully humanized IgG-like bispecific antibody for effective dual targeting of CXCR3 and CCR6. PLoS One 12(9):e0184278

  27. Yang Y, Zhang T, Cao H, Yu D, Zhang T, Zhao S et al (2017) The pharmacological efficacy of the anti-IL17 scFv and sTNFR1 bispecific fusion protein in inflammation mouse stimulated by LPS. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 92:905–912

    Article  CAS  Google Scholar 

  28. Jung K, Lee D, Lim HS, Lee SI, Kim YJ, Lee GM et al (2010) Double anti-angiogenic and anti-inflammatory protein Valpha targeting VEGF-A and TNF-alpha in retinopathy and psoriasis. J Biol Chem 286(16):14410–14418

    Article  Google Scholar 

  29. Choi BD, Kuan CT, Cai M, Archer GE, Mitchell DA, Gedeon PC et al (2013) Systemic administration of a bispecific antibody targeting EGFRvIII successfully treats intracerebral glioma. Proc Natl Acad Sci U S A 110(1):270–275

    Article  PubMed  CAS  Google Scholar 

  30. Dan Z, Tan Z, Xia H, Wu G (2013 Aug) Construction and expression of D-dimer and GPIIb/IIIa single-chain bispecific antibody. Experimental and therapeutic medicine 6(2):552–556

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Arndt C, Feldmann A, Koristka S, Cartellieri M, Dimmel M, Ehninger A et al (2014) Simultaneous targeting of prostate stem cell antigen and prostate-specific membrane antigen improves the killing of prostate cancer cells using a novel modular T cell-retargeting system. Prostate 74(13):1335–1346

    Article  PubMed  CAS  Google Scholar 

  32. Taki S, Kamada H, Inoue M, Nagano K, Mukai Y, Higashisaka K et al (2015) A novel bispecific antibody against human CD3 and ephrin receptor A10 for breast cancer therapy. PLoS One 10(12):e0144712

    Article  PubMed  PubMed Central  Google Scholar 

  33. Guettinger Y, Barbin K, Peipp M, Bruenke J, Dechant M, Horner H et al A recombinant bispecific single-chain fragment variable specific for HLA class II and Fc alpha RI (CD89) recruits polymorphonuclear neutrophils for efficient lysis of malignant B lymphoid cells. J Immunol 184(3):1210–1217

  34. Bruenke J, Fischer B, Barbin K, Schreiter K, Wachter Y, Mahr K et al (2004) A recombinant bispecific single-chain Fv antibody against HLA class II and FcgammaRIII (CD16) triggers effective lysis of lymphoma cells. Br J Haematol 125(2):167–179

    Article  PubMed  CAS  Google Scholar 

  35. Cheng M, Santich BH, Xu H, Ahmed M, Huse M, Cheung NK (2016) Successful engineering of a highly potent single-chain variable-fragment (scFv) bispecific antibody to target disialoganglioside (GD2) positive tumors. Oncoimmunology. 5(6):e1168557

    Article  PubMed  PubMed Central  Google Scholar 

  36. Yamamoto K, Trad A, Baumgart A, Huske L, Lorenzen I, Chalaris A et al (2012) A novel bispecific single-chain antibody for ADAM17 and CD3 induces T-cell-mediated lysis of prostate cancer cells. The Biochemical journal 445(1):135–144

  37. Stamova S, Cartellieri M, Feldmann A, Arndt C, Koristka S, Bartsch H et al (2011) Unexpected recombinations in single chain bispecific anti-CD3-anti-CD33 antibodies can be avoided by a novel linker module. Mol Immunol 49(3):474–482

    Article  PubMed  CAS  Google Scholar 

  38. Webb B, Sali A (2016) Comparative protein structure modeling using MODELLER. Curr Protoc Bioinformatics 54:5.6.1–5.6.37

    Article  Google Scholar 

  39. Arcangeli C, Cantale C, Galeffi P, Rosato V (2008) Structure and dynamics of the anti-AMCV scFv(F8): effects of selected mutations on the antigen combining site. J Struct Biol 164(1):119–133

    Article  PubMed  CAS  Google Scholar 

  40. Almagro JC, Beavers MP, Hernandez-Guzman F, Maier J, Shaulsky J, Butenhof K et al (2011) Antibody modeling assessment. Proteins. 79(11):3050–3066

    Article  PubMed  CAS  Google Scholar 

  41. Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. Wiley Online Library:283–91

  42. Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35(Web Server issue):W407–W410

    Article  PubMed  PubMed Central  Google Scholar 

  43. DeLano WL (2002) The PyMOL molecular graphics system

    Google Scholar 

  44. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B et al (2015) GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. Elsevier:19–25

  45. Nagasundaram N, Zhu H, Liu J, Karthick V, George Priya C, Chakraborty C et al (2015) Analysing the effect of mutation on protein function and discovering potential inhibitors of CDK4: molecular modelling and dynamics studies. PLoS One 10(8):e0133969

    Article  Google Scholar 

  46. Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci U S A 98(18):10037–10041

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Arai R, Wriggers W, Nishikawa Y, Nagamune T, Fujisawa T (2004 Dec 1) Conformations of variably linked chimeric proteins evaluated by synchrotron X-ray small-angle scattering. Proteins. 57(4):829–838

    Article  PubMed  CAS  Google Scholar 

  48. Kuroda Y, Suenaga A, Sato Y, Kosuda S, Taiji M (2016) All-atom molecular dynamics analysis of multi-peptide systems reproduces peptide solubility in line with experimental observations. Sci Rep 6:19479

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Kamaraj B, Bogaerts A (2015) Structure and function of p53-DNA complexes with inactivation and rescue mutations: a molecular dynamics simulation study. PLoS One 10(8):e0134638

    Article  PubMed  PubMed Central  Google Scholar 

  50. Mohammadi M, Nejatollahi F, Sakhteman A, Zarei N (2016) Insilico analysis of three different tag polypeptides with dual roles in scFv antibodies. J Theor Biol 402:100–106

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The content of this paper is extracted from the Ph.D thesis of Asghar Barkhordari. We thank the Isfahan University, Research Department of Medical Sciences, and the University of Shahrekord, in Iran for their financial supports of this project.

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Authors and Affiliations

  1. Department of Pharmaceutical Biotechnology, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran

    A. Barkhordari & H. Mirmohammad-Sadeghi

  2. Biology Department, Faculty of Science, Shahrekord University, Shahrekord, 8818634141, Iran

    K. Mahnam

  3. Nanotechnology Research Center, Shahrekord University, Shahrekord, 8818634141, Iran

    K. Mahnam

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  1. A. Barkhordari
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  3. H. Mirmohammad-Sadeghi
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Correspondence to K. Mahnam.

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Barkhordari, A., Mahnam, K. & Mirmohammad-Sadeghi, H. Designing a new bispecific tandem single-chain variable fragment antibody against tumor necrosis factor-α and interleukin-23 using in silico studies for the treatment of rheumatoid arthritis. J Mol Model 26, 225 (2020). https://doi.org/10.1007/s00894-020-04510-5

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