Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01

Abstract

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson–Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Structure and sequence comparison of htsFLT01 and sFLT01 proteins.
Fig. 2: Protein complex equilibration validation.
Fig. 3: htsFLT01 and sFLT01 3D structures.
Fig. 4: Residual interaction network analysis.
Fig. 5: htsFLT01 western blotting and tube network formation quantification.
Fig. 6: Confocal microscopy of retinal vasculature 2 weeks after AAV2-htsFLT01 intravitreal delivery.

Data availability

Data will be made available on reasonable request.

References

  1. de Jong EK, Geerlings MJ, den Hollander AI. Age-related macular degeneration. Genetics and Genomics of Eye Disease: MA, USA: Elsevier; Academic Press, 2020. p. 155–80.

  2. Simons M, Gordon E, Claesson-Welsh L. Mechanisms and regulation of endothelial VEGF receptor signalling. Nat Rev Mol Cell Biol. 2016;17:611–25.

    Article  CAS  PubMed  Google Scholar 

  3. Olsson AK, Dimberg A, Kreuger J, Claesson-Welsh L. VEGF receptor signalling - in control of vascular function. Nat Rev Mol Cell Biol. 2006;7:359–71.

    Article  CAS  PubMed  Google Scholar 

  4. Ruiz de Almodovar C, Lambrechts D, Mazzone M, Carmeliet P. Role and therapeutic potential of VEGF in the nervous system. Physiol Rev. 2009;89:607–48.

    Article  CAS  PubMed  Google Scholar 

  5. Falavarjani KG, Nguyen QJE. Adverse events and complications associated with intravitreal injection of anti-VEGF agents: a review of literature. Eye (Lond). 2013;27:787–94.

    Article  PubMed  CAS  Google Scholar 

  6. Bakri SJ, Thorne JE, Ho AC, Ehlers JP, Schoenberger SD, Yeh S, et al. Safety and efficacy of anti-vascular endothelial growth factor therapies for neovascular age-related macular degeneration: a report by the american academy of ophthalmology. Ophthalmology. 2019;126:55–63.

    Article  PubMed  Google Scholar 

  7. Meyer CH, Michels S, Rodrigues EB, Hager A, Mennel S, Schmidt JC, et al. Incidence of rhegmatogenous retinal detachments after intravitreal antivascular endothelial factor injections. Acta Ophthalmol. 2011;89:70–5.

    Article  CAS  PubMed  Google Scholar 

  8. Ladas ID, Karagiannis DA, Rouvas AA, Kotsolis AI, Liotsou A, Vergados IJR. Safety of repeat intravitreal injections of bevacizumab versus ranibizumab: our experience after 2000 injections. Retina. 2009;29:313–8.

    Article  PubMed  Google Scholar 

  9. Tolentino MJSoo. Systemic and ocular safety of intravitreal anti-VEGF therapies for ocular neovascular disease. Surv Ophthalmol. 2011;56:95–113.

    Article  Google Scholar 

  10. Colella P, Ronzitti G, Mingozzi F. Emerging issues in AAV-mediated in vivo gene therapy. Mol Ther Methods Clin Dev. 2018;8:87–104.

    Article  CAS  PubMed  Google Scholar 

  11. Guimaraes TAC, Georgiou M, Bainbridge JWB, Michaelides M. Gene therapy for neovascular age-related macular degeneration: rationale, clinical trials and future directions. Br J Ophthalmol. 2021;105:151–7.

    Article  PubMed  Google Scholar 

  12. Arepalli S, Kaiser PK. Pipeline therapies for neovascular age related macular degeneration. Int J Retina Vitreous. 2021;7:55.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Pecen PE, Kaiser PK. Current phase 1/2 research for neovascular age-related macular degeneration. Curr Opin Ophthalmol. 2015;26:188–93.

    Article  PubMed  Google Scholar 

  14. He X, Cheng R, Benyajati S, Ma JX. PEDF and its roles in physiological and pathological conditions: implication in diabetic and hypoxia-induced angiogenic diseases. Clin Sci (Lond). 2015;128:805–23.

    Article  Google Scholar 

  15. Rodrigues GA, Shalaev E, Karami TK, Cunningham J, Slater NK, Rivers HM. Pharmaceutical development of AAV-based gene therapy products for the eye. Pharm Res. 2019;36:29.

    Article  CAS  Google Scholar 

  16. Naso MF, Tomkowicz B, Perry WL, Strohl WRJB. Adeno-associated virus (AAV) as a vector for gene therapy. BioDrugs. 2017;31:317–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chen HJWJoMG. Adeno-associated virus vectors for human gene therapy. World J Med Genet. 2015;5:28–45.

    Article  Google Scholar 

  18. Rasmussen H, Chu KW, Campochiaro P, Gehlbach PL, Haller JA, Handa JT, et al. Clinical protocol. An open-label, phase I, single administration, dose-escalation study of ADGVPEDF.11D (ADPEDF) in neovascular age-related macular degeneration (AMD). Hum Gene Ther. 2001;12:2029–32.

    CAS  PubMed  Google Scholar 

  19. Campochiaro PA, Nguyen QD, Shah SM, Klein ML, Holz E, Frank RN, et al. Adenoviral vector-delivered pigment epithelium-derived factor for neovascular age-related macular degeneration: results of a phase I clinical trial. Hum Gene Ther. 2006;17:167–76.

    Article  CAS  PubMed  Google Scholar 

  20. Rakoczy EP, Lai CM, Magno AL, Wikstrom ME, French MA, Pierce CM, et al. Gene therapy with recombinant adeno-associated vectors for neovascular age-related macular degeneration: 1 year follow-up of a phase 1 randomised clinical trial. Lancet. 2015;386:2395–403.

    Article  CAS  PubMed  Google Scholar 

  21. Constable IJ, Pierce CM, Lai CM, Magno AL, Degli-Esposti MA, French MA, et al. Phase 2a Randomized Clinical Trial: Safety and Post Hoc Analysis of Subretinal rAAV.sFLT-1 for Wet Age-related Macular Degeneration. EBioMedicine. 2016;14:168–75.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Campochiaro PA, Lauer AK, Sohn EH, Mir TA, Naylor S, Anderton MC, et al. Lentiviral Vector Gene Transfer of Endostatin/Angiostatin for Macular Degeneration (GEM) Study. Hum Gene Ther. 2017;28:99–111.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Binley K, Widdowson PS, Kelleher M, de Belin J, Loader J, Ferrige G, et al. Safety and biodistribution of an equine infectious anemia virus-based gene therapy, RetinoStat((R)), for age-related macular degeneration. Hum Gene Ther. 2012;23:980–91.

    Article  CAS  PubMed  Google Scholar 

  24. Kumar-Singh R. The role of complement membrane attack complex in dry and wet AMD - From hypothesis to clinical trials. Exp Eye Res. 2019;184:266–77.

    Article  CAS  PubMed  Google Scholar 

  25. Cashman SM, Ramo K, Kumar-Singh R. A non membrane-targeted human soluble CD59 attenuates choroidal neovascularization in a model of age related macular degeneration. PLoS ONE. 2011;6:e19078.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Czajkowsky DM, Hu J, Shao Z, Pleass RJ. Fc‐fusion proteins: new developments and future perspectives. EMBO Mol Med. 2012;4:1015–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Rath T, Baker K, Dumont JA, Peters RT, Jiang H, Qiao S-W, et al. Fc-fusion proteins and FcRn: structural insights for longer-lasting and more effective therapeutics. Crit Rev Biotechnol. 2015;35:235–54.

    Article  CAS  PubMed  Google Scholar 

  28. Liu L. Pharmacokinetics of monoclonal antibodies and Fc-fusion proteins. Protein Cell. 2018;9:15–32.

    Article  CAS  PubMed  Google Scholar 

  29. Kim HS, Kim I, Zheng L, Vernes J-M, Meng YG, Spiess C, editors. Evading pre-existing anti-hinge antibody binding by hinge engineering. MAbs. 2016;8:1536–47.

  30. Huang T, Mathieu M, Lee S, Wang X, Kee YS, Bevers JJ, et al. Molecular characterization of human anti-hinge antibodies derived from single-cell cloning of normal human B cells. J Biol Chem. 2018;293:906–19.

    Article  CAS  PubMed  Google Scholar 

  31. Yan B, Boyd D, Kaschak T, Tsukuda J, Shen A, Lin Y, et al. Engineering upper hinge improves stability and effector function of a human IgG1. J Biol Chem. 2012;287:5891–7.

    Article  CAS  PubMed  Google Scholar 

  32. Saunders KO. Conceptual Approaches to Modulating Antibody Effector Functions and Circulation Half-Life. Front Immunol. 2019;10:1296.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. D’Eall C, Pon RA, Rossotti MA, Krahn N, Spearman M, Callaghan D, et al. Modulating antibody‐dependent cellular cytotoxicity of epidermal growth factor receptor‐specific heavy‐chain antibodies through hinge engineering. J Immunol. 2019;177:1129–38.

    Google Scholar 

  34. Dall’Acqua WF, Cook KE, Damschroder MM, Woods RM. Wu HJTJoI. Modulation of the effector functions of a human IgG1 through engineering of its hinge region. J Immunol. 2006;177:1129–38.

    Article  PubMed  Google Scholar 

  35. Pechan P, Rubin H, Lukason M, Ardinger J, DuFresne E, Hauswirth WW, et al. Novel anti-VEGF chimeric molecules delivered by AAV vectors for inhibition of retinal neovascularization. Gene Ther. 2009;16:10–6.

    Article  CAS  PubMed  Google Scholar 

  36. Bagley RG, Kurtzberg L, Weber W, Nguyen T-H, Roth S, Krumbholz R, et al. sFLT01: a novel fusion protein with antiangiogenic activity. Mol Cancer Ther. 2011;10:404–15.

    Article  CAS  PubMed  Google Scholar 

  37. Yang S, Zhao J, Sun X. Resistance to anti-VEGF therapy in neovascular age-related macular degeneration: a comprehensive review. Drug Des Devel Ther. 2016;10:1857–67.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Lukason M, DuFresne E, Rubin H, Pechan P, Li Q, Kim I, et al. Inhibition of choroidal neovascularization in a nonhuman primate model by intravitreal administration of an AAV2 vector expressing a novel anti-VEGF molecule. Mol Ther. 2011;19:260–5.

    Article  CAS  PubMed  Google Scholar 

  39. Heier JS, Kherani S, Desai S, Dugel P, Kaushal S, Cheng SH, et al. Intravitreous injection of AAV2-sFLT01 in patients with advanced neovascular age-related macular degeneration: a phase 1, open-label trial. Lancet. 2017;390:50–61.

    Article  CAS  PubMed  Google Scholar 

  40. Wiesmann C, Fuh G, Christinger HW, Eigenbrot C, Wells JA, de Vos AMJC. Crystal structure at 1.7 Å resolution of VEGF in complex with domain 2 of the Flt-1 receptor. Cell. 1997;91:695–704.

    Article  CAS  PubMed  Google Scholar 

  41. Davari M, Soheili Z-S, Samiei S, Sharifi Z, Pirmardan ER. Overexpression of miR-183/-96/-182 triggers neuronal cell fate in Human Retinal Pigment Epithelial (hRPE) cells in culture. Biochem Biophys Res Commun. 2017;483:745–51.

    Article  CAS  PubMed  Google Scholar 

  42. Šali AJCOiB. Modelling mutations and homologous proteins. Curr Opin Biotechnol. 1995;6:437–51.

    Article  Google Scholar 

  43. Bagley RG, Kurtzberg L, Weber W, Nguyen TH, Roth S, Krumbholz R, et al. sFLT01: a novel fusion protein with antiangiogenic activity. Mol Cancer Ther. 2011;10:404–15.

    Article  CAS  PubMed  Google Scholar 

  44. Kingsley LJ, Brunet V, Lelais G, McCloskey S, Milliken K, Leija E, et al. Development of a virtual reality platform for effective communication of structural data in drug discovery. J Mol Graph Model. 2019;89:234–41.

    Article  CAS  PubMed  Google Scholar 

  45. Laskowski R, MacArthur M, Thornton J. PROCHECK: validation of protein-structure coordinates. International Tables for Crystallography. 2012;684–7.

  46. 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:W407–W10.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Sippl MJ. Recognition of errors in three‐dimensional structures of proteins. Proteins. 1993;17:355–62.

  48. Abraham MJ, Murtola T, Schulz R, Pá ll S, Smith JC, Hess B, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1–2:19–25.

    Article  Google Scholar 

  49. Bjelkmar P, Larsson P, Cuendet MA, Hess B, Lindahl E. Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models. J Chem Theory Comput. 2010;6:459–66.

    Article  CAS  PubMed  Google Scholar 

  50. Berendsen H, Grigera J, Straatsma T. The missing term in effective pair potentials. J Phys Chem. 1987;91:6269–71.

    Article  CAS  Google Scholar 

  51. Hess B. P-LINCS: a parallel linear constraint solver for molecular simulation. J Chem Theory Comput. 2008;4:116–22.

    Article  CAS  PubMed  Google Scholar 

  52. Hess B, Bekker H, Berendsen HJ, Fraaije JG. LINCS: a linear constraint solver for molecular simulations. J Comput Chem. 1997;18:1463–72.

    Article  CAS  Google Scholar 

  53. Zambrano R, Jamroz M, Szczasiuk A, Pujols J, Kmiecik S, Ventura S. AGGRESCAN3D (A3D): server for prediction of aggregation properties of protein structures. Nucleic Acids Res. 2015;43:W306–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Kuriata A, Iglesias V, Pujols J, Kurcinski M, Kmiecik S, Ventura S. Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility. Nucleic Acids Res. 2019;47:W300–W7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Ali M, Pandey RK, Khatoon N, Narula A, Mishra A, Prajapati VK. Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection. Sci Rep. 2017;7:9232.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Hajighahramani N, Nezafat N, Eslami M, Negahdaripour M, Rahmatabadi SS, Ghasemi Y. Immunoinformatics analysis and in silico designing of a novel multi-epitope peptide vaccine against Staphylococcus aureus. Infect Genet Evol. 2017;48:83–94.

    Article  CAS  PubMed  Google Scholar 

  57. Solanki V, Tiwari V. Subtractive proteomics to identify novel drug targets and reverse vaccinology for the development of chimeric vaccine against Acinetobacter baumannii. Sci Rep. 2018;8:9044.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Saadi M, Karkhah A, Nouri HR. Development of a multi-epitope peptide vaccine inducing robust T cell responses against brucellosis using immunoinformatics based approaches. Infect Genet Evol. 2017;51:227–34.

    Article  CAS  PubMed  Google Scholar 

  59. Meza B, Ascencio F, Sierra-Beltran AP, Torres J, Angulo C. A novel design of a multi-antigenic, multistage and multi-epitope vaccine against Helicobacter pylori: an in silico approach. Infect Genet Evol. 2017;49:309–17.

    Article  CAS  PubMed  Google Scholar 

  60. Chauhan V, Rungta T, Goyal K, Singh MP. Designing a multi-epitope based vaccine to combat Kaposi Sarcoma utilizing immunoinformatics approach. Sci Rep. 2019;9:2517.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Rana A, Akhter Y. A multi-subunit based, thermodynamically stable model vaccine using combined immunoinformatics and protein structure based approach. Immunobiology. 2016;221:544–57.

    Article  CAS  PubMed  Google Scholar 

  62. Dhanda SK, Usmani SS, Agrawal P, Nagpal G, Gautam A, Raghava GPS. Novel in silico tools for designing peptide-based subunit vaccines and immunotherapeutics. Brief Bioinform. 2017;18:467–78.

    CAS  PubMed  Google Scholar 

  63. Bhatnager R, Bhasin M, Arora J, Dang AS. Epitope based peptide vaccine against SARS-COV2: an immune-informatics approach. J Biomol Struct Dyn. 2021;39:5690–705.

    Article  CAS  PubMed  Google Scholar 

  64. Alam A, Khan A, Imam N, Siddiqui MF, Waseem M, Malik MZ, et al. Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach. Brief Bioinform. 2021;22:1309–23.

    Article  CAS  PubMed  Google Scholar 

  65. Scussel R, Feuser PE, Luiz GP, Galvani NC, Fagundes MI, Goncalves Dal-Bo A, et al. Peptide-Integrated Superparamagnetic Nanoparticles for the Identification of Epitopes from SARS-CoV-2 Spike and Nucleocapsid Proteins. ACS Appl Nano Mater. 2022;5:642–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Shah I, Jamil S, Rehmat S, Butt HA, Ali SS, Idrees M, et al. Evaluation and identification of essential therapeutic proteins and vaccinomics approach towards multi-epitopes vaccine designing against Legionella pneumophila for immune response instigation. Comput Biol Med. 2022;143:105291.

    Article  CAS  PubMed  Google Scholar 

  67. Ojha R, Gurjar K, Ratnakar TS, Mishra A, Prajapati VK. Designing of a bispecific antibody against SARS-CoV-2 spike glycoprotein targeting human entry receptors DPP4 and ACE2. Hum Immunol. 2022;83:346–55.

    Article  CAS  PubMed  Google Scholar 

  68. Ismail S, Waheed Y, Ahmad S, Ahsan O, Abbasi SW, Sadia K. An in silico study to unveil potential drugs and vaccine chimera for HBV capsid assembly protein: combined molecular docking and dynamics simulation approach. J Mol Model. 2022;28:51.

    Article  CAS  PubMed  Google Scholar 

  69. Khan A, Khan S, Saleem S, Nizam-Uddin N, Mohammad A, Khan T, et al. Immunogenomics guided design of immunomodulatory multi-epitope subunit vaccine against the SARS-CoV-2 new variants, and its validation through in silico cloning and immune simulation. Comput Biol Med. 2021;133:104420.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Saha S, Raghava GPS. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res. 2006;34:W202–W9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Saha CK, Mahbub Hasan M, Saddam Hossain M, Asraful Jahan M, Azad AK. In silico identification and characterization of common epitope-based peptide vaccine for Nipah and Hendra viruses. Asian Pac J Trop Med. 2017;10:529–38.

    Article  CAS  PubMed  Google Scholar 

  72. Nguyen TL, Lee Y, Kim H. Immunogenic Epitope-Based Vaccine Prediction from Surface Glycoprotein of MERS-CoV by Deploying Immunoinformatics Approach. Int J Pept Res Ther. 2022;28:77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Yazdani Z, Rafiei A, Valadan R, Ashrafi H, Pasandi M, Kardan M. Designing a potent L1 protein-based HPV peptide vaccine: a bioinformatics approach. Comput Biol Chem. 2020;85:107209.

    Article  CAS  PubMed  Google Scholar 

  74. Ghosh P, Bhakta S, Bhattacharya M, Sharma AR, Sharma G, Lee SS, et al. A Novel Multi-Epitopic Peptide Vaccine Candidate Against Helicobacter pylori: In-Silico Identification, Design, Cloning and Validation Through Molecular Dynamics. Int J Pept Res Ther. 2021;27:1149–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Naqvi STQ, Yasmeen M, Ismail M, Muhammad SA, Nawazish IHS, Ali A, et al. Designing of Potential Polyvalent Vaccine Model for Respiratory Syncytial Virus by System Level Immunoinformatics Approaches. Biomed Res Int. 2021;2021:9940010.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Selvaraj G, Kaliamurthi S, Peslherbe GH, Wei DQ. Are the Allergic Reactions of COVID-19 Vaccines Caused by mRNA Constructs or Nanocarriers? Immunological Insights. Interdiscip Sci. 2021;13:344–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Ashik AI, Hasan M, Tasnim AT, Chowdhury MB, Hossain T, Ahmed S. An immunoinformatics study on the spike protein of SARS-CoV-2 revealing potential epitopes as vaccine candidates. Heliyon. 2020;6:e04865.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Abd Albagi SO, Al-Nour MY, Elhag M, Tageldein Idris Abdelihalim A, Musa Haroun E, Adam, Essa ME, et al. A multiple peptides vaccine against COVID-19 designed from the nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the immunoinformatics approach. Inform Med Unlocked. 2020;21:100476.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Sharma S, Solanki V, Tiwari V. Reverse vaccinology approach to design a vaccine targeting membrane lipoproteins of Salmonella typhi. J Biomol Struct Dyn. 2021:1–16.

  80. Dimitrov I, Naneva L, Doytchinova I, Bangov I. AllergenFP: allergenicity prediction by descriptor fingerprints. Bioinformatics. 2014;30:846–51.

    Article  CAS  PubMed  Google Scholar 

  81. Abraham Peele K, Srihansa T, Krupanidhi S, Ayyagari VS, Venkateswarulu TC. Design of multi-epitope vaccine candidate against SARS-CoV-2: a in-silico study. J Biomol Struct Dyn. 2021;39:3793–801.

    Article  CAS  PubMed  Google Scholar 

  82. Soltan MA, Elbassiouny N, Gamal H, Elkaeed EB, Eid RA, Eldeen MA, et al. In Silico Prediction of a Multitope Vaccine against Moraxella catarrhalis: Reverse Vaccinology and Immunoinformatics. Vaccines (Basel). 2021;9:1–13.

    Google Scholar 

  83. Sanami S, Zandi M, Pourhossein B, Mobini GR, Safaei M, Abed A, et al. Design of a multi-epitope vaccine against SARS-CoV-2 using immunoinformatics approach. Int J Biol Macromol. 2020;164:871–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Halimatul Munawaroh HS, Gumilar GG, Berliana JD, Aisyah S, Nuraini VA, Ningrum A, et al. In silico proteolysis and molecular interaction of tilapia (Oreochromis niloticus) skin collagen-derived peptides for environmental remediation. Environ Res. 2022:113002.

  85. Rahmat Ullah S, Majid M, Rashid MI, Mehmood K, Andleeb S. Immunoinformatics Driven Prediction of Multiepitopic Vaccine Against Klebsiella pneumoniae and Mycobacterium tuberculosis Coinfection and Its Validation via In Silico Expression. Int J Pept Res Ther. 2021;27:987–99.

    Article  CAS  PubMed  Google Scholar 

  86. Singh A, Thakur M, Sharma LK, Chandra K. Designing a multi-epitope peptide based vaccine against SARS-CoV-2. Sci Rep. 2020;10:16219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Adhikari UK, Tayebi M, Rahman MM. Immunoinformatics Approach for Epitope-Based Peptide Vaccine Design and Active Site Prediction against Polyprotein of Emerging Oropouche Virus. J Immunol Res. 2018;2018:6718083.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Zhou F, He S, Zhang Y, Wang Y, Sun H, Liu Q. Prediction and characterization of the T cell epitopes for the major soybean protein allergens using bioinformatics approaches. Proteins. 2022;90:418–34.

    Article  CAS  PubMed  Google Scholar 

  89. Dimitrov I, Bangov I, Flower DR, Doytchinova I. AllerTOP v.2–a server for in silico prediction of allergens. J Mol Model. 2014;20:2278.

    Article  PubMed  CAS  Google Scholar 

  90. Venkatarajan MS, Braun W. New quantitative descriptors of amino acids based on multidimensional scaling of a large number of physical–chemical properties. Mol Modeling Ann. 2001;7:445–53.

    Article  CAS  Google Scholar 

  91. Nyström Å, Andersson PM, Lundstedt T. Multivariate data analysis of topographically modified α‐melanotropin analogues using auto and cross auto covariances (ACC). Quant Structure‐Activity Relation. 2000;19:264–9.

    Article  Google Scholar 

  92. Dimitrov I, Bangov I, Flower DR, Doytchinova I. AllerTOP v. 2—a server for in silico prediction of allergens. J Mol Modeling. 2014;20:1–6.

    Article  CAS  Google Scholar 

  93. Dimitrov I, Flower DR, Doytchinova I, editors. AllerTOP-a server for in silico prediction of allergens. BMC Bioinforma. 2013;14:1–9.

  94. Lapinsh M, Gutcaits A, Prusis P, Post C, Lundstedt T, Wikberg JE. Classification of G‐protein coupled receptors by alignment‐independent extraction of principal chemical properties of primary amino acid sequences. Protein Sc. 2002;11:795–805.

    Article  CAS  Google Scholar 

  95. Dehghani B, Hashempour T, Hasanshahi Z. Using immunoinformatics and structural approaches to design a novel HHV8 vaccine. Int J Peptide Res Ther. 2020;26:321–31.

    Article  CAS  Google Scholar 

  96. Yazdani Z, Rafiei A, Valadan R, Ashrafi H, Pasandi M, Kardan M. Designing a potent L1 protein-based HPV peptide vaccine: a bioinformatics approach. Comput Biol Chem. 2020;85:107209.

    Article  CAS  PubMed  Google Scholar 

  97. Nguyen TL, Lee Y, Kim H. Immunogenic Epitope-Based Vaccine Prediction from Surface Glycoprotein of MERS-CoV by Deploying Immunoinformatics Approach. Int J Peptide Res Ther. 2022;28:1–11.

    Article  CAS  Google Scholar 

  98. Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 2007;8:4.

    Article  CAS  Google Scholar 

  99. Jyotisha, Singh S, Qureshi IA. Multi-epitope vaccine against SARS-CoV-2 applying immunoinformatics and molecular dynamics simulation approaches. J Biomol Struct Dyn. 2020:1–17.

  100. Karagoz IK, Munk MR, Kaya M, Ruckert R, Yildirim M, Karabas L. Using bioinformatic protein sequence similarity to investigate if SARS CoV-2 infection could cause an ocular autoimmune inflammatory reactions? Exp Eye Res. 2021;203:108433.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Yadav S, Prakash J, Shukla H, Das KC, Tripathi T, Dubey VK. Design of a multi-epitope subunit vaccine for immune-protection against Leishmania parasite. Pathogens Global Health. 2020;114:471–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Kumar Pandey R, Ojha R, Mishra A, Kumar, Prajapati V. Designing B‐and T‐cell multi‐epitope based subunit vaccine using immunoinformatics approach to control Zika virus infection. J Cell Biochem. 2018;119:7631–42.

    Article  CAS  PubMed  Google Scholar 

  103. Dey J, Mahapatra SR, Patnaik S, Lata S, Kushwaha GS, Panda RK, et al. Molecular Characterization and Designing of a Novel Multiepitope Vaccine Construct Against Pseudomonas aeruginosa. Int J Peptide Res Ther. 2022;28:1–19.

    Article  CAS  Google Scholar 

  104. Yukeswaran L, Shreeranjana S, Subhashini T. Immunoinformatics Aided Multi-epitope Based Vaccine Design Against Crimean-Congo Virus. AIJR Abstracts. 2021:43.

  105. Oprea M, Antohe F. Reverse-vaccinology strategy for designing T-cell epitope candidates for Staphylococcus aureus endocarditis vaccine. Biologicals. 2013;41:148–53.

    Article  CAS  PubMed  Google Scholar 

  106. Kalita P, Padhi AK, Zhang KY, Tripathi T. Design of a peptide-based subunit vaccine against novel coronavirus SARS-CoV-2. Microbial Pathogenesis. 2020;145:104236.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Ponomarenko J, Bui HH, Li W, Fusseder N, Bourne PE, Sette A, et al. ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinform. 2008;9:514.

    Article  CAS  Google Scholar 

  108. Bhasin M, Raghava GP. Prediction of CTL epitopes using QM, SVM and ANN techniques. Vaccine. 2004;22:3195–204.

    Article  CAS  PubMed  Google Scholar 

  109. Morris JH, Huang CC, Babbitt PC, Ferrin TE. structureViz: linking Cytoscape and UCSF Chimera. Bioinformatics. 2007;23:2345–7.

    Article  CAS  PubMed  Google Scholar 

  110. Doncheva NT, Klein K, Domingues FS, Albrecht M. Analyzing and visualizing residue networks of protein structures. Trends Biochem Sci. 2011;36:179–82.

    Article  CAS  PubMed  Google Scholar 

  111. Brysbaert G, Lorgouilloux K, Vranken WF, Lensink MF. RINspector: a Cytoscape app for centrality analyses and DynaMine flexibility prediction. Bioinformatics. 2018;34:294–6.

    Article  CAS  PubMed  Google Scholar 

  112. Amitai G, Shemesh A, Sitbon E, Shklar M, Netanely D, Venger I, et al. Network analysis of protein structures identifies functional residues. J Mol Biol. 2004;344:1135–46.

    Article  CAS  PubMed  Google Scholar 

  113. Brysbaert G, Mauri T, Lensink MF. Comparing protein structures with RINspector automation in Cytoscape. F1000Res. 2018;7:563.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Kay P, Yang YC, Paraoan L. Directional protein secretion by the retinal pigment epithelium: roles in retinal health and the development of age‐related macular degeneration. J Cell Mol Med. 2013;17:833–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Pirmardan ER, Soheili Z-S, Samiei S, Ahmadieh H, Mowla SJ, Naseri M, et al. In Vivo Evaluation of PAX6 Overexpression and NMDA Cytotoxicity to Stimulate Proliferation in the Mouse Retina. Sci Rep. 2018;8:17700.

    Article  CAS  Google Scholar 

  116. DeCicco-Skinner KL, Henry GH, Cataisson C, Tabib T, Gwilliam JC, Watson NJ, et al. Endothelial cell tube formation assay for the in vitro study of angiogenesis. J Vis Exp. 2014;91:e51312.

    Google Scholar 

  117. Faibish M, Shao RJ, Jove J. A Matrigel-based tube formation assay to assess the vasculogenic activity of tumor cells. J Vis Exp. 2011;55:1–4.

    Google Scholar 

  118. Arnaoutova I, George J, Kleinman HK, Benton GJA. The endothelial cell tube formation assay on basement membrane turns 20: state of the science and the art. Angiogenesis. 2009;12:267–74.

    Article  PubMed  Google Scholar 

  119. Fruttiger M. Development of the mouse retinal vasculature: angiogenesis versus vasculogenesis. Invest Ophthalmol Vis Sci. 2002;43:522–7.

  120. Brown AS, Zhang M, Cucevic V, Pavlin CJ, Foster FS. In vivo assessment of postnatal murine ocular development by ultrasound biomicroscopy. Curr Eye Res. 2005;30:45–51.

    Article  PubMed  Google Scholar 

  121. Kowalczuk L, Touchard E, Omri S, Jonet L, Klein C, Valamanes F, et al. Placental growth factor contributes to micro-vascular abnormalization and blood-retinal barrier breakdown in diabetic retinopathy. PLoS One. 2011;6:e17462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Sandin S, Ofverstedt LG, Wikstrom AC, Wrange O, Skoglund U. Structure and flexibility of individual immunoglobulin G molecules in solution. Structure. 2004;12:409–15.

    Article  CAS  PubMed  Google Scholar 

  123. Saphire EO, Stanfield RL, Crispin MD, Parren PW, Rudd PM, Dwek RA, et al. Contrasting IgG structures reveal extreme asymmetry and flexibility. J Mol Biol. 2002;319:9–18.

    Article  CAS  PubMed  Google Scholar 

  124. Chiu ML, Goulet DR, Teplyakov A, Gilliland GL. Antibody Structure and Function: The Basis for Engineering Therapeutics. Antibodies (Basel). 2019;8:1–80.

    Google Scholar 

  125. Moritz B, Stracke JO. Assessment of disulfide and hinge modifications in monoclonal antibodies. Electrophoresis. 2017;38:769–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Reibaldi M, Pulvirenti A, Avitabile T, Bonfiglio V, Russo A, Mariotti C, et al. Pooled Estimates of Incidence of Endophthalmitis after Intravitreal Injection of Anti-Vascular Endothelial Growth Factor Agents with and without Topical Antibiotic Prophylaxis. Retina. 2018;38:1–11.

    Article  PubMed  Google Scholar 

  127. Rosenfeld PJ, Brown DM, Heier JS, Boyer DS, Kaiser PK, Chung CY, et al. Ranibizumab for neovascular age-related macular degeneration. N Engl J Med. 2006;355:1419–31.

    Article  CAS  PubMed  Google Scholar 

  128. Bhavsar AR, Googe JM Jr. Stockdale CR, Bressler NM, Brucker AJ, Elman MJ, et al. Risk of endophthalmitis after intravitreal drug injection when topical antibiotics are not required: the diabetic retinopathy clinical research network laser-ranibizumab-triamcinolone clinical trials. Arch Ophthalmol. 2009;127:1581–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Bhatt SS, Stepien KE, Joshi K. Prophylactic antibiotic use after intravitreal injection: effect on endophthalmitis rate. Retina. 2011;31:2032–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Bhavsar AR, Ip MS, Glassman AR. Drcrnet, the SSG. The risk of endophthalmitis following intravitreal triamcinolone injection in the DRCRnet and SCORE clinical trials. Am J Ophthalmol. 2007;144:454–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Kim SJ, Toma HS. Antimicrobial resistance and ophthalmic antibiotics: 1-year results of a longitudinal controlled study of patients undergoing intravitreal injections. Arch Ophthalmol. 2011;129:1180–8.

    Article  PubMed  Google Scholar 

  132. Milder E, Vander J, Shah C, Garg S. Changes in antibiotic resistance patterns of conjunctival flora due to repeated use of topical antibiotics after intravitreal injection. Ophthalmology. 2012;119:1420–4.

    Article  PubMed  Google Scholar 

  133. Cheung CS, Wong AW, Lui A, Kertes PJ, Devenyi RG, Lam WC. Incidence of endophthalmitis and use of antibiotic prophylaxis after intravitreal injections. Ophthalmology. 2012;119:1609–14.

    Article  PubMed  Google Scholar 

  134. Dall’Acqua WF, Cook KE, Damschroder MM, Woods RM, Wu H. Modulation of the effector functions of a human IgG1 through engineering of its hinge region. J Immunol. 2006;177:1129–38.

    Article  PubMed  Google Scholar 

  135. Valeich J, Boyd D, Kanwar M, Stenzel D, De Ghosh D, Ebrahimi A, et al. Taking the Hinge off: An Approach to Effector-Less Monoclonal Antibodies. Antibodies (Basel). 2020;9:1–14.

    CAS  Google Scholar 

  136. Stewart MW. The expanding role of vascular endothelial growth factor inhibitors in ophthalmology. Mayo Clin Proc. 2012;87:77–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Stewart MW, Grippon S, Kirkpatrick P. Aflibercept. Nat Rev Drug Discov. 2012;11:269–70.

    Article  CAS  PubMed  Google Scholar 

  138. He J, Wang H, Liu Y, Li W, Kim D, Huang H. Blockade of vascular endothelial growth factor receptor 1 prevents inflammation and vascular leakage in diabetic retinopathy. J Ophthalmol. 2015;2015:605946.

    Article  PubMed  PubMed Central  Google Scholar 

  139. Van Bergen T, Hu TT, Etienne I, Reyns GE, Moons L, Feyen JHM. Neutralization of placental growth factor as a novel treatment option in diabetic retinopathy. Exp Eye Res. 2017;165:136–50.

    Article  PubMed  CAS  Google Scholar 

  140. Jiang B, Xu S, Hou X, Pimentel DR, Brecher P, Cohen RA. Temporal control of NF-kappaB activation by ERK differentially regulates interleukin-1beta-induced gene expression. J Biol Chem. 2004;279:1323–9.

    Article  CAS  PubMed  Google Scholar 

  141. Bonfiglio V, Platania CBM, Lazzara F, Conti F, Pizzo C, Reibaldi M, et al. TGF-beta Serum Levels in Diabetic Retinopathy Patients and the Role of Anti-VEGF Therapy. Int J Mol Sci. 2020;21:1–16.

    Article  CAS  Google Scholar 

  142. Tokunaga CC, Mitton KP, Dailey W, Massoll C, Roumayah K, Guzman E, et al. Effects of anti-VEGF treatment on the recovery of the developing retina following oxygen-induced retinopathy. Investig Ophthalmol Vis Sci. 2014;55:1884–92.

    Article  CAS  Google Scholar 

  143. Dolar-Szczasny J, Bucolo C, Zweifel S, Carnevali A, Rejdak R, Zaluska W, et al. Evaluation of Aqueous Flare Intensity in Eyes Undergoing Intravitreal Bevacizumab Therapy to Treat Neovascular Age-Related Macular Degeneration. Front Pharmacol. 2021;12:656774.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Montemagno C, Pages G. Resistance to Anti-angiogenic Therapies: A Mechanism Depending on the Time of Exposure to the Drugs. Front Cell Dev Biol. 2020;8:584.

    Article  PubMed  PubMed Central  Google Scholar 

  145. Gacche RN, Assaraf YG. Redundant angiogenic signaling and tumor drug resistance. Drug Resist Updat. 2018;36:47–76.

    Article  PubMed  Google Scholar 

  146. Latifi-Navid H, Soheili ZS, Samiei S, Sadeghi M, Taghizadeh S, Pirmardan ER, et al. Network analysis and the impact of Aflibercept on specific mediators of angiogenesis in HUVEC cells. J Cell Mol Med. 2021;25:8285–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Rezzola S, Loda A, Corsini M, Semeraro F, Annese T, Presta M, et al. Angiogenesis-Inflammation Cross Talk in Diabetic Retinopathy: Novel Insights From the Chick Embryo Chorioallantoic Membrane/Human Vitreous Platform. Front Immunol. 2020;11:581288.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Haibe Y, Kreidieh M, El Hajj H, Khalifeh I, Mukherji D, Temraz S, et al. Resistance Mechanisms to Anti-angiogenic Therapies in Cancer. Front Oncol. 2020;10:221.

    Article  PubMed  PubMed Central  Google Scholar 

  149. Lazzara F, Fidilio A, Platania CBM, Giurdanella G, Salomone S, Leggio GM, et al. Aflibercept regulates retinal inflammation elicited by high glucose via the PlGF/ERK pathway. Biochem Pharmacol. 2019;168:341–51.

    Article  CAS  PubMed  Google Scholar 

  150. Winterhoff B, Konecny GE. Targeting fibroblast growth factor pathways in endometrial cancer. Curr Probl Cancer. 2017;41:37–47.

    Article  PubMed  Google Scholar 

  151. Chae YK, Ranganath K, Hammerman PS, Vaklavas C, Mohindra N, Kalyan A, et al. Inhibition of the fibroblast growth factor receptor (FGFR) pathway: the current landscape and barriers to clinical application. Oncotarget. 2017;8:16052–74.

    Article  PubMed  Google Scholar 

  152. Turner N, Grose R. Fibroblast growth factor signalling: from development to cancer. Nat Rev Cancer. 2010;10:116–29.

    Article  CAS  PubMed  Google Scholar 

  153. Larrieu-Lahargue F, Welm AL, Bouchecareilh M, Alitalo K, Li DY, Bikfalvi A, et al. Blocking Fibroblast Growth Factor receptor signaling inhibits tumor growth, lymphangiogenesis, and metastasis. PLoS ONE. 2012;7:e39540.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Brzozowa M, Wojnicz R, Kowalczyk-Ziomek G, Helewski K. The Notch ligand Delta-like 4 (DLL4) as a target in angiogenesis-based cancer therapy? Contemp Oncol (Pozn). 2013;17:234–7.

    CAS  Google Scholar 

  155. Li JL, Sainson RC, Oon CE, Turley H, Leek R, Sheldon H, et al. DLL4-Notch signaling mediates tumor resistance to anti-VEGF therapy in vivo. Cancer Res. 2011;71:6073–83.

    Article  CAS  PubMed  Google Scholar 

  156. Oon CE, Bridges E, Sheldon H, Sainson RCA, Jubb A, Turley H, et al. Role of Delta-like 4 in Jagged1-induced tumour angiogenesis and tumour growth. Oncotarget. 2017;8:40115–31.

    Article  PubMed  PubMed Central  Google Scholar 

  157. Garajova I, Giovannetti E, Biasco G, Peters GJ. c-Met as a Target for Personalized Therapy. Transl Oncogenom. 2015;7:13–31.

    Google Scholar 

  158. Razzak M. Targeted therapies: hepatocyte growth factor-a culprit of drug resistance. Nat Rev Clin Oncol. 2012;9:429.

    Article  PubMed  Google Scholar 

  159. Nakagawa T, Matsushima T, Kawano S, Nakazawa Y, Kato Y, Adachi Y, et al. Lenvatinib in combination with golvatinib overcomes hepatocyte growth factor pathway-induced resistance to vascular endothelial growth factor receptor inhibitor. Cancer Sci. 2014;105:723–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Zhou L, Liu XD, Sun M, Zhang X, German P, Bai S, et al. Targeting MET and AXL overcomes resistance to sunitinib therapy in renal cell carcinoma. Oncogene. 2016;35:2687–97.

    Article  CAS  PubMed  Google Scholar 

  161. Cascone T, Xu L, Lin HY, Liu W, Tran HT, Liu Y, et al. The HGF/c-MET Pathway Is a Driver and Biomarker of VEGFR-inhibitor Resistance and Vascular Remodeling in Non-Small Cell Lung Cancer. Clin Cancer Res. 2017;23:5489–501.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Chen W, Wu J, Shi H, Wang Z, Zhang G, Cao Y, et al. Hepatic stellate cell coculture enables sorafenib resistance in Huh7 cells through HGF/c-Met/Akt and Jak2/Stat3 pathways. Biomed Res Int. 2014;2014:764981.

    PubMed  PubMed Central  Google Scholar 

  163. Shojaei F, Lee JH, Simmons BH, Wong A, Esparza CO, Plumlee PA, et al. HGF/c-Met acts as an alternative angiogenic pathway in sunitinib-resistant tumors. Cancer Res. 2010;70:10090–100.

    Article  CAS  PubMed  Google Scholar 

  164. Scholz A, Harter PN, Cremer S, Yalcin BH, Gurnik S, Yamaji M, et al. Endothelial cell-derived angiopoietin-2 is a therapeutic target in treatment-naive and bevacizumab-resistant glioblastoma. EMBO Mol Med. 2016;8:39–57.

    Article  CAS  PubMed  Google Scholar 

  165. Karlan BY, Oza AM, Richardson GE, Provencher DM, Hansen VL, Buck M, et al. Randomized, double-blind, placebo-controlled phase II study of AMG 386 combined with weekly paclitaxel in patients with recurrent ovarian cancer. J Clin Oncol. 2012;30:362–71.

    Article  CAS  PubMed  Google Scholar 

  166. Mazzieri R, Pucci F, Moi D, Zonari E, Ranghetti A, Berti A, et al. Targeting the ANG2/TIE2 axis inhibits tumor growth and metastasis by impairing angiogenesis and disabling rebounds of proangiogenic myeloid cells. Cancer Cell. 2011;19:512–26.

    Article  CAS  PubMed  Google Scholar 

  167. Cumpanas AA, Cimpean AM, Ferician O, Ceausu RA, Sarb S, Barbos V, et al. The Involvement of PDGF-B/PDGFRbeta Axis in the Resistance to Antiangiogenic and Antivascular Therapy in Renal Cancer. Anticancer Res. 2016;36:2291–5.

    CAS  PubMed  Google Scholar 

  168. Ishii Y, Hamashima T, Yamamoto S, Sasahara M. Pathogenetic significance and possibility as a therapeutic target of platelet derived growth factor. Pathol Int. 2017;67:235–46.

    Article  PubMed  Google Scholar 

  169. Demoulin JB, Essaghir A. PDGF receptor signaling networks in normal and cancer cells. Cytokine Growth Factor Rev. 2014;25:273–83.

    Article  CAS  PubMed  Google Scholar 

  170. Appelmann I, Liersch R, Kessler T, Mesters RM, Berdel WE. Angiogenesis inhibition in cancer therapy: platelet-derived growth factor (PDGF) and vascular endothelial growth factor (VEGF) and their receptors: biological functions and role in malignancy. Recent Results Cancer Res. 2010;180:51–81.

    Article  CAS  PubMed  Google Scholar 

  171. Dmitrieva OS, Shilovskiy IP, Khaitov MR, Grivennikov SI. Interleukins 1 and 6 as Main Mediators of Inflammation and Cancer. Biochemistry (Mosc). 2016;81:80–90.

    Article  CAS  Google Scholar 

  172. Chung AS, Wu X, Zhuang G, Ngu H, Kasman I, Zhang J, et al. An interleukin-17-mediated paracrine network promotes tumor resistance to anti-angiogenic therapy. Nat Med. 2013;19:1114–23.

    Article  CAS  PubMed  Google Scholar 

  173. Huang D, Ding Y, Zhou M, Rini BI, Petillo D, Qian CN, et al. Interleukin-8 mediates resistance to antiangiogenic agent sunitinib in renal cell carcinoma. Cancer Res. 2010;70:1063–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  174. Del Vecchio M, Bajetta E, Canova S, Lotze MT, Wesa A, Parmiani G, et al. Interleukin-12: biological properties and clinical application. Clin Cancer Res. 2007;13:4677–85.

    Article  PubMed  Google Scholar 

  175. Yang B, Kang H, Fung A, Zhao H, Wang T, Ma D. The role of interleukin 17 in tumour proliferation, angiogenesis, and metastasis. Mediators Inflamm. 2014;2014:623759.

    Article  PubMed  PubMed Central  Google Scholar 

  176. Xi HQ, Wu XS, Wei B, Chen L. Eph receptors and ephrins as targets for cancer therapy. J Cell Mol Med. 2012;16:2894–909.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Sawamiphak S, Seidel S, Essmann CL, Wilkinson GA, Pitulescu ME, Acker T, et al. Ephrin-B2 regulates VEGFR2 function in developmental and tumour angiogenesis. Nature. 2010;465:487–91.

    Article  CAS  PubMed  Google Scholar 

  178. Depner C, Zum Buttel H, Bogurcu N, Cuesta AM, Aburto MR, Seidel S, et al. EphrinB2 repression through ZEB2 mediates tumour invasion and anti-angiogenic resistance. Nat Commun. 2016;7:12329.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Cunha SI, Pietras K. ALK1 as an emerging target for antiangiogenic therapy of cancer. Blood. 2011;117:6999–7006.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. de Vinuesa AG, Bocci M, Pietras K, Ten Dijke P. Targeting tumour vasculature by inhibiting activin receptor-like kinase (ALK)1 function. Biochem Soc Trans. 2016;44:1142–9.

    Article  PubMed  CAS  Google Scholar 

  181. Hu-Lowe DD, Chen E, Zhang L, Watson KD, Mancuso P, Lappin P, et al. Targeting activin receptor-like kinase 1 inhibits angiogenesis and tumorigenesis through a mechanism of action complementary to anti-VEGF therapies. Cancer Res. 2011;71:1362–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Gore AV, Swift MR, Cha YR, Lo B, McKinney MC, Li W, et al. Rspo1/Wnt signaling promotes angiogenesis via Vegfc/Vegfr3. Development. 2011;138:4875–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  183. Pereira C, Schaer DJ, Bachli EB, Kurrer MO, Schoedon G. Wnt5A/CaMKII signaling contributes to the inflammatory response of macrophages and is a target for the antiinflammatory action of activated protein C and interleukin-10. Arterioscler Thromb Vasc Biol. 2008;28:504–10.

    Article  CAS  PubMed  Google Scholar 

  184. Dailey W, Shunemann R, Yang F, Moore M, Knapp A, Chen P, et al. Differences in activation of intracellular signaling in primary human retinal endothelial cells between isoforms of VEGFA 165. Mol Vis. 2021;27:191–205.

    CAS  PubMed  PubMed Central  Google Scholar 

  185. Plyukhova AA, Budzinskaya MV, Starostin KM, Rejdak R, Bucolo C, Reibaldi M, et al. Comparative Safety of Bevacizumab, Ranibizumab, and Aflibercept for Treatment of Neovascular Age-Related Macular Degeneration (AMD): A Systematic Review and Network Meta-Analysis of Direct Comparative Studies. J Clin Med. 2020;9:1–14.

    Article  CAS  Google Scholar 

  186. Booth BJ, Ramakrishnan B, Narayan K, Wollacott AM, Babcock GJ, Shriver Z, et al. Extending human IgG half-life using structure-guided design. MAbs. 2018;10:1098–110.

    CAS  PubMed  PubMed Central  Google Scholar 

  187. Bajardi-Taccioli A, Blum A, Xu C, Sosic Z, Bergelson S, Feschenko M. Effect of protein aggregates on characterization of FcRn binding of Fc-fusion therapeutics. Mol Immunol. 2015;67:616–24.

    Article  CAS  PubMed  Google Scholar 

  188. Chen X, Zaro JL, Shen W-C. Fusion protein linkers: property, design and functionality. Adv Drug Deliv Rev. 2013;65:1357–69.

    Article  CAS  PubMed  Google Scholar 

  189. Brysbaert G, Mauri T, de Ruyck J, Lensink MF. Identification of Key Residues in Proteins Through Centrality Analysis and Flexibility Prediction with RINspector. Curr Protoc Bioinform. 2019;65:e66.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Institute of Genetic Engineering and Biotechnology (NIGEB) through grant no.649. Our gratitude thanks to the INSF, Iran National Science Foundation, for the Doctoral Research Support Grant to perform this study (No. 96004188).

Author information

Authors and Affiliations

Authors

Contributions

Z-SS designed the research; FZ, SS, ERP, ST, HL-N performed the research; ERP, MS, SSA, HA, AH-M, HL-N analyzed the data. FZ, Z-SS, ERP, SSA; HL-N wrote the paper.

Corresponding author

Correspondence to Zahra-Soheila Soheili.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Animal experiments were performed under the ARVO (Association for Research in Vision and Ophthalmology) protocol for the use of animals and protocols and were approved by the ethical committee of the “Ophthalmic Research Center, Shahid Beheshti University of Medical Sciences” and the “National Institute of Genetic Engineering and Biotechnology”.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zakeri, F., Latifi-Navid, H., Soheili, ZS. et al. Design, construction and in vivo functional assessment of a hinge truncated sFLT01. Gene Ther (2022). https://doi.org/10.1038/s41434-022-00362-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41434-022-00362-1

Search

Quick links