Skip to main content

Advertisement

SpringerLink
Log in

Analysis of Tumor Necrosis Factor Function Using the Resonant Recognition Model

  • Original Paper
  • Published:
Cell Biochemistry and Biophysics Aims and scope Submit manuscript

Abstract

The tumor necrosis factor (TNF) is a complex protein that plays a very important role in a number of biological functions including apoptotic cell death, tumor regression, cachexia, inflammation inhibition of tumorigenesis and viral replication. Its most interesting function is that it is an inhibitor of tumorigenesis and inductor of apoptosis. Thus, the TNF could be a good candidate for cancer therapy. However, the TNF has also inflammatory and toxic effects. Therefore, it would be very important to understand complex functions of the TNF and consequently be able to predict mutations or even design the new TNF-related proteins that will have only a tumor inhibition function, but not other side effects. This can be achieved by applying the resonant recognition model (RRM), a unique computational model of analysing macromolecular sequences of proteins, DNA and RNA. The RRM is based on finding that certain periodicities in distribution of free electron energies along protein, DNA and RNA are strongly correlated to the biological function of these macromolecules. Thus, based on these findings, the RRM has capabilities of protein function identification, prediction of bioactive amino acids and protein design with desired biological function. Using the RRM, we separate different functions of TNF as different periodicities (frequencies) within the distribution of free energy electrons along TNF protein. Interestingly, these characteristic TNF frequencies are related to previously identified characteristics of proto-oncogene and oncogene proteins describing TNF involvement in oncogenesis. Consequently, we identify the key amino acids related to the crucial TNF function, i.e. receptor recognition. We have also designed the peptide which will have the ability to recognise the receptor without side effects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Wajant, H., Pfizenmaier, K., & Scheurich, P. (2003). Tumor necrosis factor signalling. Cell Death and Differentiation, 10, 45–65.

    Article  CAS  PubMed  Google Scholar 

  2. Tumor necrosis factor. (2015) Wikipedia

  3. Locksley, R. M., Killeen, N., & Lenardo, M. J. (2001). The TNF and TNF receptor superfamilies: integrating mammalian biology. Cell, 104(4), 487–501. doi:10.1016/S0092-8674(01)00237-9.

    Article  CAS  PubMed  Google Scholar 

  4. Pennica, D., Nedwin, G. E., Hayflick, J. S., Seeburg, P. H., Derynck, R., Palladino, M. A., et al. (1984). Goeddel DV (1984) Human tumour necrosis factor: precursor structure, expression and homology to lymphotoxin. Nature, 312(5996), 724–729.

    Article  CAS  PubMed  Google Scholar 

  5. Ohtsuka, H., Koiwa, M., Hatsugaya, A., Kudo, K., Hoshi, F., Itoh, N., et al. (2001). Relationship between serum TNF activity and insulin resistance in dairy cows affected with naturally occurring fatty liver. Journal of Veterinary Medical Science, 63(9), 1021–1025.

    Article  CAS  PubMed  Google Scholar 

  6. Ho, M. W. (2007). The real bioinformatics revolution—proteins and nucleic acids singing to one another? Science in Society., 2007(33), 42–45.

    Google Scholar 

  7. Cosic, I. (1994). Macromolecular bioactivity: is it resonant interaction between macromolecules?-Theory and applications. IEEE Transaction on Biomedical Engineering, 1994(41), 1101–1114.

    Article  Google Scholar 

  8. Cosic, I. (1995). Virtual spectroscopy for fun and profit. Biotechnology, 1995(13), 236–238.

    Article  Google Scholar 

  9. Cosic, I. (1997). The Resonant Recognition Model of Macromolecular Bioactivity: Theory and Applications. Basel: Birkhauser Verlag.

    Book  Google Scholar 

  10. Cosic, I., Lazar, K., & Cosic, D. (2014). Cellular ageing—telomere, telomerase and progerin analysed using resonant recognition model. MD Medical Data, 6(3), 205–209.

    Google Scholar 

  11. Pirogova, E. & Cosic, I. (2001) Examination of amino acid indexes within the resonant recognition model. Proceedings of the 2nd conference of the Victorian Chapter of the IEEE EMBS (pp. 124–127).

  12. Pirogova, E., Fang, Q., Akay, M., & Cosic, I. (2002). Investigation of the structure and function relationships of Oncogene proteins. Proceeding of the IEEE, 90(12), 1859–1868.

    Article  CAS  Google Scholar 

  13. Almansour, N., Pirogova, E., Coloe, P., Cosic, I., & Istivan, T. (2012). Investigation of cytotoxicity of negative control peptides versus bioactive peptides on skin cancer and normal cells: a comparative study. Future Medicinal Chemistry, 4(12), 1553–1565.

    Article  CAS  PubMed  Google Scholar 

  14. Istivan, T., Pirogova, E., Gan, E., Almansour, N., Coloe, P., & Cosic, I. (2011). Biological effects of a De Novo designed myxoma virus peptide analogue: Evaluation of cytotoxicity on tumor cells. Public Library of Science (PLoS) One, 6(9), 1–10.

    Google Scholar 

  15. Pirogova, E., Istivan, T., Gan, E., & Cosic, I. (2011). Advances in methods for therapeutic peptide discovery, design and development. Current Pharmaceutical Biotechnology, 12(8), 1117–1127.

    Article  CAS  PubMed  Google Scholar 

  16. Cosic, I., & Pirogova, E. (2007). Bioactive Peptide Design using the Resonant Recognition Model. Nonlinear Biomedical Physics. doi:10.1186/1753-4631-1-7.

    PubMed  PubMed Central  Google Scholar 

  17. Krsmanovic, V., Biquard, J. M., Sikorska-Walker, M., Cosic, I., Desgranges, C., Trabaud, M. A., et al. (1998). Investigation into the cross-reactivity of rabbit antibodies raised against nonhomologous pairs of synthetic peptides derived from HIV-1 gp120 proteins. The Journal of Peptide Research, 52(5), 410–412.

    Article  CAS  PubMed  Google Scholar 

  18. Cosic, I., Drummond, A. E., & Underwood, J. R. (1994). Hearn MTW (1994) In vitro inhibition of the actions of basic FGF by a novel 16 amino acid peptides. Molecular and Cellular Biochemistry, 130, 1–9.

    Article  CAS  PubMed  Google Scholar 

  19. Cosic, I., & Hearn, M. T. W. (1991). “Hot Spot” amino acid distribution in Ha-ras oncogene product p21: relationship to guanine binding site. Journal of Molecular Recognition, 4, 57–62.

    Article  CAS  PubMed  Google Scholar 

  20. Cosic, I., & Hearn, M. T. W. (1992). Studies on protein-DNA interactions using the resonant recognition model: Application to repressors and transforming proteins. European Journal of Biochemistry, 205, 613–619.

    Article  CAS  PubMed  Google Scholar 

  21. Cosic, I., Hodder, A. N., Aguilar, M. I., & Hearn, M. T. W. (1991). Resonant recognition model and protein topography: Model studies with myoglobin, haemoglobin and lysozyme. European Journal of Biochemistry, 198, 113–119.

    Article  CAS  PubMed  Google Scholar 

  22. Caceres, J. L. H., Cosic, I., & Cosic, D. (2015). Application of the resonant recognition model to the study of plasmodium proteins involved in malaria infection. MD Medical Data, 7(1), 007–014.

    Google Scholar 

  23. Schmier, S., Mostafa, A., Haarmann, T., Bannert, N., Ziebuhr, J., Veljkovic, V., et al. (2015). In silico prediction and experimental confirmation of HA residues conferring enhanced human receptor specificity of H5N1 influenza A viruses. Scientific Reports, 2015, 5. doi:10.1038/srep11434.

    Google Scholar 

Download references

Acknowledgments

This work was supported by AMALNA Consulting.

Author information

Authors and Affiliations

  1. RMIT University, La Trobe Street, Melbourne, VIC, 3000, Australia

    Irena Cosic

  2. AMALNA Consulting, 46 Second St, Black Rock, VIC, 3193, Australia

    Irena Cosic, Drasko Cosic & Katarina Lazar

Authors
  1. Irena Cosic
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Drasko Cosic
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Katarina Lazar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Irena Cosic.

Ethics declarations

Conflict of interests

The authors declare that they have no conflict of interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cosic, I., Cosic, D. & Lazar, K. Analysis of Tumor Necrosis Factor Function Using the Resonant Recognition Model. Cell Biochem Biophys 74, 175–180 (2016). https://doi.org/10.1007/s12013-015-0716-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12013-015-0716-3

Keywords

Search

Navigation