Prediction of Putative Protein Interactions between Zika Virus and Its Hosts Using Computational Techniques

  • Surendra Kumar Sagar Department of Zoology, Swami Shraddhanand College (University of Delhi), Delhi, India.
  • Manoj Kumar Centre for Economic Studies and Planning, Jawaharlal Nehru University, New Delhi, India.
  • Prithvi Singh Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.
  • Shweta Sankhwar Department of Computer Science, Maitreyi College (University of Delhi), New Delhi, India.
  • Ravins Dohare Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.
Keywords: ZIKV, PPI; hZIKV-similar, Protein Structure, Protein-Interaction Prediction

Abstract

Generally, protein-interaction prediction between the proteins of any host and the virus’s proteins is quite crucial for the infection and the pathogenesis of the virus, which makes it striking target for the development of the therapeutics. The major aim of the present study was to utilize the structure-based approach to predict proteins responsible for the propagation of the ZIKV infection in the host machinery. A computational structure-based approach has been applied for the prediction of interacting proteins. From this methodology, we come up with the interactions which are very crucial for the virus infection propagation into the host’s cellular system. As there is a notable relationship between the Zika virus and the neurodevelopment abnormalities, still there is no specific system underlying which impaired neurological development has not been determined. We encounter some of the interactions which are predicted from the methodology adopted in our work, through which we can say that these are some interactions which cause neuron disorders as the major problem associated with this viral infection.

How to cite this article:
Sagar SK, Kumar M, Singh P, Sankhwar S, Dohare R. Prediction of Putative Protein Interactions between Zika Virus and Its Hosts Using Computational Techniques. J Commun Dis. 2021;53(4):84-96.

DOI: https://doi.org/10.24321/0019.5138.202178

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Published
2021-12-31

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