Homology modeling – a step towards vaccine development by analyzing structure of haemophilus influenza protein, transcriptional regulator H10994

https://doi.org/10.53730/ijhs.v7nS1.14495

Authors

  • Anila Farid Lecturer, Department of Biochemistry, Abbottabad International Medical College, Abbottabad
  • Madeeha Jadoon Assistant Professor, Department of Biochemistry, Women Medical and Dental College, Abbottabad
  • Sofia Shoukat Assistant Professor, Department of Biochemistry, Ayub Medical College, Abbottabad
  • Uzma Faryal Professor and HOD, Department of Biochemistry, Women Medical and Dental College, Abbottabad
  • Bilal Karim Assistant Professor Biochemistry, Islamabad Medical and Dental College, Islamabad
  • Anwar Shahzad Associate Professor, Community Medicine and Public Health AIMI, Abbottabad

Keywords:

Haemophilus influenza, Homology modeling, vaccine development

Abstract

Introduction: Haemophilus influenza is a type of bacterium that is non motile, gram negative and causes poisoning and infection including pneumonia,bronchitis etc. In order to study the resistivity of H.influenza protein, transcription regulator: HI0433, homology modeling is an important step to predict structure. Material and methods: Bioinformatics such as CMR, BLAST, modeller Prcheck and Prosa was carried out to find 3D structure of protein. Results and Discussion: H.influenza has 1792 proteins. Out of these, 456 hypothetical proteins were found. Homology modeling of transcriptional regulator H10994 was done it consists of 8 helices and 7 beta sheets. Ramachandran plot has shown that it consists of 95.2% particles in maximum allowed regions, 2.9 % particles in fewer allowed region, 1.4% particles in inadequate allowed region, 5% particles in disallowed region. Conclusion: By homology modeling of H. influenza, transcriptional regulator protein (HI0433), structure was designed which has provided enough information for vaccine development to control its transcription for causing disease.

Downloads

Download data is not yet available.

References

Arora, D.R. (2007). Textbook of Microbiology, 2nd Edition

Kuhnert, P., Christensen, H. (2008).Pasteurellaceae: Biology, Genomics and Molecular Aspects. Caister Academic Press. ISBN 978-1-904455-34-9.

Ryan, K.J., Ray, C.G., (2004). Sherris Medical Microbiology (4th ed.). McGraw Hill. pp. 396–401. ISBN 0-8385-8529-9.

Chang, C.M., Lauderdale, T.L., Lee, H.C., Lee, N.Y., Wu, C.J., Chen, P.L., Lee C.C., Chen, P.C., Ko, W.C., (2010). Colonisation of fluoroquinolone-resistant Haemophilus influenzae among nursing home residents in southern Taiwan". J. Hosp. Infect. 75 (4): 304–8.

Roberts, M. C. and Soge, O.O., (2011). Characterization of macrolide resistance genes in Haemophilus influenzae isolated from children with cystic fibrosis. J. Antimicrob. Chemother. 66 (1): 100–4.

Bourne, P. E. and Weissig, H. (2003). Structural Bioinformatics. Wiley-Liss

Mosimann, S., Meleshko, R. and James, M.N.G. (1995). A critical assessment of comparative molecular modeling of tertiary structures of proteins. Proteins, 23, 301-317.

Deng W,Liou SR, Plunkett G of human organic cation, Mayhew GF, Rose DJ, Burland V, et al. (2003). Comparative genomics of Salmonella enteric serovar Typhi strains Ty2 and CT18.Journal of bacteriology. 1;185(7):2330-7.

Janson G, Zhang C, Prado MG, Paiardini A. (2017). PyMod 2.0:improvement in protein sequence-structure analysis and homology modeling within PyMOL. Bioinformatics. Feb 1;33(3):444-6.

Dakal TC, Kumar R, Romator D. (2017). Structural modeling of human organic cation transporters.Computational Biology and Chemistry. 1;68:153-6

Costanzi S. (2011). Homology modeling of class ag proteincoupled receptors. In Homology Modeling (pp.259-279).Humana Press. 16. Qiu J, Zang S,Ma Y,Owusu L,Zhou L ,Jiang

Meier A, Soding J. (2015). Automatic prediction of protein 3D. structures by probabilistic multi-template homology modeling. PLoS Comput Biol. 23;(10):e1004343.

Published

13-08-2023

How to Cite

Farid, A., Jadoon, M., Shoukat, S., Faryal, U., Karim, B., & Shahzad, A. (2023). Homology modeling – a step towards vaccine development by analyzing structure of haemophilus influenza protein, transcriptional regulator H10994. International Journal of Health Sciences, 7(S1), 2344–2349. https://doi.org/10.53730/ijhs.v7nS1.14495

Issue

Section

Peer Review Articles