Computational prediction of B and T-cell epitopes of Kyasanur Forest Disease virus marker proteins towards the development of precise diagnosis and potent subunit vaccine

Abstract

Kyasanur Forest Disease (KFD), also known as ‘monkey fever’, caused by KFD Virus (KFDV), is a highly neglected tropical disease endemic to Western Ghat region of Karnataka, India. Recently, KFD, which is fatal for both monkeys and humans with a mortality rate of 2–10% has been found to spread from its epicenter to neighboring districts and states also. The current ELISA based KFD detection method is very non-specific due to cross-reactivity with other flaviviruses. Further, presently available formalin-inactivated vaccine has been found to be less effective leading to disease susceptibility and severity. To address these, the present study was aimed at predicting the potent specific B and T-cell epitopes of KFDV immunogenic marker proteins using diverse computational tools aiming at developing precise diagnostic method and an effective subunit vaccine. Here, we have chosen E, NS1 and NS5 proteins as markers of KFDV by taking into account of their differential and non-overlapping sequences with selected arboviruses. Based on the linear and nonlinear epitope prediction tools and important biophysical parameters, we identified three potential linear and ten nonlinear B-cell epitopes. We also predicted T-cell epitope peptides which binds to MHC class-I and class-II receptors for the effective T-cell activation. Thus, our molecular docking and molecular dynamics simulation analysis has identified six different T_H-cell epitopes based on the distribution frequency of MHC-II haplotypes in the human population and one T_C-cell epitope from NS5 protein that has maximum interaction with class-I MHC. Overall, we have successfully identified potential B and T-cell epitope marker peptides present in the envelope and two non-structural proteins.

Communicated by Ramaswamy H. Sarma

Keywords:

• KFD
• KFDV
• epitope
• molecular docking
• molecular dynamic simulation

Acknowledgment

Authors are thankful to Dr. Sandeep Telkar, for his help in modelling the 3D structure of proteins. We extend our thanks to Dr. Sharath B. S and Dr. Shivanand Kandagalla for their support in analyzing molecular docking and molecular dynamics simulation data.The authors extend their gratitude to Dr. Santhosh K. N for his assistance in critical reading of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contribution

Dr. N.B. Thippeswamy conceptualized the study, supervised the work, and corrected the manuscript. Mr. Sayad Hafeez was involved in conducting the studies and manuscript writing. Dr. Rajeshwara N. Achur and Dr. S.K. Kiran helped in the study design and data interpretation.

Additional information

Funding

The authors are grateful to VGST- K-FIST (L-II), Karnataka, India, File no. VGST-K-FIST/GRD. no. 343 (2015-17) for the financial assistance provided in conducting this study and Lady Tata Memorial Trust- Junior research Scholarship (2018-2020) and Senior reserch Scholarship (2020-2022)., Mumbai, for providing the Junior Research Fellowship to Mr. Sayad Hafeez.