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bioRxiv2024

Construction of an Immunoinformatics-Based Multi-Epitope Vaccine Candidate targeting Kyasanur Forest Disease Virus

Kyasanur Forest Disease (KFD) is one of the neglected tick-borne viral zoonoses. KFD virus was initially considered endemic to the Western Ghats region of Karnataka. Still, over the years, there have been reports of its spread to newer areas within and outside Karnataka. The absence of an effective treatment for KFD expedites the need for further research and development of novel vaccines. The present study was designed to develop a multi-epitope vaccine candidate against KFDV using immunoinformatic tools. After analyzing 74 complete KFDV genome sequences for genetic recombination and phylogeny, different prioritized B and T cell epitopes were combined using various linkers to construct the vaccine candidate. Docking analysis of the designed vaccine construct revealed a stable interaction with the TLR2-TLR6 receptor complex. After confirming the stability of the vaccine receptor complex, codon optimization was done to ensure the efficient translation of the designed multi-epitope vaccine in the prokaryotic host system, and the subsequent in-silico cloning into the pET30b(+) expression vector was carried out. Immunoinformatics analysis of the multi-epitope vaccine in the current study is satisfactory as it can significantly accelerate the initial stages of vaccine development by narrowing down potential vaccine candidates and providing insights into their design. Experimental validation of the potential multi-epitope vaccine candidate remains crucial to confirm effectiveness and safety in real-world conditions.

bioinformatics↗

bioRxiv2020

Comparative MD simulations and advanced analytics based studies on wild-type and hot-spot mutant A59G HRas

The Ras family of proteins is known to play an important role in cellular signal transduction. The oncoprotein Ras is also found to be mutated in [~]90% of the pancreatic cancers, of which G12V, G13V, A59G and Q61L are the known hot-spot mutants. These ubiquitous proteins fall in the family of G-proteins, and hence switches between active GTP bound and inactive GDP bound states, which is hindered in most of its oncogenic mutant counterparts. Moreover, Ras being a GTPase has an intrinsic property to hydrolyze GTP to GDP, which is obstructed due to mutations and lends the mutants stuck in constitutively active state leading to oncogenic behavior. In this regard, the present study aims to understand the dynamics involved in the hot-spot mutant A59G-Ras using long classical MD simulations ([~]10{micro}s) and comparing the same with its wild-type counterpart. Advanced analytics using Markov State Model (MSM) based approach has been deployed to comparatively understand the transition path for the wild-type and mutant systems. Roles of crucial residues like Tyr32, Gln61 and Tyr64 have also been established using multivariate PCA analyses. Furthermore, this multivariate PCA analysis also provides crucial features which may be used as reaction coordinates for biased simulations for further studies. The absence of formation of pre-hydrolysis network is also reported for the mutant conformation, using the distance-based analyses (between crucial residues) of the conserved regions. The implications of this study strengthen the hypothesis that the disruption of the pre-hydrolysis network in the mutant A59G ensemble might lead to permanently active oncogenic conformation in the mutant conformers.

biophysics↗