In South Asia, Haemaphysalis spinigera tick transmits Kyasanur Forest Disease Virus (KFDV), a flavivirus that causes severe hemorrhagic fever with neurological manifestations such as mental disturbances, severe headache, tremors, and vision deficits in infected human beings with a fatality rate of 3–10%. The disease was first reported in March 1957 from Kyasanur forest of Karnataka (India) from sick and dying monkeys. Since then, between 400 and 500 humans cases per year have been recorded; monkeys and small mammals are common hosts of this virus. KFDV can cause epizootics with high fatality in primates and is a level-4 virus according to the international biosafety rules. The density of tick vectors in a given year correlates with the incidence of human disease. The virus is a positive strand RNA virus and its genome was discovered to code for one polyprotein that is cleaved post-translationally into 3 structural proteins (Capsid protein, Envelope Glycoprotein M and Envelope Glycoprotein E) and 7 non-structural proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5). KFDV has a high degree of sequence homology with most members of the TBEV serocomplex. Alkhurma virus is a KFDV variant sharing a sequence similarity of 97%. KFDV is classified as a NIAID Category C priority pathogen due to its extreme pathogenicity and lack of US FDA approved vaccines and therapeutics; also, the infectious dose is currently unknown for KFD. In India, formalin-inactivated KFDV vaccine produced in chick embryo fibroblast is being used. Nevertheless, further efforts are required to enhance its long-term efficacy. KFDV remains an understudied virus and there remains a lack of insight into its pathogenesis; moreover, specific treatment to the disease is not available to date. Environmental and climatic factors involved in disseminating Kyasanur Forest Disease are required to be fully explored. There should be a mapping of endemic areas and cross-border veterinary surveillance needs to be developed in high-risk regions. The involvement of both animal and health sector is pivotal for circumscribing the spread of this disease to new areas.

Human papillomavirus (HPV) induced cervical cancer is the second most common cause of death, after breast cancer, in females. Three prophylactic vaccines by Merck Sharp & Dohme (MSD) and GlaxoSmithKline (GSK) have been confirmed to prevent high-risk HPV strains but these vaccines have been shown to be effective only in girls who have not been exposed to HPV previously. The constitutively expressed HPV oncoproteins E6 and E7 are usually used as target antigens for HPV therapeutic vaccines. These early (E) proteins are involved, for example, in maintaining the malignant phenotype of the cells. In this study, we predicted antigenic peptides of HPV types 16 and 18, encoded by E6 and E7 genes, using an immunoinformatics approach. To further evaluate the immunogenic potential of the predicted peptides, we studied their ability to bind to class I major histocompatibility complex (MHC-I) molecules in a computational docking study that was supported by molecular dynamics (MD) simulations and estimation of the free energies of binding of the peptides at the MHC-I binding cleft. Some of the predicted peptides exhibited comparable binding free energies and/or pattern of binding to experimentally verified MHC-I-binding epitopes that we used as references in MD simulations. Such peptides with good predicted affinity may serve as candidate epitopes for the development of therapeutic HPV peptide vaccines.

Maize Chlorotic Mottle Virus (MCMV) is a deleterious pathogen which causes Maize Lethal Necrosis Disease (MLND) that results in substantial yield loss of Maize crop worldwide. The positive-sense RNA genome of MCMV (4.4 kb) encodes six proteins: P32 (32 kDa protein), RNA dependent RNA polymerases (P50 and P111), P31 (31 kDa protein), P7 (7 kDa protein), coat protein (25 kDa). P31, P7 and coat protein are encoded from sgRNA1, located at the 3′end of the genome and sgRNA2 is located at the extremity of the 3′genome end. The objective of this study is to locate the possible attachment sites of Zea mays derived miRNAs in the genome of MCMV using four diverse miRNA target prediction algorithms. In total, 321 mature miRNAs were retrieved from miRBase (miRNA database) and were tested for hybridization of MCMV genome. These algorithms considered the parameters of seed pairing, minimum free energy, target site accessibility, multiple target sites, pattern recognition and folding energy for attachment. Out of 321 miRNAs only 10 maize miRNAs are predicted for silencing of MCMV genome. The results of this study can hence act as the first step towards the development of MCMV resistant transgenic Maize plants through expression of the selected miRNAs.

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