Saint Louis encephalitis virus, a member of the flaviviridae subgroup, is a culex mosquito-borne pathogen. Despite severe epidemic outbreaks on several occasions, not much progress has been made with regard to an epitope-based vaccine designed for Saint Louis encephalitis virus. The envelope proteins were collected from a protein database and analyzed with an in silico tool to identify the most immunogenic protein. The protein was then verified through several parameters to predict the T-cell and B-cell epitopes. Both T-cell and B-cell immunity were assessed to determine that the protein can induce humoral as well as cell-mediated immunity. The peptide sequence from 330–336 amino acids and the sequence REYCYEATL from the position 57 were found as the most potential B-cell and T-cell epitopes, respectively. Furthermore, as an RNA virus, one important thing was to establish the epitope as a conserved one; this was also done by in silico tools, showing 63.51% conservancy. The epitope was further tested for binding against the HLA molecule by computational docking techniques to verify the binding cleft epitope interaction. However, this is a preliminary study of designing an epitope-based peptide vaccine against Saint Louis encephalitis virus; the results awaits validation by in vitro and in vivo experiments.

In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

The Middle East respiratory syndrome coronavirus (MERS-CoV) is a virus that manifests itself in viral infection with fever, cough, shortness of breath, renal failure and severe acute pneumonia, which often result in a fatal outcome. MERS-CoV has been shown to spread between people who are in close contact. Transmission from infected patients to healthcare personnel has also been observed and is irredeemable with present technology. Genetic studies on MERS-CoV have shown that ORF 1ab encodes replicase polyproteins and play a foremost role in viral infection. Therefore, ORF 1ab replicase polyprotein may be used as suitable target for disease control. Viral activity can be controlled by RNA interference (RNAi) technology, a leading method for post transcriptional gene silencing in a sequence specific manner. However, there is a genetic inconsistency in different viral isolates; it is a great challenge to design potential RNAi (miRNA and siRNA) molecules which can silence the respective target genes rather than any other viral gene simultaneously. In current study four effective miRNA and five siRNA molecules for silencing of nine different strains of MERS-CoV were rationally designed and corroborated using computational methods, which might lead to knockdown the activity of virus. siRNA and miRNA molecules were predicted against ORF1ab gene of different strains of MERS-CoV as effective candidate using computational methods. Thus, this method may provide an insight for the chemical synthesis of antiviral RNA molecule for the treatment of MERS-CoV, at genomic level.

Recent concerning facts of Chikungunya virus (CHIKV); a Togaviridae family alphavirus has proved this as a worldwide emerging threat which causes Chikungunya fever and devitalizing arthritis. Despite severe outbreaks and lack of antiviral drug, a mere progress has been made regarding to an epitope-based vaccine designed for CHIKV. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites by using various immunoinformatics and docking simulation tools. Initially, whole proteome of CHIKV was retrieved from database and perused to identify the most immunogenic protein. Structural properties of the selected protein were analyzed. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell were checked for the selected protein. The peptide region spanning 9 amino acids from 397 to 405 and the sequence YYYELYPTM were found as the most potential B cell and T cell epitopes respectively. This peptide could interact with as many as 19 HLAs and showed high population coverage ranging from 69.50% to 84.94%. By using in silico docking techniques the epitope was further assessed for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post therapeutic strategy, three dimensional structure was predicted along with validation and verification that resulted in molecular docking study to identify the potential drug binding sites and suitable therapeutic inhibitor against targeted protein. Finally, pharmacophore study was also performed in quest of seeing potent drug activity. However, this computational epitope-based peptide vaccine designing and target site prediction against CHIKV opens up a new horizon which may be the prospective way in Chikungunya virus research; the results require validation by in vitro and in vivo experiments.

BackgroundMalaria has been a major life threatening mosquito borne disease from long since. Unavailability of any effective vaccine and recent emergence of multi drug resistant strains of malaria pathogen Plasmodium falciparum continues to cause persistent deaths in the tropical and sub-tropical region. As a result, demands for new targets for more effective anti-malarial drugs are escalating. Transketolase is an enzyme of the pentose phosphate pathway; a novel pathway which is involved in energy generation and nucleic acid synthesis. Moreover, significant difference in homology between Plasmodium falciparum transketolase (Pftk) and human (Homo sapiens) transketolase makes it a suitable candidate for drug therapy. Our present study is aimed to predict the 3D structure of Plasmodium falciparum transketolase and design an inhibitor against it.ResultsThe primary and secondary structural features of the protein is calculated by ProtParam and SOPMA respectively which revealed the protein is composed of 43.3 % alpha helix and 33.04 % random coils along with 15.62 % extended strands, 8.04 % beta turns. The three dimensional structure of the transketolase is constructed using homology modeling tool MODELLAR utilizing several available transketolase structures as templates. The structure is then subjected to deep optimization and validated by structure validation tools PROCHECK, VERIFY 3D, ERRAT, QMEAN. The predicted model scored 0.74 for global model reliability in PROCHECK analysis, which ensures the quality of the model. According to VERIFY 3D the predicted model scored 0.77 which determines good environmental profile along with ERRAT score of 78.313 which is below 95 % rejection limit. Protein-protein and residue–residue interaction networks are generated by STRING and RING server respectively. CASTp server was used to analyze active sites and His 109, Asn 108 and His 515 are found to be more positive site to dock the substrate, in addition molecular docking simulation with Autodock vina determined the estimated free energy of molecular binding was of −6.6 kcal/mol for most favorable binding of 6′-Methyl-Thiamin Diphosphate.ConclusionThis predicted structure of Pftk will serve first hand in the future development of effective Pftk inhibitors with potential anti-malarial activity. However, this is a preliminary study of designing an inhibitor against Plasmodium falciparum 3D7; the results await justification by in vitro and in vivo experimentations.