In-silico Hierarchical Approach for the Identification of Potential Universal Vaccine Candidates (PUVCs) from Neisseria gonorrhoeae.

Abstract Objectives Resistance to the currently recommended extended-spectrum cephalosporins, which is used to treat Gonorrhea, is increasing continuously and leading to a threat of untreatable infection. It is, therefore, becoming extremely essential to search for new therapeutic strategies to control Gonorrhea. Vaccination may be considered as an effective control measure to control this disease, which is caused by Neisseria gonorrhoeae . Methods In-silico hierarchical approach was used to help identify candidate proteins of N. gonorrhoeae that might contribute significantly in vaccine research. In contrast to the conventional vaccine research which requires at least 10–12 years, the present approach would reduce the time period drastically and help to identify Potential Universal Vaccine Candidates (PUVCs). These proteins were further analyzed for the presence of T-cell and linear B-cell epitopes, by using HLAPred and ABCpred servers respectively, in order to facilitate the identification of Multi Epitope Peptide Vaccine Constructs. Results We have identified 23 non-host candidate proteins, using the proteomic information of four sequenced strains of N. gonorrhoeae namely FA 1090, TCDC_NG08107, NCCP11945 and MS11 and labeled them as PUVCs. Since all these identified 23 PUVCs contained both T cell and B cell epitopes, these have been further reiterated as PUVCs which could be used as promising leads for vaccine development. Conclusions This hierarchical approach is the first comprehensive study to identify potential vaccine candidates which once utilized for vaccine development would surely serve as promising tools for effective control of Gonorrhea.