Immunoinformatic identification of the epitope-based vaccine candidates from Maltoporin, FepA and OmpW of Shigella Spp, with molecular docking confirmation

Investigation of the vaccine potential of an in silico designed FepA peptide vaccine against Shigella flexneri in mice model

“…We have selected the peptide candidate from the whole FepA protein of Shigella from our previous immunoinformatics study [36] . Where T-cell epitopes of FepA protein were predicted by the NetCTL and IEDB server using a previously utilized protocol [37] .…”

“…Where T-cell epitopes of FepA protein were predicted by the NetCTL and IEDB server using a previously utilized protocol [37] . A 15aa epitope of FepA has 99.0 % population coverage based on MHC class I and MHC class II and is significantly non-toxic, non-allergic, and immunogenic [36] . This epitope was also shown to have B-cell inducing ability shown bioinformatically.…”

Computational approach for identifying immunogenic epitopes and optimizing peptide vaccine through in-silico cloning against Mycoplasma genitalium

“…The coverage of each epitope in the world population was then computed. Only NIAPISFSFTPFTAA has a population coverage of over 99.53 percent among the most conserved epitopes ( Table 5 ) [ 28 ]. In addition, the population coverage of this epitope is measured in various regions of the globe.…”

“…For MHC-II binding affinity analysis, we extended 9-mer epitopes to 15-mer and determined the IC50 value using the recommended MHC-II binding tool from IEDB. Also, the threshold for MHC-I epitopes was considered at an IC50 value of ≤250 nM and for MHC-II epitopes at a value of ≤100 nM, respectively [ 28 ].…”

A conserved subunit vaccine designed against SARS-CoV-2 variants showed evidence in neutralizing the virus

“…The surface glycoprotein was subjected to a CDD domain search, where the S1 and S2 domain sequences were extracted (Figure S1 ). All four proteins (E, M, S1, and S2) were analyzed for T-cell epitope prediction by adopting the previously used approaches described elsewhere (Bappy et al 2020 ; Islam et al 2020 ; Ullah et al 2021 ). Briefly, the NetCTL v1.2 server (Larsen et al 2007 ) was utilized to predict the most antigenic regions of the proteins by selecting the 9-mer T-cell epitopes based on the interaction with commonly occurring HLA class I supertypes in the human population, i.e., A1, A2, A3, A24, A26, B7, B8, B27, B39, B44, B58, B59, and B62.…”