10
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Computer-aided vaccine designing approach against fish pathogens Edwardsiella tarda and Flavobacterium columnare using bioinformatics softwares

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Edwardsiella tarda and Flavobacterium columnare are two important intracellular pathogenic bacteria that cause the infectious diseases edwardsiellosis and columnaris in wild and cultured fish. Prediction of major histocompatibility complex (MHC) binding is an important issue in T-cell epitope prediction. In a healthy immune system, the T-cells must recognize epitopes and induce the immune response. In this study, T-cell epitopes were predicted by using in silico immunoinformatics approach with the help of bioinformatics tools that are less expensive and are not time consuming. Such identification of binding interaction between peptides and MHC alleles aids in the discovery of new peptide vaccines. We have reported the potential peptides chosen from the outer membrane proteins (OMPs) of E. tarda and F. columnare, which interact well with MHC class I alleles. OMPs from E. tarda and F. columnare were selected and analyzed based on their antigenic and immunogenic properties. The OMPs of the genes TolC and FCOL_04620, respectively, from E. tarda and F. columnare were taken for study. Finally, two epitopes from the OMP of E. tarda exhibited excellent protein–peptide interaction when docked with MHC class I alleles. Five epitopes from the OMP of F. columnare had good protein–peptide interaction when docked with MHC class I alleles. Further in vitro studies can aid in the development of potential peptide vaccines using the predicted peptides.

          Related collections

          Most cited references 49

          • Record: found
          • Abstract: not found
          • Article: not found

          Protein structure prediction using Rosetta.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A semi-empirical method for prediction of antigenic determinants on protein antigens.

            Analysis of data from experimentally determined antigenic sites on proteins has revealed that the hydrophobic residues Cys, Leu and Val, if they occur on the surface of a protein, are more likely to be a part of antigenic sites. A semi-empirical method which makes use of physicochemical properties of amino acid residues and their frequencies of occurrence in experimentally known segmental epitopes was developed to predict antigenic determinants on proteins. Application of this method to a large number of proteins has shown that our method can predict antigenic determinants with about 75% accuracy which is better than most of the known methods. This method is based on a single parameter and thus very simple to use.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Monte Carlo-minimization approach to the multiple-minima problem in protein folding.

               Z Li,  Harold Scheraga (1987)
              A Monte Carlo-minimization method has been developed to overcome the multiple-minima problem. The Metropolis Monte Carlo sampling, assisted by energy minimization, surmounts intervening barriers in moving through successive discrete local minima in the multidimensional energy surface. The method has located the lowest-energy minimum thus far reported for the brain pentapeptide [Met5]enkephalin in the absence of water. Presumably it is the global minimum-energy structure. This supports the concept that protein folding may be a Markov process. In the presence of water, the molecules appear to exist as an ensemble of different conformations.
                Bookmark

                Author and article information

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                1177-8881
                2016
                23 May 2016
                : 10
                : 1703-1714
                Affiliations
                [1 ]Department of Bioinformatics, School of Life Sciences, Vels University, Pallavaram, Chennai, Tamil Nadu, India
                [2 ]Centre for Fish Immunology, School of Life Sciences, Vels University, Pallavaram, Chennai, Tamil Nadu, India
                Author notes
                Correspondence: Radha Mahendran, Department of Bioinformatics, School of Life Sciences, Vels University, Velan Nagar, P.V.Vaithiyalingam Road, Pallavaram, Chennai 600 117, Tamil Nadu, India, Tel +91 90 0323 7145, Fax +91 44 2266 2513, Email mahenradha@ 123456gmail.com
                Article
                dddt-10-1703
                10.2147/DDDT.S95691
                4883809
                27284239
                © 2016 Mahendran et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Comments

                Comment on this article