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ImmunoInformaticsBioinformaticsPeer-reviewed journal article

Epitopedia: identifying molecular mimicry between pathogens and known immune epitopes

Christian A. BalbiniD, Janelle Nunez-CastillaiD, Vitalii StebliankiniD, Prabin BaraliD, Masrur SobhaniD, Trevor CickovskiiD, Ananda Mohan MondaliD, Giri NarasimhaniD, Prem P. ChapagainiD, Kalai MatheeiD, Jessica Siltberg-LiberlesiD

PDFDOIPreprint

Abstract

Upon infection, foreign antigenic proteins stimulate the hosts immune system to produce antibodies targeting the pathogen. These antibodies bind to regions on the antibody called epitopes. Structural similarity (molecular mimicry) of epitopes between an infecting pathogen and host proteins or other pathogenic proteins the host has previously encountered can impact the host immune response to the pathogen and may lead to cross-reactive antibodies. The ability to identify potential regions of molecular mimicry in a pathogen can illuminate immune effects which are especially important to pathogen treatment and vaccine design. Here we present Epitopedia, a software pipeline that facilitates the identification of regions that may exhibit potential three-dimensional molecular mimicry between an antigenic pathogen protein and known immune epitopes as catalogued by the immune epitope database (IEDB). Epitopedia is open-source software released under the MIT license and is freely available on GitHub, including a Docker container with all other software dependencies preinstalled. We performed an analysis describing how various secondary structure states, identity between pentapeptide pairs, and identity between the parent sequences of pentapeptide pairs affects RMSD. We found that pentapeptides pairs in a helical conformation had considerably lower RMSD values than those in Extended or Coil conformations. We also found that RMSD is significantly increased when pentapeptide pairs are from non-homologous sequences.

Citations
14
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