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TECHNOLOGY AND CODE article

Front. Genet.
Sec. Computational Genomics
Volume 15 - 2024 | doi: 10.3389/fgene.2024.1500684

MMPred: a tool to predict peptide mimicry events in MHC class II recognition

Provisionally accepted
Filippo Guerri Filippo Guerri 1,2Valentin Junet Valentin Junet 1,2Judith Farrés Judith Farrés 2Xavier Daura Xavier Daura 1,3,4*
  • 1 Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
  • 2 Anaxomics Biotech SL, Barcelona, Catalonia, Spain
  • 3 Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Catalonia, Spain
  • 4 Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Cerdanyola del Vallès, Spain

The final, formatted version of the article will be published soon.

    We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. Starting with two protein or peptide sets (e.g., from human and SARS-CoV-2), MMPred facilitates the generation, investigation, and testing of mimicry hypotheses by providing epitope predictions specifically for MHC class II alleles, which are frequently implicated in autoimmunity. However, the tool is easily extendable to MHC class I predictions by incorporating pre-trained models from CNN-PepPred and NetMHCpan. To evaluate MMPred's ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbialpeptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. MMPred code and user guide are made freely available at https://github.com/ComputBiol-IBB/MMPRED.

    Keywords: Molecular Mimicry, epitope prediction, Sequence Alignment, MHC class II, autoimmune disease, SARS-CoV-2

    Received: 29 Sep 2024; Accepted: 25 Nov 2024.

    Copyright: © 2024 Guerri, Junet, Farrés and Daura. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xavier Daura, Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.