In silico selection of damage-associated molecular patterns (DAMPS) and their receptors in humans
Keywords:Bioinformatics; Immune system; Innate Immunity; mRNA; Molecular Biology.
Damage-associated molecular patterns (DAMPs) are intracellular molecules released into the extracellular environment after injury. These are recognized by pattern recognition receptors (PRRs) and activate the innate immune system, triggering an inflammatory response. The most commonly studied DAMPs are S100 proteins, Thermal Shock Proteins (HSPs) and High Mobility Box Group 1 (HMGB1). Among the PRRs are the Toll-like Receptor (TLRs), the Receptor for Advanced Glycation End Products (RAGEs), Nod-like Receptor (NLRs) and the Absent Receptor in Melanoma 2 (AIM-2). DAMPs are intimately involved in the etiopathogenesis of chronic diseases such as cancer, diabetes, liver disease, heart disease and neurodegenerative diseases. It is very important to select molecular markers that enable the assembly of biological assays, with a view to elucidating the evaluation of the immune response. The present study evaluated different human DAMPs and their receptors in order to find molecular markers associated with diseases using bioinformatics tools. The screening of messenger RNA (mRNA) amino acid sequences was performed on the NCBI database using the nucleotide tool. Secondary mRNA prediction using RNAStructure and RNA foldWebServer software, epitope antigenicity prediction using the Immune Epitope Database Analysis Resource software and primer design using the Primer-BLAST Platform were evaluated. Considering the best predictions of secondary mRNA from receptors and DAMPs, 104 epitopes and 83 molecular marker candidates were predicted. The results presented are promising and could be used as immunomodulators or as diagnostic and prognostic platforms in various diseases.
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Copyright (c) 2022 Erika Aparecida Oliveira; Rebeca Louise de Araujo Brabosa; Wanderley José Mantovani Bittencourt; Laura Cristina Jardim Porto Pimenta; Luciano José Pereira; Elaine Maria Seles Dorneles; Ana Paula Peconick
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