Avaliação in silico de padrões moleculares associados ao dano (DAMPs) e seus receptores em seres humanos

Abstract

Damage associated molecular patterns (DAMPs) are intracellular molecules that are released into the extracellular environment after cell damage, and are pattern recognition receptors (PRRs) and activate the innate immune system, triggering an inflammatory response. The immune response trigg ered by DAMPs is called sterile inflammation because it is initiated after trauma, ischemia, cellular necrosis, without pathogenic action. Among the PRRs are the Toll -like Receptor (TLRs), the Receptor for Advanced Glycation Endproducts (RAGEs), Interleukin 1 Receptor (IL1R1), Nod-like Receptor (NLRs), and Melanoma 2 Absent Receptor (AIM- 2). These PRRs are expressed in macrophages, dendritic cells and in several other defense cells, and trigger signaling cascades, such as activation of nuclear factor κB (NF-κB), mitogen-activated protein kinase (MAPK), interferon I (IFN- I), phosphatidylinositol-3-kinase (PI3K), inducing transcription of genes for expression of pro inflammatory cytokines and chemokines important in the immune response. Among the most commonly mentioned DAMPs are S100 proteins, Heat Shock Proteins (HSPs) and the High Mobility Box Group 1 (HMGB1). These molecules are closely involved in the etiopathogenesis of chronic diseases such as cancer, diabetes, liver disease, heart disease; and neurodegenerative diseases. In this context, the creation of specific markers that allow the assembly of biological assays, with a view to elucidating the molecular mechanisms implicit in these diseases, is of great relevance. Thus, with the aid of bioinformatics, the present work investigated different human DAMPs and their receptors, obtaining their amino acid sequences, free energy prediction, prediction of epitope antigenicity, similarity analysis and primer designs with the potential to amplify target sequences. The results presented are promising and could be used as immuno modulators or diagnostic and prognostic platforms in various diseases.