This review proposes a structured immunoinformatics framework tailored for diagnostic applications, addressing the current gap in standardized pipelines compared to well-established workflows in reverse vaccinology. Immunoinformatics integrates experimental immunology with computational approaches to predict antigen-epitope recognition by B and T cell immune receptors, supporting the identification of diagnostic and therapeutic targets. It enables rapid and cost-efficient prediction of peptide-MHC binding affinity and epitope immunogenicity through machine learning models and specialized algorithms trained on curated immunological data sets. Although epitope prediction pipelines are well-established in vaccinology, standardized frameworks for their application in diagnostic assays remain underdeveloped. This gap reflects challenges in integrating and implementing prediction tools within diagnostic development protocols, which demand distinct validation criteria and clinical applicability compared to vaccine design. We examine key methodological developments, and practical applications are illustrated through case studies involving viral, bacterial, parasitic, and fungal pathogens. Drawing from this assessment, we outline a modular pipeline for epitope prioritization that integrates sequence analysis, structural modeling, consensus-based prediction, and validation strategies. Analysis of the current literature suggests that prediction algorithms utilizing artificial intelligence models yield high accuracy in epitope identification. Following experimental validation, this approach demonstrates considerable potential for implementation in diagnostics. This integrative strategy underscores the value of combining AI-driven prediction, structural modeling, and multiepitope design in translational diagnostics. Epitope-centric approaches promise significant advances in biomarker platforms for diagnostics, vaccine development, and therapeutic design. This review highlights the integrative value of widely adopted immunoinformatics tools and their applicability to serological diagnostics.

Antimicrobial resistance is an increasing worldwide public health burden that threatens to make existent antimicrobials obsolete. An important mechanism of antimicrobial resistance is the overexpression of efflux pumps, which reduce the intracellular concentration of antimicrobials. TolC is the outer membrane protein of an efflux pump that has gained attention as a therapeutic target. Little is known about the immune response against TolC. Here we evaluated the immune response against TolC from Escherichia coli. TolC in silico epitope prediction showed several residues that could bind to human antibodies, and we showed that human plasma presented higher titers of anti-TolC IgG and IgA, than IgM. E. coli recombinant TolC protein stimulated macrophages in vitro to produce nitric oxide, as well as IL-6 and TNF-α, assessed by Griess assay and ELISA, respectively. Immunization of mice with TolC intraperitoneally and an in vitro re-stimulation led to increased T cell proliferation and IFNγ production, evaluated by flow cytometry and ELISA, respectively. TolC mouse immunization stimulated anti-TolC IgM and IgG production, with higher levels of IgG1 and IgG2, amongst the IgG subclasses. Anti-TolC murine antibodies could bind to live E. coli and increase bacterial uptake and elimination by macrophages in vitro. Intraperitoneal or intranasal, but not oral, immunizations with inactivated E. coli also led to anti-TolC antibody production. Finally, TolC immunization increased mouse survival rates to antimicrobial-sensitive or resistant E. coli infection. Our results showed that TolC is immunogenic, leading to the production of protective antibodies against E. coli, reinforcing its value as a therapeutic target.

Protein–protein docking is a cornerstone of computational structural biology, yet its reliability for large, multimeric assemblies remains uncertain. Standard workflows typically include geometry optimization or molecular dynamics equilibration to relieve local strains and improve input quality, but the extent to which these preparatory steps alter docking outcomes has not been systematically evaluated. Here, we address this question using the mitochondrial chaperonin Hsp60, a dynamic double-ring complex essential for protein folding, and MIX, a kinetoplastid-specific protein with unresolved function, as a stress test system. By comparing docking predictions across minimized, equilibrated, and ensemble-refined structures of Hsp60 in three conformational states (apo, ATP-bound, and ATP–Hsp10), we show that structural relaxation profoundly reshapes the docking landscape. Minimization alone often yielded favorable scores but localized binding, while longer MD trajectories exposed alternative sites, including central cavity, equatorial ATP pocket, and apical domain, each consistent with distinct regulatory hypotheses. These findings reveal that docking outcomes are highly sensitive to receptor preparation, especially in complexes undergoing large conformational transitions. More broadly, our study highlights an underappreciated vulnerability of docking pipelines and calls for ensemble-based and dynamics-aware approaches when predicting interactions in large biomolecular machines.

Antimicrobial resistance is an increasing worldwide public health burden that threatens to make the existent antimicrobials obsolete. Among the mechanisms of antimicrobial resistance is the overexpression of efflux pumps, such as the AcrA–AcrB–TolC which extrude diverse compounds, reducing the intracellular concentration of antimicrobials. TolC is the outer membrane protein of this pump and has recently gained attention as a therapeutic target. However, little is known about the immune response generated against the TolC protein. Here we evaluated the cellular and humoral immune response against the TolC from Escherichia coli . An in silico epitope prediction of the E. coli TolC showed several residues could bind to human antibodies, and we showed that human plasma presented anti-TolC IgG and IgA antibodies. Gram-negative infected patients presented a slight increase in anti-TolC IgM amounts, compared to controls. Recombinant E. coli TolC protein stimulated macrophages in vitro to produce nitric oxide, as well as IL-6 and TNF-α, assessed by Griess assay and ELISA, respectively. Immunization of mice with TolC intraperitoneally and an in vitro re-stimulation of lymph node cells led to increased percentage of T cell proliferation and IFNγ production, evaluated by flow cytometry and ELISA, respectively. We observed that TolC mouse immunization stimulated anti-TolC IgM and IgG production, with a higher level of IgG1 and IgG2, amongst the IgG subclasses. Finally, TolC IgG from mouse immune serum could bind to live E. coli, increase bacterial uptake by macrophages in vitro . TolC immunized mice had a survival rate increased in 60% post infection with E. coli . Our results showed that TolC is immunogenic, activating macrophages, T and B cells, leading to the production of protective antibodies against E. coli .

Aqui apresentamos a segunda edição da Revista BIOINFO. Nesta nova edição, disponibilizamos 10 novos artigos relacionados a bioinformática e a biologia computacional. BIOINFO é um projeto amplo que engloba um portal (disponível em https://www.bioinfo.com.br), uma rede de divulgação e uma revista digital focada em publicar conteúdo voltado à divulgação científica em bioinformática e biologia computacional escrito em língua portuguesa. Boa leitura!