Self-immunity and the autoimmune network: a molecular perspective to ontogeny and regulation of the immune system

Protein Structure Prediction: Conventional and Deep Learning Perspectives

Protein structure prediction is a way to bridge the sequence-structure gap, one of the main challenges in computational biology and chemistry. Predicting any protein's accurate structure is of paramount importance for the scientific community, as these structures govern their function. Moreover, this is one of the complicated optimization problems that computational biologists have ever faced. Experimental protein structure determination methods include X-ray crystallography, Nuclear Magnetic Resonance Spectroscopy and Electron Microscopy. All of these are tedious and time-consuming procedures that require expertise. To make the process less cumbersome, scientists use predictive tools as part of computational methods, using data consolidated in the protein repositories. In recent years, machine learning approaches have raised the interest of the structure prediction community. Most of the machine learning approaches for protein structure prediction are centred on co-evolution based methods. The accuracy of these approaches depends on the number of homologous protein sequences available in the databases. The prediction problem becomes challenging for many proteins, especially those without enough sequence homologs. Deep learning methods allow for the extraction of intricate features from protein sequence data without making any intuitions. Accurately predicted protein structures are employed for drug discovery, antibody designs, understanding protein-protein interactions, and interactions with other molecules. This article provides a review of conventional and deep learning approaches in protein structure prediction. We conclude this review by outlining a few publicly available datasets and deep learning architectures currently employed for protein structure prediction tasks.

Analysis of IgG subclasses of human antitopoisomerase I autoantibodies suggests chronic B cell stimulation

Antitopoisomerase I autoantibodies are highly specific of scleroderma and are mainly IgG. The present study was designed to evaluate the prevalence of each IgG antitopoisomerase I subclass. An ELISA for the detection of IgG antitopoisomerase I subclasses was standardized and used to study the antibodies from 49 antitopoisomerase I-positive patients identified from a total of 541 patients. Correlations and multivariate analysis were performed to determine the frequency of associations between the IgG antitopoisomerase I subclasses. All IgG antitopoisomerase I subclasses were found. Twelve patients (24.5%) had all four IgG antitopoisomerase I subclasses, 13 (26.5%) had three, 16 (32.7%) had two, and 7 (14.3%) had only one antitopoisomerase I subclass. The presence of all four IgG antitopoisomerase I subclasses suggests that this specific B-cell is the target of multiple activation pathways which indicate that there is a complex T-cell-cytokine-driven process. Together with the absence of other autoantibodies in these sera, our results support the concept of a multiple but highly selected and chronic B-cell activation in scleroderma patients with antitopoisomerase I.

Ontogeny of the immune system and the invisible frontier to immune regulation

The data presented focus on three topics: 1) Self-reactivity of early B cells as a constitutive feature of the immune system; 2) Self-reactive V regions and their possible involvement in immune regulation; and 3) Autoantibodies directed at T cell surface molecules as a new form of direct regulation of the B cell repertoire on the T cell compartment. Evidence is provided for lack of substantial difference in the reactivity of neonatal hybridomas from normal and autoimmune mice, and the proposal is made that the immune systems of normal and autoimmune neonatal mice start with similar characteristics implying that avoidance of autoimmune disease is matter of active regulation through a process learned in ontogeny. Two general possibilities for immune regulation are discussed. One is based on the V regions of self-reactive antibodies and their antigenic determinants. The other is through natural autoantibodies able to interfere with the state of activation of T cells. It is concluded that the role of highly conserved structures like self antigens is to maintain immunoglobulin genes and favor their expression in the incipient immune system so that simple patterns of regulation can be set in motion and made available.

Idiotypic analysis of human anti-topoisomerase I autoantibodies

Anti-topoisomerase I autoantibodies (anti-topo I) are associated with proximal scleroderma and are of prognostic significance in patients with Raynaud's phenomenon. Polyclonal anti-idiotypic sera were raised against affinity-purified anti-topo I from 2 patients with scleroderma (EM, SG) and 1 healthy individual (NM). All 3 anti-topo I preparations expressed immunodominant private Ids in or near the antigen binding site of the autoantibody. Further analysis of Id-EM showed isotypic restriction to IgG and a stable Id-expression over the course of 9 years. Id-SG and Id-NM were expressed on IgG and on IgA. The idiotypic character of anti-topo I closely resembles that of anti-centromere autoantibodies which are associated with the CREST syndrome of scleroderma. The data suggest an antigen-driven process in the origin of autoantibodies in scleroderma.

Idiotypic analysis of human anticentromere autoantibodies

The idiotypes (Ids) of anticentromere antibodies (ACA) have been studied using a fusion protein obtained from cloned cDNA of the major centromere antigen, CENP-B, for isolation of the autoantibodies. IgG-ACA were affinity purified from 4 patient sera and anti-Ids prepared in rabbits. Analysis revealed the existence of two distinct types of immunodominant Ids. One Id is near the antibody combining site and one is framework associated. A longterm longitudinal study of Id expression in a patient who seroconverted from ACA (-) to ACA (+) when she developed Raynaud's phenomenon showed a close correlation between Id expression and ACA titers (r = 0.94). These results may be interpreted as evidence for an autoantigen driven process in the anticentromere immune response.