Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In Protein science : a publication of the Protein Society

The IL-6 family of cytokines, known for their pleiotropic behavior, share binding to the gp130 receptor for signal transduction with the necessity to bind other receptors. Leukemia inhibitory factor receptor is triggered by the IL-6 family proteins: leukemia inhibitory factor (LIF), oncostatin-m (OSM), cardiotrophin-1 (CT-1), ciliary neurotrophic factor (CNTF) and cardiotrophin-like cytokine factor 1 (CLCF1). Besides the conserved binding sites to the receptor, not much is known in terms of diversity and characteristics of these proteins in different organisms. Herein, we describe the sequence analysis of LIF, OSM and CT-1 from several organisms, and m17, a LIF ortholog found in fishes, regarding its phylogenetics, intrinsic properties and the impact of conserved residues on structural features. Sequences were identified in 7 classes of vertebrates, showing high conservation values in binding site III, but protein-dependent results on binding site II. GRAVY, isoelectric point and molecular weight parameters were relevant to differentiate classes in each protein and to enable, for the first time and with high fidelity, the prediction of both organism class and protein type just using machine learning approaches. OSM sequences from primates showed an increased BC loop when compared to the remaining mammals, which could influence binding to OSM receptor and tune signaling pathways. Overall, this study highlights the potential of sequence diversity analysis to understand IL-6 cytokine family evolution, showing conservation of function-related motifs and evolution of class and protein-dependent characteristics. Our results could impact future medical treatment of disorders associated with imbalances in these cytokines. This article is protected by copyright. All rights reserved.

Costa André da, Franco-Duarte Ricardo, Machado Raul, Gomes Andreia C


IL-6 cytokine family, Leukemia inhibitory factor, Machine learning, Protein evolution, Sequence diversity analysis