Zinc deficiency causes immune dysfunction. In T lymphocytes, hypozincemia promotes thymus atrophy, polarization imbalance, and altered cytokine production. Zinc supplementation is commonly used to boost immune function to prevent infectious diseases in at-risk populations. However, the molecular players involved in zinc homeostasis in lymphocytes are poorly understood. In this paper, we wanted to determine the identity of the transporter responsible for zinc entry into lymphocytes. First, in human Jurkat cells, we characterized the effect of zinc on proliferation and activation and found that zinc supplementation enhances activation when T lymphocytes are stimulated using anti-CD3/anti-CD28 Abs. We show that zinc entry depends on specific pathways to correctly tune the NFAT, NF-κB, and AP-1 activation cascades. Second, we used various human and murine models to characterize the zinc transporter family, Zip, during T cell activation and found that Zip6 was strongly upregulated early during activation. Therefore, we generated a Jurkat Zip6 knockout (KO) line to study how the absence of this transporter affects lymphocyte physiology. We found that although Zip6KO cells showed no altered zinc transport or proliferation under basal conditions, under activation, these KO cells showed deficient zinc transport and a drastically impaired activation program. Our work shows that zinc entry into activated lymphocytes depends on Zip6 and that this transporter is essential for the correct function of the cellular activation machinery.
Protein-protein interactions (PPIs) in all the molecular aspects that take place both inside and outside cells. However, determining experimentally the structure and affinity of PPIs is expensive and time consuming. Therefore, the development of computational tools, as a complement to experimental methods, is fundamental. Here, we present a computational suite: MODPIN, to model and predict the changes of binding affinity of PPIs. In this approach we use homology modeling to derive the structures of PPIs and score them using state-of-the-art scoring functions. We explore the conformational space of PPIs by generating not a single structural model but a collection of structural models with different conformations based on several templates. We apply the approach to predict the changes in free energy upon mutations and splicing variants of large datasets of PPIs to statistically quantify the quality and accuracy of the predictions. As an example, we use MODPIN to study the effect of mutations in the interaction between colicin endonuclease 9 and colicin endonuclease 2 immune protein from Escherichia coli. Finally, we have compared our results with other state-of-art methods. K E Y W O R D S prediction of binding affinity, protein interaction comparative modeling, protein-protein binding affinity, protein-protein interactions
Background Statistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein–protein interaction (PPI) structures. In previous works we decomposed the statistical potentials in different terms, named Split-Statistical Potentials, accounting for the type of amino acid pairs, their hydrophobicity, solvent accessibility and type of secondary structure. These potentials have been successfully used to identify near-native structures in protein structure prediction, rank protein docking poses, and predict PPI binding affinities. Results Here, we present the SPServer, a web server that applies the Split-Statistical Potentials to analyze protein folds and protein interfaces. SPServer provides global scores as well as residue/residue-pair profiles presented as score plots and maps. This level of detail allows users to: (1) identify potentially problematic regions on protein structures; (2) identify disrupting amino acid pairs in protein interfaces; and (3) compare and analyze the quality of tertiary and quaternary structural models. Conclusions While there are many web servers that provide scoring functions to assess the quality of either protein folds or PPI structures, SPServer integrates both aspects in a unique easy-to-use web server. Moreover, the server permits to locally assess the quality of the structures and interfaces at a residue level and provides tools to compare the local assessment between structures. Server address https://sbi.upf.edu/spserver/.
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