Targeting CK2 mediated signaling to impair/tackle SARS-CoV-2 infection: a computational biology approach.

BACKGROUND: Similarities in the hijacking mechanisms used by SARS-CoV-2 and several types of cancer, suggest the repurposing of cancer drugs to treat Covid-19. CK2 kinase antagonists have been proposed for cancer treatment. A recent study in cells infected with SARS-CoV-2 found a significant CK2 kinase activity, and the use of a CK2 inhibitor showed antiviral responses. CIGB-300, originally designed as an anticancer peptide, is an antagonist of CK2 kinase activity that binds to the CK2 phospho-acceptor sites. Recent preliminary results show the antiviral activity of CIGB-300 using a surrogate model of coronavirus. Here we present a computational biology study that provides evidence, at the molecular level, of how CIGB-300 may interfere with the SARS-CoV-2 life cycle within infected human cells. METHODS: Sequence analyses and data from phosphorylation studies were combined to predict infection-induced molecular mechanisms that can be interfered by CIGB-300. Next, we integrated data from multi-omics studies and data focusing on the antagonistic effect on the CK2 kinase activity of CIGB-300. A combination of network and functional enrichment analyses was used. RESULTS: Firstly, from the SARS-CoV studies, we inferred the potential incidence of CIGB-300 in SARS-CoV-2 interference on the immune response. Afterwards, from the analysis of multiple omics data, we proposed the action of CIGB-300 from the early stages of viral infections perturbing the virus hijacking of RNA splicing machinery. We also predicted the interference of CIGB-300 in virus-host interactions that are responsible for the high infectivity and the particular immune response to SARS-CoV-2 infection. Furthermore, we provided evidence of how CIGB-300 may participate in the attenuation of phenotypes related to muscle, bleeding, coagulation and respiratory disorders. CONCLUSIONS: Our computational analysis proposes putative molecular mechanisms that support the antiviral activity of CIGB-300.

A self-consistent probabilistic formulation for inference of interactions.

Large molecular interaction networks are nowadays assembled in biomedical researches along with important technological advances. Diverse interaction measures, for which input solely consisting of the incidence of causal-factors, with the corresponding outcome of an inquired effect, are formulated without an obvious mathematical unity. Consequently, conceptual and practical ambivalences arise. We identify here a probabilistic requirement consistent with that input, and find, by the rules of probability theory, that it leads to a model multiplicative in the complement of the effect. Important practical properties are revealed along these theoretical derivations, that has not been noticed before.

Predicting CK2 beta-dependent substrates using linear patterns.

CK2 is a constitutively active Ser/Thr protein kinase deregulated in cancer and other pathologies, responsible for about the 20% of the human phosphoproteome. The holoenzyme is a complex composed of two catalytic (α or α´) and two regulatory (ß) subunits, with individual subunits also coexisting in the cell. In the holoenzyme, CK2ß is a substrate-dependent modulator of kinase activity. Therefore, a comprehensive characterization of CK2 cellular function should firstly address which substrates are phosphorylated exclusively when CK2ß is present (class-III or beta-dependent substrates). However, current experimental constrains limit this classification to a few substrates. Here, we took advantage of motif-based prediction and designed four linear patterns for predicting class-III behavior in sets of experimentally determined CK2 substrates. Integrating high-throughput substrate prediction, functional classification and network analysis, our results suggest that beta-dependent phosphorylation might exert particular regulatory roles in viral infection and biological processes/pathways like apoptosis, DNA repair and RNA metabolism. It also pointed, that human beta-dependent substrates are mainly nuclear, a few of them shuttling between nuclear and cytoplasmic compartments.

Mechanisms of cellular uptake, intracellular transportation, and degradation of CIGB-300, a Tat-conjugated peptide, in tumor cell lines.

CIGB-300 is a cyclic synthetic peptide that induces apoptosis in malignant cells, elicits antitumor activity in cancer animal models, and shows tumor reduction signs when assayed in first-in-human phase I trial in patients with cervical tumors. CIGB-300 impairs phosphorylation by casein kinase 2 through targeting the substrate's phosphoacceptor domain. CIGB-300 was linked to the cell penetrating peptide Tat to facilitate the delivery into cells. Previously, we showed that CIGB-300 had a differential antiproliferative behavior in different tumor cell lines. In this work, we studied differential antiproliferative behavior in terms of cellular uptake, intracellular transportation, and degradation in tumor cell lines with dissimilar sensitivity to CIGB-300. The internalization of CIGB-300 was studied in different malignant cell lines. We found that the cell membrane heparan sulfate proteoglycans act as main receptors for extracellular CIGB-300 uptake. The most sensitive tumor cell lines showed higher intracellular incorporation of CIGB-300 in comparison to less sensitive cell lines. Furthermore, CIGB-300 uptake is time- and concentration-dependent in all studied cell lines. It was shown that CIGB-300 has the ability to penetrate cells mainly by direct membrane translocation. However, a minor proportion of the peptide uses an energy-dependent endocytic pathway mechanism to gain access into cells. CIGB-300 is internalized and transported into cells preferentially by caveolae-mediated endocytosis. Lysosomes are involved in CIGB-300 degradation; highly sensitive cell lines showed degradation at earlier times compared to low sensitive cells. Altogether, our data suggests a mechanism of internalization, vesicular transportation, and degradation for CIGB-300 in tumor cells.