BackgroundHeparanase, a mammalian endo-β-D-glucuronidase, specifically degrades heparan sulfate proteoglycans ubiquitously associated with the cell surface and extracellular matrix. This single gene encoded enzyme is over-expressed in most human cancers, promoting tumor metastasis and angiogenesis.Principal FindingsWe report that targeted disruption of the murine heparanase gene eliminated heparanase enzymatic activity, resulting in accumulation of long heparan sulfate chains. Unexpectedly, the heparanase knockout (Hpse-KO) mice were fertile, exhibited a normal life span and did not show prominent pathological alterations. The lack of major abnormalities is attributed to a marked elevation in the expression of matrix metalloproteinases, for example, MMP2 and MMP14 in the Hpse-KO liver and kidney. Co-regulation of heparanase and MMPs was also noted by a marked decrease in MMP (primarily MMP-2,-9 and 14) expression following transfection and over-expression of the heparanase gene in cultured human mammary carcinoma (MDA-MB-231) cells. Immunostaining (kidney tissue) and chromatin immunoprecipitation (ChIP) analysis (Hpse-KO mouse embryonic fibroblasts) suggest that the newly discovered co-regulation of heparanase and MMPs is mediated by stabilization and transcriptional activity of β-catenin.Conclusions/SignificanceThe lack of heparanase expression and activity was accompanied by alterations in the expression level of MMP family members, primarily MMP-2 and MMP-14. It is conceivable that MMP-2 and MMP-14, which exert some of the effects elicited by heparanase (i.e., over branching of mammary glands, enhanced angiogenic response) can compensate for its absence, in spite of their different enzymatic substrate. Generation of viable Hpse-KO mice lacking significant abnormalities may provide a promising indication for the use of heparanase as a target for drug development.

Mammalian heparanase degrades heparan sulfate, the most prominent polysaccharide of the extracellular matrix. Causal involvement of heparanase in tumor progression is well documented. Little is known, however, about mechanisms that regulate heparanase gene expression. Mutational inactivation of tumor suppressor p53 is the most frequent genetic alteration in human tumors. p53 is a transcription factor that regulates a wide variety of cellular promoters. In this study, we demonstrate that wild-type (wt) p53 binds to heparanase promoter and inhibits its activity, whereas mutant p53 variants failed to exert an inhibitory effect. Moreover, p53-H175R mutant even activated heparanase promoter activity. Elimination or inhibition of p53 in several cell types resulted in a significant increase in heparanase gene expression and enzymatic activity. Trichostatin A abolished the inhibitory effect of wt p53, suggesting the involvement of histone deacetylation in negative regulation of the heparanase promoter. Altogether, our results indicate that the heparanase gene is regulated by p53 under normal conditions, while mutational inactivation of p53 during cancer development leads to induction of heparanase expression, providing a possible explanation for the frequent increase of heparanase levels observed in the course of tumorigenesis.

Here, we describe an application of the backbone cyclic (BC) proteinomimetic approach to the design and the synthesis of a BC peptide which functionally mimics the nuclear localization signal (NLS) region of the human immunodeficiency virus type 1 matrix protein (HIV-1 MA). On the basis of the NMR structure of HIV-1 MA, a library of BC peptides was designed and screened for the ability to inhibit nuclear import of NLS-BSA in digitonin-permeabilized HeLa and Colo-205 cultured cells. The screening yielded a lead compound (IC50 = 3 microM) which was used for the design of a second library. This library led to the discovery of a highly potent BC peptide, designated BCvir, with an IC50 value of 35 nM. This inhibitory potency is compared to a value of 12 microM exhibited by the linear parent HIV-1 MA NLS peptide. BCvir also reduced HIV-1 production by 75% in infected nondividing cultured human T-cells and was relatively resistant to tryptic digestion. These properties make BCvir a potential candidate for the development of a novel class of antiviral drugs which will be based on blocking nuclear import of viral genomes.

Atomic structures of several proteins from the coronavirus family are still partial or unavailable. A possible reason for this gap is the instability of these proteins outside of the cellular context, thereby prompting the use of in-cell approaches. In situ cross-linking and mass spectrometry (in situ CLMS) can provide information on the structures of such proteins as they occur in the intact cell. Here, we applied targeted in situ CLMS to structurally probe Nsp1, Nsp2, and nucleocapsid (N) proteins from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and obtained cross-link sets with an average density of one cross-link per 20 residues. We then employed integrative modeling that computationally combined the cross-linking data with domain structures to determine full-length atomic models. For the Nsp2, the cross-links report on a complex topology with long-range interactions. Integrative modeling with structural prediction of individual domains by the AlphaFold2 system allowed us to generate a single consistent all-atom model of the full-length Nsp2. The model reveals three putative metal binding sites and suggests a role for Nsp2 in zinc regulation within the replication–transcription complex. For the N protein, we identified multiple intra- and interdomain cross-links. Our integrative model of the N dimer demonstrates that it can accommodate three single RNA strands simultaneously, both stereochemically and electrostatically. For the Nsp1, cross-links with the 40S ribosome were highly consistent with recent cryogenic electron microscopy structures. These results highlight the importance of cellular context for the structural probing of recalcitrant proteins and demonstrate the effectiveness of targeted in situ CLMS and integrative modeling.