Biology subjects

Weglarz-Tomczak, E.

Publications and source records attributed to Weglarz-Tomczak, E..

3 recordsLinked to original sources

bioRxiv2020

Discovery of potent inhibitors of PLproCoV2 by screening libraries of selen-containing compounds

A collection of twelve organoselenium compounds, structural analogues of antioxidant drug ebselen were screened for inhibition of the papain-like protease (PLpro) from the acute respiratory syndrome coronavirus 2 (SARS-CoV-2, CoV2). This cysteine protease, being responsible for the hydrolysis of peptide bonds between specific amino acids, plays a critical role in CoV2 replication and in assembly of new viral particles within human cells. The activity of the PLpro CoV2 is essential for the progression of coronavirus disease 2019 (COVID-19) and it constitutes a key target for the development of anti-COVID-19 drugs. Here, we identified four strong inhibitors that bind favorably to the PLpro CoV2 with the IC50 in the nanomolar range.

biochemistry↗

bioRxiv2020

Ebselen as a highly active inhibitor of PLProCoV2

Since December 2019 a novel a coronavirus identified as SARS-CoV-2 or COV2 has been spreading around the world. On the 16th of May around 4.5 million people got infected and over 300,000 died due to the infection of COV2. The effective treatment remains a challenge. Targeted therapeutics are still under investigation. The papain-like protease (PLPro) from the human SARS-CoV-2 coronavirus is a cysteine protease that plays a critical role in virus replication. Its activity is required to process the viral polyprotein into functional, mature subunits. Moreover, COV2 uses this enzyme to modulate the hosts immune system to its own benefit. Therefore, it represents a highly promising target for the development of antiviral drugs. In this work, we discovered that ebselen, a synthetic organoselenium drug molecule with anti-inflammatory, anti-oxidant and cytoprotective activity in mammalian cells and cytotoxicity in lower organisms, is a highly active inhibitor of PLProCoV2. We proved that ebselen is a covalent, fast-binding inhibitor of PLProCoV2 exhibiting a low micromolar potency. Furthermore, we identified a difference between PLPro from SARS-CoV-1 (the corona virus which caused the 2002-2004 outbreak, SARS) and SARS-CoV-2 that allows to explain the difference in dynamics of the replication, and, thus, the disease progression. Namely, we present that they show differences in the binding affinity of substrates that we observed through kinetics and molecular docking studies. Using a novel Approximate Bayesian Computation method we were able to find kinetic constants for both enzymes. Molecular modeling study on the structure of the active site and binding mode of the ebselen with SARS and COV2 showed also significant differences that could explain our observation that ebselen is less active and slower bounding with SARS than COV2. In conclusion, we show that ebselen inhibits the activity of the essential viral enzyme papain-like protease (PLpro) from SARS-COV-2 in low micromolar range.

biochemistry↗

bioRxiv2019

Nature and Nurture integrated through an adjustable Flux Balance Analysis: The impact of cell-nutrition changes on the Warburg effect in hepatocellular carcinoma

How cancer cells utilize nutrients to support their growth and proliferation in complex nutritional systems is still an open question. However, it is certainly determined by both genetics and an environmental-specific context. The interactions between them lead to profound metabolic specialization, such as consuming glucose and glutamine and producing lactate at prodigious rates. To investigate whether and how glucose and glutamine availability impact metabolic specialization, we integrated computational modeling on the genome-scale metabolic reconstruction with an experimental study on cell lines. We used the most comprehensive human metabolic network model to date, Recon3D, to build cell line-specific models. RNA-Seq data was used to specify the activity of genes in each cell line and the uptake rates were quantitatively constrained according to nutrient availability. To integrated both constraints we applied a novel method, named GENSI (Gene Expression and Nutrients Simultaneous Integration), that translates the relative importance of gene expression and nutrient availability data into the metabolic fluxes based on an observed experimental feature(s). We applied GENSI to study hepatocellular carcinoma addiction to glucose/glutamine. We were able to identify that proliferation, and lactate production is associated with the presence of glucose but does not necessarily increase with its concentration when the latter exceeds the physiological concentration. There was no such association with glutamine. We show that the integration of gene expression and nutrient availability data into genome-wide models improves the prediction of metabolic phenotypes.

systems biology↗