Biology subjects

Chernobrovkin, A.

Publications and source records attributed to Chernobrovkin, A..

4 recordsLinked to original sources

bioRxiv2024

Proteomic Discovery of RNA-Protein Molecular Clamps Using a Thermal Shift Assay with ATP and RNA (TSAR)

Uncompetitive inhibition is an effective strategy for suppressing dysregulated enzymes and their substrates, but discovery of suitable ligands depends on often-unavailable structural knowledge and serendipity. Hence, despite surging interest in mass spectrometry-based target identification, proteomic studies of substrate-dependent target engagement remain sparse. Herein, we describe a strategy for the discovery of substrate-dependent ligand binding. Using proteome integral solubility alteration (PISA) assays, we show that simple biochemical additives can enable detection of RNA-protein-small molecule complexes in native cell lysates. We apply our approach to rocaglates, molecules that specifically clamp RNA to eukaryotic translation initiation factor 4A (eIF4A), DEAD-box helicase 3X (DDX3X), and potentially other members of the DEAD-box (DDX) helicase family. To identify unexpected interactions, we used a target class-specific thermal window and compared ATP analog and RNA base dependencies for key rocaglate-DDX interactions. We report and validate novel DDX targets of high-profile rocaglates - including the clinical candidate Zotatifin - using limited proteolysis-mass spectrometry and fluorescence polarization (FP) experiments. We also provide structural insight into divergent DDX3X affinities between synthetic rocaglates. Taken together, our study provides a model for screening uncompetitive inhibitors using a chemical proteomics approach and uncovers actionable DDX clamping targets, clearing a path towards characterization of novel molecular clamps and associated RNA helicases.

biochemistry↗

bioRxiv2020

CETSA MS profiling for a comparative assessment of FDA approved antivirals repurposed for COVID-19 therapy identifies Trip13 as a Remdesivir off-target

The reuse of pre-existing small molecules for a novel emerging disease threat is a rapid measure to discover unknown applications for previously validated therapies. A pertinent and recent example where such strategy could be employed is in the fight against COVID-19. Therapies designed or discovered to target viral proteins also have off-target effects on the host proteome when employed in a complex physiological environment. This study aims to assess these host cell targets for a panel of FDA approved antiviral compounds including Remdesivir, using the cellular thermal shift assay (CETSA(R)) coupled to mass spectrometry (CETSA MS) in non-infected cells. CETSA MS is a powerful method to delineate direct and indirect interactions between small molecules and protein targets in intact cells. Biologically active compounds can induce changes in thermal stability, in their primary binding partners as well as in proteins that in turn interact with the direct targets. Such engagement of host targets by antiviral drugs may contribute to the clinical effect against the virus but can also constitute a liability. We present here a comparative study of CETSA molecular target engagement fingerprints of antiviral drugs to better understand the link between off-targets and efficacy.

pharmacology and toxicology↗

bioRxiv2018

System-wide Identification of Enzyme Substrates by Thermal Analysis (SIESTA)

Despite the immense importance of enzyme-substrate reactions, there is a lack of generic and unbiased tools for identifying and prioritizing substrate proteins which are modulated in the structural and functional levels through modification. Here we describe a high-throughput unbiased proteomic method called System-wide Identification and prioritization of Enzyme Substrates by Thermal Analysis (SIESTA). The approach assumes that enzymatic post-translational modification of substrate proteins might change their thermal stability. SIESTA successfully identifies several known and novel substrate candidates for selenoprotein thioredoxin reductase 1, protein kinase B (AKT1) and poly-(ADP-ribose) polymerase-10 systems in up to a depth of 7179 proteins. Wider application of SIESTA can enhance our understanding of the role of enzymes in homeostasis and disease, open new opportunities in investigating the effect of PTMs on signal transduction, and facilitate drug discovery.

biochemistry↗

bioRxiv2018

ProTargetMiner: A proteome signature library of anticancer molecules for functional discovery

We present a publicly available, expandable proteome signature library of anticancer molecules in A549 adenocarcinoma cells. Based on 287 proteomes affected by 56 drugs, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. By employing the specificity concept in partial least square modeling, deconvolution of drug targets and mechanistic proteins is achieved for most compounds, including some kinase inhibitors. We built the first protein co-regulation database that takes into account both protein expression and degradation. A surprising number of strong anti-correlations is found, underscoring the importance of protein repression in cell regulation. Our analysis uncovered a group of proteins with extremely steady expression which are likely essential for core cellular functions. These findings bring about deeper understanding of cell mechanics. Extension of the dataset to novel compounds will facilitate drug design. The introduced specificity concept and modeling scheme are beneficial in other analysis types as well.\n\nStatement of SignificanceProTargetMiner is the first of its kind library of proteome responses of human cancer cells to anticancer molecules. This expandable resource facilitates the deconvolution of drug targets, action mechanisms, and cellular effects. It reveals death modalities, uncovers protein co-regulation and anti-correlation networks and defines the \"untouchable\" proteome essential for core cellular functionalities.

cell biology↗