Paracrine Induction of HIF by Glutamate in Breast Cancer: EglN1 Senses Cysteine

The HIF transcription factor promotes adaptation to hypoxia and stimulates the growth of certain cancers, including triple-negative breast cancer (TNBC). The HIFα subunit is usually prolyl-hydroxylated by EglN family members under normoxic conditions, causing its rapid degradation. We confirmed that TNBC cells secrete glutamate, which we found is both necessary and sufficient for the paracrine induction of HIF1α in such cells under normoxic conditions. Glutamate inhibits the xCT glutamate-cystine antiporter, leading to intracellular cysteine depletion. EglN1, the main HIFα prolyl-hydroxylase, undergoes oxidative self-inactivation in the absence of cysteine both in biochemical assays and in cells, resulting in HIF1α accumulation. Therefore, EglN1 senses both oxygen and cysteine

sCIP-ing towards streamlined chemoproteomics

Mapping the ligandability or potential druggability of all proteins in the human proteome is a central goal of mass spectrometry-based chemoproteomics. Achieving this ambitious objective requires high throughput and high coverage sample preparation and LC-MS/MS analysis for hundreds to thousands of reactive compounds and chemical probes. Conducting chemoproteomic screens at this scale benefits from technical innovations that achieve increased sample throughput. Multiplexed analysis using commercially available amine-reactive isobaric reagents (e.g. tandem mass tags or TMT) is a favored strategy to decrease instrument acquisition time. These reagents are ideally suited for protein-based quantification applications, with efficient capping and pooling of peptides after sequence specific digestion. The added enrichment steps in nearly all chemoproteomic sample preparation workflows reveals a still largely untapped opportunity for isobaric labeling, namely incorporation of the TMT label into the chemoproteomic enrichment handle for early sample pooling and increased sample preparation throughput. Here we realize this vision by establishing the silane-based Cleavable Linkers for Isotopically-labeled Proteomics (sCIP)-TMT proteomic platform. sCIP-TMT pairs a custom click-compatible sCIP capture reagent that is readily functionalized in high yield with commercially available TMT tags. Synthesis and benchmarking of a 10-plex set of sCIP-TMT reveals a 1.5-fold decrease in sample preparation time together with high coverage and high accuracy quantification. By screening a focused library of cysteine-reactive electrophiles, we demonstrate the utility of sCIP-TMT for chemoproteomic target hunting, identifying 789 total liganded cysteines. Distinguished by its compatibility with established enrichment and quantification protocols, we expect sCIP-TMT will readily translate to a wide range of chemoproteomic applications

New approaches to target RNA binding proteins

RNA binding proteins (RBPs) are a large and diverse class of proteins that regulate all aspects of RNA biology. As RBP dysregulation has been implicated in a number of human disorders, including cancers and neurodegenerative disease, small molecule chemical probes that target individual RBPs represent useful tools for deciphering RBP function and guiding the production of new therapeutics. While RBPs are often thought of as tough-to-drug, the discovery of a number of small molecules that target RBPs has spurred considerable recent interest in new strategies for RBP chemical probe discovery. Here we review current and emerging technologies for high throughput RBP-small molecule screening that we expect will help unlock the full therapeutic potential of this exciting protein class

Introduction to the themed collection on Covalent Drug Discovery

Guest editors Keriann Backus, Zhengying Pan and Lyn Jones introduce the themed collection on Covalent Drug Discovery

Photoaffinity labelling strategies for mapping the small molecule–protein interactome

Nearly all FDA approved drugs and bioactive small molecules exert their effects by binding to and modulating proteins. Consequently, understanding how small molecules interact with proteins at an molecular level is a central challenge of modern chemical biology and drug development. Complementary to structure-guided approaches, chemoproteomics has emerged as a method capable of high-throughput identification of proteins covalently bound by small molecules. To profile noncovalent interactions, established chemoproteomic workflows typically incorporate photoreactive moieties into small molecule probes, which enable trapping of small molecule-protein interactions (SMPIs). This strategy, termed photoaffinity labelling (PAL), has been utilized to profile an array of small molecule interactions, including for drugs, lipids, metabolites, and cofactors. Herein we describe the discovery of photocrosslinking chemistries, including a comparison of the strengths and limitations of implementation of each chemotype in chemoproteomic workflows. In addition, we highlight key examples where photoaffinity labelling has enabled target deconvolution and interaction site mapping

From chemoproteomic‐detected amino acids to genomic coordinates: insights into precise multi‐omic data integration

Abstract The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotype–phenotype associations. Due, in part, to challenges associated with accurate inter‐database mapping, such multi‐omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential “druggability” of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic‐detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase‐8. Our study provides a roadmap for more precise inter‐database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites

Defining the Cell Surface Cysteinome Using Two-Step Enrichment Proteomics

The plasma membrane proteome is a rich resource of functionally important and therapeutically relevant protein targets. Distinguished by high hydrophobicity, heavy glycosylation, disulfide-rich sequences, and low overall abundance, the cell surface proteome remains undersampled in established proteomic pipelines, including our own cysteine chemoproteomics platforms. Here, we paired cell surface glycoprotein capture with cysteine chemoproteomics to establish a two-stage enrichment method that enables chemoproteomic profiling of cell Surface Cysteinome. Our "Cys-Surf" platform captures >2,800 total membrane protein cysteines in 1,046 proteins, including 1,907 residues not previously captured by bulk proteomic analysis. By pairing Cys-Surf with an isotopic chemoproteomic readout, we uncovered 821 total ligandable cysteines, including known and novel sites. Cys-Surf also robustly delineates redox-sensitive cysteines, including cysteines prone to activation-dependent changes to cysteine oxidation state and residues sensitive to addition of exogenous reductants. Exemplifying the capacity of Cys-Surf to delineate functionally important cysteines, we identified a redox sensitive cysteine in the low-density lipoprotein receptor (LDLR) that impacts both the protein localization and uptake of low-density lipoprotein (LDL) particles. Taken together, the Cys-Surf platform, distinguished by its two-stage enrichment paradigm, represents a tailored approach to delineate the functional and therapeutic potential of the plasma membrane cysteinome

From chemoproteomic‐detected amino acids to genomic coordinates: insights into precise multi‐omic data integration

The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotype-phenotype associations. Due, in part, to challenges associated with accurate inter-database mapping, such multi-omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential "druggability" of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic-detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase-8. Our study provides a roadmap for more precise inter-database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites