Nonparametric Analysis of Thermal Proteome Profiles Reveals Novel Drug-binding Proteins

Thermal Proteome Profiling Reveals Insight to Antiproliferative and Pro-Apoptotic Effects of Lagunamide A in the Modulation of DNA Damage Repair

Lagunamide A is a biologically active natural product with a yet unidentified molecular mode of action. Cellular studies revealed that lagunamide A is a potent inhibitor of cancer cell proliferation, promotes apoptosis and causes mitochondrial dysfunction. To decipher the cellular mechanism responsible for these effects, we utilized thermal protein profiling (TPP) and identified EYA3 as a stabilized protein in cells upon lagunamide A treatment. EYA3, involved in the DNA damage repair process, was functionally investigated via siRNA based knockdown studies and corresponding effects of lagunamide A on DNA repair were confirmed. Furthermore, we showed that lagunamide A sensitized tumor cells to treatment with the drug doxorubicin highlighting a putative therapeutic strategy.

Orpinolide disrupts a leukemic dependency on cholesterol transport by inhibiting OSBP

Metabolic alterations in cancer precipitate in associated dependencies that can be therapeutically exploited. To meet this goal, natural product-inspired small molecules can provide a resource of invaluable chemotypes. Here, we identify orpinolide, a synthetic withanolide analog with pronounced antileukemic properties, via orthogonal chemical screening. Through multiomics profiling and genome-scale CRISPR-Cas9 screens, we identify that orpinolide disrupts Golgi homeostasis via a mechanism that requires active phosphatidylinositol 4-phosphate signaling at the endoplasmic reticulum-Golgi membrane interface. Thermal proteome profiling and genetic validation studies reveal the oxysterol-binding protein OSBP as the direct and phenotypically relevant target of orpinolide. Collectively, these data reaffirm sterol transport as a therapeutically actionable dependency in leukemia and motivate ensuing translational investigation via the probe-like compound orpinolide.

Stability-based approaches in chemoproteomics

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

Structure-activity relationship and target investigation of 2-aryl quinolines with nematocidal activity

Within the context of our anthelmintic discovery program, we recently identified and evaluated a quinoline derivative, called ABX464 or obefazimod, as a nematocidal candidate; synthesised a series of analogues which were assessed for activity against the free-living nematode Caenorhabditis elegans; and predicted compound-target relationships by thermal proteome profiling (TPP) and in silico docking. Here, we logically extended this work and critically evaluated the anthelmintic activity of ABX464 analogues on Haemonchus contortus (barber's pole worm) - a highly pathogenic nematode of ruminant livestock. First, we tested a series of 44 analogues on H. contortus (larvae and adults) to investigate the nematocidal pharmacophore of ABX464, and identified one compound with greater potency than the parent compound and showed moderate activity against a select number of other parasitic nematodes (including Ancylostoma, Heligmosomoides and Strongyloides species). Using TPP and in silico modelling studies, we predicted protein HCON_00074590 (a predicted aldo-keto reductase) as a target candidate for ABX464 in H. contortus. Future work aims to optimise this compound as a nematocidal candidate and investigate its pharmacokinetic properties. Overall, this study presents a first step toward the development of a new nematocide.

IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data

IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States-Cellular Thermal Shift Assay) provides a highly resolved means to systematically study the interactions of proteins with other cellular components, including metabolites, nucleic acids and other proteins, at the proteome level, but no freely available and user-friendly data analysis software has been reported. Here, we report IMPRINTS.CETSA, an R package that provides the basic data processing framework for robust analysis of the IMPRINTS-CETSA data format, from preprocessing and normalization to visualization. We also report an accompanying R package, IMPRINTS.CETSA.app, which offers a user-friendly Shiny interface for analysis and interpretation of IMPRINTS-CETSA results, with seamless features such as functional enrichment and mapping to other databases at a single site. For the hit generation part, the diverse behaviors of protein modulations have been typically segregated with a two-measure scoring method, i.e. the abundance and thermal stability changes. We present a new algorithm to classify modulated proteins in IMPRINTS-CETSA experiments by a robust single-measure scoring. In this way, both the numerical changes and the statistical significances of the IMPRINTS information can be visualized on a single plot. The IMPRINTS.CETSA and IMPRINTS.CETSA.app R packages are freely available on GitHub at https://github.com/nkdailingyun/IMPRINTS.CETSA and https://github.com/mgerault/IMPRINTS.CETSA.app, respectively. IMPRINTS.CETSA.app is also available as an executable program at https://zenodo.org/records/10636134.

Comparative structure activity and target exploration of 1,2-diphenylethynes in Haemonchus contortus and Caenorhabditis elegans

Infections and diseases caused by parasitic nematodes have a major adverse impact on the health and productivity of animals and humans worldwide. The control of these parasites often relies heavily on the treatment with commercially available chemical compounds (anthelmintics). However, the excessive or uncontrolled use of these compounds in livestock animals has led to major challenges linked to drug resistance in nematodes. Therefore, there is a need to develop new anthelmintics with novel mechanism(s) of action. Recently, we identified a small molecule, designated UMW-9729, with nematocidal activity against the free-living model organism Caenorhabditis elegans. Here, we evaluated UMW-9729's potential as an anthelmintic in a structure-activity relationship (SAR) study in C. elegans and the highly pathogenic, blood-feeding Haemonchus contortus (barber's pole worm), and explored the compound-target relationship using thermal proteome profiling (TPP). First, we synthesised and tested 25 analogues of UMW-9729 for their nematocidal activity in both H. contortus (larvae and adults) and C. elegans (young adults), establishing a preliminary nematocidal pharmacophore for both species. We identified several compounds with marked activity against either H. contortus or C. elegans which had greater efficacy than UMW-9729, and found a significant divergence in compound bioactivity between these two nematode species. We also identified a UMW-9729 analogue, designated 25, that moderately inhibited the motility of adult female H. contortus in vitro. Subsequently, we inferred three H. contortus proteins (HCON_00134350, HCON_00021470 and HCON_00099760) and five C. elegans proteins (F30A10.9, F15B9.8, B0361.6, DNC-4 and UNC-11) that interacted directly with UMW-9729; however, no conserved protein target was shared between the two nematode species. Future work aims to extend the SAR investigation in these and other parasitic nematode species, and validate individual proteins identified here as possible targets of UMW-9729. Overall, the present study evaluates this anthelmintic candidate and highlights some challenges associated with early anthelmintic investigation.

Experimental and data analysis advances in thermal proteome profiling

Method development for mass spectrometry (MS)-based thermal shift proteomic assays have advanced to probe small molecules with known and unknown protein-ligand interaction mechanisms and specificity, which is predominantly used in characterization of drug-protein interactions. In the discovery of target and off-target protein-ligand interactions, a thorough investigation of method development and their impact on the sensitivity and accuracy of protein-small molecule and protein-protein interactions is warranted. In this review, we discuss areas of improvement at each stage of thermal proteome profiling data analysis that includes processing of MS-based data, method development, and their effect on the overall quality of thermal proteome profiles. We also overview the optimization of experimental strategies and prioritization of an increased number of independent biological replicates over the number of evaluated temperatures.

Ligand Modification-Free Methods for the Profiling of Protein-Environmental Chemical Interactions

Adverse health outcomes caused by environmental chemicals are often initiated via their interactions with proteins. Essentially, one environmental chemical may interact with a number of proteins and/or a protein may interact with a multitude of environmental chemicals, forming an intricate interaction network. Omics-wide protein-environmental chemical interaction profiling (PECI) is of prominent importance for comprehensive understanding of these interaction networks, including the toxicity mechanisms of action (MoA), and for providing systematic chemical safety assessment. However, such information remains unknown for most environmental chemicals, partly due to their vast chemical diversity. In recent years, with the continuous efforts afforded, especially in mass spectrometry (MS) based omics technologies, several ligand modification-free methods have been developed, and new attention for systematic PECI profiling was gained. In this Review, we provide a comprehensive overview on these methodologies for the identification of ligand-protein interactions, including affinity interaction-based methods of affinity-driven purification, covalent modification profiling, and activity-based protein profiling (ABPP) in a competitive mode, physicochemical property changes assessment methods of ligand-directed nuclear magnetic resonance (ligand-directed NMR), MS integrated with equilibrium dialysis for the discovery of allostery systematically (MIDAS), thermal proteome profiling (TPP), limited proteolysis-coupled mass spectrometry (LiP-MS), stability of proteins from rates of oxidation (SPROX), and several intracellular downstream response characterization methods. We expect that the applications of these ligand modification-free technologies will drive a considerable increase in the number of PECI identified, facilitate unveiling the toxicological mechanisms, and ultimately contribute to systematic health risk assessment of environmental chemicals.

Structure activity relationship and target prediction for ABX464 analogues in Caenorhabditis elegans

Global challenges with treatment failures and/or widespread resistance in parasitic worms against commercially available anthelmintics lend impetus to the development of new anthelmintics with novel mechanism(s) of action. The free-living nematode Caenorhabditis elegans is an important model organism used for drug discovery, including the screening and structure-activity investigation of new compounds, and target deconvolution. Previously, we conducted a whole-organism phenotypic screen of the 'Pandemic Response Box' (from Medicines for Malaria Venture, MMV) and identified a hit compound, called ABX464, with activity against C. elegans and a related, parasitic nematode, Haemonchus contortus. Here, we tested a series of 44 synthesized analogues to explore the pharmacophore of activity on C. elegans and revealed five compounds whose potency was similar or greater than that of ABX464, but which were not toxic to human hepatoma (HepG2) cells. Subsequently, we employed thermal proteome profiling (TPP), protein structure prediction and an in silico-docking algorithm to predict ABX464-target candidates. Taken together, the findings from this study contribute significantly to the early-stage drug discovery of a new nematocide based on ABX464. Future work is aimed at validating the ABX464-protein interactions identified here, and at assessing ABX464 and associated analogues against a panel of parasitic nematodes, towards developing a new anthelmintic with a mechanism of action that is distinct from any of the compounds currently-available commercially.

CurveCurator: a recalibrated F-statistic to assess, classify, and explore significance of dose-response curves

Dose-response curves are key metrics in pharmacology and biology to assess phenotypic or molecular actions of bioactive compounds in a quantitative fashion. Yet, it is often unclear whether or not a measured response significantly differs from a curve without regulation, particularly in high-throughput applications or unstable assays. Treating potency and effect size estimates from random and true curves with the same level of confidence can lead to incorrect hypotheses and issues in training machine learning models. Here, we present CurveCurator, an open-source software that provides reliable dose-response characteristics by computing p-values and false discovery rates based on a recalibrated F-statistic and a target-decoy procedure that considers dataset-specific effect size distributions. The application of CurveCurator to three large-scale datasets enables a systematic drug mode of action analysis and demonstrates its scalable utility across several application areas, facilitated by a performant, interactive dashboard for fast data exploration.

Principles and challenges of modeling temporal and spatial omics data

Studies with temporal or spatial resolution are crucial to understand the molecular dynamics and spatial dependencies underlying a biological process or system. With advances in high-throughput omic technologies, time- and space-resolved molecular measurements at scale are increasingly accessible, providing new opportunities to study the role of timing or structure in a wide range of biological questions. At the same time, analyses of the data being generated in the context of spatiotemporal studies entail new challenges that need to be considered, including the need to account for temporal and spatial dependencies and compare them across different scales, biological samples or conditions. In this Review, we provide an overview of common principles and challenges in the analysis of temporal and spatial omics data. We discuss statistical concepts to model temporal and spatial dependencies and highlight opportunities for adapting existing analysis methods to data with temporal and spatial dimensions.

Protein interactome of 3',5'-cAMP reveals its role in regulating the actin cytoskeleton

Identification of protein interactors is ideally suited for the functional characterization of small molecules. 3',5'-cAMP is an evolutionary ancient signaling metabolite largely uncharacterized in plants. To tap into the physiological roles of 3',5'-cAMP, we used a chemo-proteomics approach, thermal proteome profiling (TPP), for the unbiased identification of 3',5'-cAMP protein targets. TPP measures shifts in the protein thermal stability upon ligand binding. Comprehensive proteomics analysis yielded a list of 51 proteins significantly altered in their thermal stability upon incubation with 3',5'-cAMP. The list contained metabolic enzymes, ribosomal subunits, translation initiation factors, and proteins associated with the regulation of plant growth such as CELL DIVISION CYCLE 48. To functionally validate obtained results, we focused on the role of 3',5'-cAMP in regulating the actin cytoskeleton suggested by the presence of actin among the 51 identified proteins. 3',5'-cAMP supplementation affected actin organization by inducing actin-bundling. Consistent with these results, the increase in 3',5'-cAMP levels, obtained either by feeding or by chemical modulation of 3',5'-cAMP metabolism, was sufficient to partially rescue the short hypocotyl phenotype of the actin2 actin7 mutant, severely compromised in actin level. The observed rescue was specific to 3',5'-cAMP, as demonstrated using a positional isomer 2',3'-cAMP, and true for the nanomolar 3',5'-cAMP concentrations reported for plant cells. In vitro characterization of the 3',5'-cAMP-actin pairing argues against a direct interaction between actin and 3',5'-cAMP. Alternative mechanisms by which 3',5'-cAMP would affect actin dynamics, such as by interfering with calcium signaling, are discussed. In summary, our work provides a specific resource, 3',5'-cAMP interactome, as well as functional insight into 3',5'-cAMP-mediated regulation in plants.

Mode of action studies confirm on-target engagement of lysyl-tRNA synthetase inhibitor and lead to new selection marker for Cryptosporidium

Introduction

Cryptosporidiosis is a leading cause of diarrheal-associated morbidity and mortality, predominantly affecting children under 5 years old in low-and-middle-income countries. There is no effective treatment and no vaccine. New therapeutics are emerging from drug discovery efforts. It is critical that mode of action studies are performed alongside drug discovery to ensure the best clinical outcomes. Unfortunately, technology to identify and validate drug targets for Cryptosporidium is severely lacking.

Methods

We used C. parvum lysyl-tRNA synthetase (CpKRS) and DDD01510706 as a target-compound pair to develop both chemical and genetic tools for mode of action studies for Cryptosporidium. We adapted thermal proteome profiling (TPP) for Cryptosporidium, an unbiased approach for target identification.

Results

Using TPP we identified the molecular target of DDD01510706 and confirm that it is CpKRS. Genetic tools confirm that CpKRS is expressed throughout the life cycle and that this target is essential for parasite survival. Parasites genetically modified to over-express CpKRS or parasites with a mutation at the compound-binding site are resistant to treatment with DDD01510706. We leveraged these mutations to generate a second drug selection marker for genetic modification of Cryptosporidium, KRSR. This second selection marker is interchangeable with the original selection marker, NeoR, and expands the range of reverse genetic approaches available to study parasite biology. Due to the sexual nature of the Cryptosporidium life cycle, parental strains containing different drug selection markers can be crossed in vivo.

Discussion

Selection with both drug markers produces highly efficient genetic crosses (>99% hybrid progeny), paving the way for forward genetics approaches in Cryptosporidium.

HnRNP A2/B1 as a potential anti-tumor target for triptolide based on a simplified thermal proteome profiling method using XGBoost

BACKGROUND

Triptolide (TP) is a highly active natural medicinal ingredient with significant potential in anticancer. The strong cytotoxicity of this compound suggests that it may have a wide range of targets within cells. However, further target screening is required at this stage. Traditional drug target screening methods can be significantly optimized using artificial intelligence (AI).

PURPOSE

 This study aimed to identify the direct protein targets and explain the multitarget action mechanism of the anti-tumor effect of TP with the help of AI.

METHODS

 The CCK8, scratch test, and flow cytometry analysis were used to examine cell proliferation, migration, cell cycle, and apoptosis in tumor cells treated with TP in vitro. The anti-tumor effect of TP in vivo was evaluated by constructing a tumor model in nude mice. Furthermore, we established a simplified thermal proteome analysis (TPP) method based on XGBoost (X-TPP) to rapidly screen the direct targets of TP.

RESULTS

We validated the effects of TP on protein targets through RNA immunoprecipitation and pathways by qPCR and Western blotting. TP significantly inhibited tumor cell proliferation and migration and promoted apoptosis in vitro. Continuous administration of TP to tumor mice can significantly suppress tumor tissue size. We verified that TP can affect the thermal stability of HnRNP A2/B1 and exert anti-tumor effects by inhibiting HnRNP A2/B1-PI3K-AKT pathway. Adding siRNA to silence HnRNP A2/B1 also significantly down-regulated expression of AKT and PI3K.

CONCLUSION

The X-TPP method was used to show that TP regulates tumor cell activity through its potential interaction with HnRNP A2/B1.

Thermal unfolding methods in drug discovery

Thermal unfolding methods, applied in both isolated protein and cell-based settings, are increasingly used to identify and characterize hits during early drug discovery. Technical developments over recent years have facilitated their application in high-throughput approaches, and they now are used more frequently for primary screening. Widespread access to instrumentation and automation, the ability to miniaturize, as well as the capability and capacity to generate the appropriate scale and quality of protein and cell reagents have all played a part in these advances. As the nature of drug targets and approaches to their modulation have evolved, these methods have broadened our ability to provide useful chemical start points. Target proteins without catalytic function, or those that may be difficult to express and purify, are amenable to these methods. Here, we provide a review of the applications of thermal unfolding methods applied in hit finding during early drug discovery.

Decoding protein methylation function with thermal stability analysis

Protein methylation is an important modification beyond epigenetics. However, systems analyses of protein methylation lag behind compared to other modifications. Recently, thermal stability analyses have been developed which provide a proxy of a protein functional status. Here, we show that molecular and functional events closely linked to protein methylation can be revealed by the analysis of thermal stability. Using mouse embryonic stem cells as a model, we show that Prmt5 regulates mRNA binding proteins that are enriched in intrinsically disordered regions and involved in liquid-liquid phase separation mechanisms, including the formation of stress granules. Moreover, we reveal a non-canonical function of Ezh2 in mitotic chromosomes and the perichromosomal layer, and identify Mki67 as a putative Ezh2 substrate. Our approach provides an opportunity to systematically explore protein methylation function and represents a rich resource for understanding its role in pluripotency.

CETSA and thermal proteome profiling strategies for target identification and drug discovery of natural products

BACKGROUND

Monitoring target engagement at various stages of drug development is essential for natural product (NP)-based drug discovery and development. The cellular thermal shift assay (CETSA) developed in 2013 is a novel, broadly applicable, label-free biophysical assay based on the principle of ligand-induced thermal stabilization of target proteins, which enables direct assessment of drug-target engagement in physiologically relevant contexts, including intact cells, cell lysates and tissues. This review aims to provide an overview of the work principles of CETSA and its derivative strategies and their recent progress in protein target validation, target identification and drug lead discovery of NPs.

METHODS

A literature-based survey was conducted using the Web of Science and PubMed databases. The required information was reviewed and discussed to highlight the important role of CETSA-derived strategies in NP studies.

RESULTS

After nearly ten years of upgrading and evolution, CETSA has been mainly developed into three formats: classic Western blotting (WB)-CETSA for target validation, thermal proteome profiling (TPP, also known as MS-CETSA) for unbiased proteome-wide target identification, and high-throughput (HT)-CETSA for drug hit discovery and lead optimization. Importantly, the application possibilities of a variety of TPP approaches for the target discovery of bioactive NPs are highlighted and discussed, including TPP-temperature range (TPP-TR), TPP-compound concentration range (TPP-CCR), two-dimensional TPP (2D-TPP), cell surface-TPP (CS-TPP), simplified TPP (STPP), thermal stability shift-based fluorescence difference in 2D gel electrophoresis (TS-FITGE) and precipitate supported TPP (PSTPP). In addition, the key advantages, limitations and future outlook of CETSA strategies for NP studies are discussed.

CONCLUSION

The accumulation of CETSA-based data can significantly accelerate the elucidation of the mechanism of action and drug lead discovery of NPs, and provide strong evidence for NP treatment against certain diseases. The CETSA strategy will certainly bring a great return far beyond the initial investment and open up more possibilities for future NP-based drug research and development.

Investigation of cellular response to the HSP90 inhibition in human cells through thermal proteome profiling

Heat shock proteins are chaperones and they are responsible for protein folding in cells. HSP90 is one of the most important chaperones in human cells, and its inhibition is promising for cancer therapy. However, despite the development of multiple HSP90 inhibitors, none of them has been approved for disease treatment due to unexpected cellular toxicity and side-effects. Hence, a more comprehensive investigation of cellular response to HSP90 inhibitors can aid in a better understanding of the molecular mechanisms of the cytotoxicity and side effects of these inhibitors. The thermal stability shifts of proteins, which represent protein structure and interaction alterations, can provide valuable information complementary to the results obtained from commonly used abundance-based proteomics analysis. Here, we systematically investigated cell response to different HSP90 inhibitors through global quantification of protein thermal stability changes using thermal proteome profiling, together with measurement of protein abundance changes. Besides the targets and potential off-targets of the drugs, proteins with significant thermal stability changes under the HSP90 inhibition are found to be involved in cell stress responses and the translation process. Moreover, proteins with thermal stability shifts under the inhibition are upstream of those with altered expression. These findings indicate that the HSP90 inhibition perturbs cell transcription and translation processes. The current study provides a different perspective for achieving a better understanding of cellular response to the chaperone inhibition.

Deep thermal profiling for detection of functional proteoform groups

The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.

Tandem mass tag-based thermal proteome profiling for the discovery of drug-protein interactions in cancer cells

Identification of effector targets is imperative to the characterization of the mechanisms of action of novel small molecules. Here, we describe steps to identify effector drug-protein interactions in lysates derived from cancer cell lines using a thermal proteome profiling (TPP) protocol. Building on existing TTP approaches, we detail the use of an in-solution trypsin digestion technique to streamline sample preparation, a nonparametric analysis to rank proteins for prioritization, and a follow-up strategy for identifying effector interactors. For complete details on the use and execution of this protocol, please refer to Johnson et al. (2022).1.

CHalf: Folding Stability Made Simple

The structure of a protein defines its function and integrity and correlates with the protein folding stability (PFS). Quantifying PFS allows researchers to assess differential stability of proteins in different disease or ligand binding states, providing insight into protein efficacy and potentially serving as a metric of protein quality. There are a number of mass spectrometry (MS)-based methods to assess PFS, such as Thermal Protein Profiling (TPP), Stability of Proteins from Rates of Oxidation (SPROX), and Iodination Protein Stability Assay (IPSA). Despite the critical value that PFS studies add to the understanding of mechanisms of disease and treatment development, proteomics research is still primarily dominated by concentration-based studies. We found that a major reason for the lack of PFS studies is the lack of a user-friendly data processing tool. Here we present the first user-friendly software, CHalf, with a graphical user interface for calculating PFS. Besides calculating site-specific PFS of a given protein from chemical denature folding stability assays, CHalf is also compatible with thermal denature folding stability assays. CHalf also includes a set of data visualization tools to help identify changes in PFS across protein sequences and in between different treatment conditions. We expect the introduction of CHalf to lower the barrier of entry for researchers to investigate PFS, promoting the usage of PFS in studies. In the long run, we expect this increase in PFS research to accelerate our understanding of the pathogenesis and pathophysiology of disease.

Preclinical efficacy of azacitidine and venetoclax for infant KMT2A-rearranged acute lymphoblastic leukemia reveals a new therapeutic strategy

Infants with KMT2A-rearranged B-cell acute lymphoblastic leukemia (ALL) have a dismal prognosis. Survival outcomes have remained static in recent decades despite treatment intensification and novel therapies are urgently required. KMT2A-rearranged infant ALL cells are characterized by an abundance of promoter hypermethylation and exhibit high BCL-2 expression, highlighting potential for therapeutic targeting. Here, we show that hypomethylating agents exhibit in vitro additivity when combined with most conventional chemotherapeutic agents. However, in a subset of samples an antagonistic effect was seen between several agents. This was most evident when hypomethylating agents were combined with methotrexate, with upregulation of ATP-binding cassette transporters identified as a potential mechanism. Single agent treatment with azacitidine and decitabine significantly prolonged in vivo survival in KMT2A-rearranged infant ALL xenografts. Treatment of KMT2A-rearranged infant ALL cell lines with azacitidine and decitabine led to differential genome-wide DNA methylation, changes in gene expression and thermal proteome profiling revealed the target protein-binding landscape of these agents. The selective BCL-2 inhibitor, venetoclax, exhibited in vitro additivity in combination with hypomethylating or conventional chemotherapeutic agents. The addition of venetoclax to azacitidine resulted in a significant in vivo survival advantage indicating the therapeutic potential of this combination to improve outcome for infants with KMT2A-rearranged ALL.

Protein-Peptide Turnover Profiling reveals the order of PTM addition and removal during protein maturation

Post-translational modifications (PTMs) regulate various aspects of protein function, including degradation. Mass spectrometric methods relying on pulsed metabolic labeling are popular to quantify turnover rates on a proteome-wide scale. Such data have traditionally been interpreted in the context of protein proteolytic stability. Here, we combine theoretical kinetic modeling with experimental pulsed stable isotope labeling of amino acids in cell culture (pSILAC) for the study of protein phosphorylation. We demonstrate that metabolic labeling combined with PTM-specific enrichment does not measure effects of PTMs on protein stability. Rather, it reveals the relative order of PTM addition and removal along a protein's lifetime-a fundamentally different metric. This is due to interconversion of the measured proteoform species. Using this framework, we identify temporal phosphorylation sites on cell cycle-specific factors and protein complex assembly intermediates. Our results thus allow tying PTMs to the age of the modified proteins.

Current and emerging target identification methods for novel antimalarials

New antimalarial compounds with novel mechanisms of action are urgently needed to combat the recent rise in antimalarial drug resistance. Phenotypic high-throughput screens have proven to be a successful method for identifying new compounds, however, do not provide mechanistic information about the molecular target(s) responsible for antimalarial action. Current and emerging target identification methods such as in vitro resistance generation, metabolomics screening, chemoproteomic approaches and biophysical assays measuring protein stability across the whole proteome have successfully identified novel drug targets. This review provides an overview of these techniques, comparing their strengths and weaknesses and how they can be utilised for antimalarial target identification.

Thermal proteome profiling reveals Haemonchus orphan protein HCO_011565 as a target of the nematocidal small molecule UMW-868

Parasitic roundworms (nematodes) cause destructive diseases, and immense suffering in humans and other animals around the world. The control of these parasites relies heavily on anthelmintic therapy, but treatment failures and resistance to these drugs are widespread. As efforts to develop vaccines against parasitic nematodes have been largely unsuccessful, there is an increased focus on discovering new anthelmintic entities to combat drug resistant worms. Here, we employed thermal proteome profiling (TPP) to explore hit pharmacology and to support optimisation of a hit compound (UMW-868), identified in a high-throughput whole-worm, phenotypic screen. Using advanced structural prediction and docking tools, we inferred an entirely novel, parasite-specific target (HCO_011565) of this anthelmintic small molecule in the highly pathogenic, blood-feeding barber’s pole worm, and in other socioeconomically important parasitic nematodes. The “hit-to-target” workflow constructed here provides a unique prospect of accelerating the simultaneous discovery of novel anthelmintics and associated parasite-specific targets.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

Real-Time Cellular Thermal Shift Assay to Monitor Target Engagement

Determining a molecule's mechanism of action is paramount during chemical probe development and drug discovery. The cellular thermal shift assay (CETSA) is a valuable tool to confirm target engagement in cells for a small molecule that demonstrates a pharmacological effect. CETSA directly detects biophysical interactions between ligands and protein targets, which can alter a protein's unfolding and aggregation properties in response to thermal challenge. In traditional CETSA experiments, each temperature requires an individual sample, which restricts throughput and requires substantial optimization. To capture the full aggregation profile of a protein from a single sample, we developed a prototype real-time CETSA (RT-CETSA) platform by coupling a real-time PCR instrument with a CCD camera to detect luminescence. A thermally stable Nanoluciferase variant (ThermLuc) was bioengineered to withstand unfolding at temperatures greater than 90 °C and was compatible with monitoring target engagement events when fused to diverse targets. Utilizing well-characterized inhibitors of lactate dehydrogenase alpha, RT-CETSA showed significant correlation with enzymatic, biophysical, and other cell-based assays. A data analysis pipeline was developed to enhance the sensitivity of RT-CETSA to detect on-target binding. RT-CETSA technology advances capabilities of the CETSA method and facilitates the identification of ligand-target engagement in cells, a critical step in assessing the mechanism of action of a small molecule.

KOPI: Kinase inhibitOr Proteome Impact analysis

Kinase inhibitors often exert on/off-target effects, and efficient data analysis is essential for assessing these effects on the proteome. We developed a workflow for rapidly performing such a proteomic assessment, termed as kinase inhibitor proteome impact analysis (KOPI). We demonstrate KOPI’s utility with staurosporine (STS) on the leukemic K562 cell proteome. We identified systematically staurosporine’s non-kinome interactors, and showed for the first time that it caused paradoxical hyper- and biphasic phosphorylation.

Small Molecule Arranged Thermal Proximity Coaggregation (smarTPCA)-A Novel Approach to Characterize Protein-Protein Interactions in Living Cells by Similar Isothermal Dose-Responses

Chemical biology and the application of small molecules has proven to be a potent perturbation strategy, especially for the functional elucidation of proteins, their networks, and regulators. In recent years, the cellular thermal shift assay (CETSA) and its proteome-wide extension, thermal proteome profiling (TPP), have proven to be effective tools for identifying interactions of small molecules with their target proteins, as well as off-targets in living cells. Here, we asked the question whether isothermal dose-response (ITDR) CETSA can be exploited to characterize secondary effects downstream of the primary binding event, such as changes in post-translational modifications or protein-protein interactions (PPI). By applying ITDR-CETSA to MAPK14 kinase inhibitor treatment of living HL-60 cells, we found similar dose-responses for the direct inhibitor target and its known interaction partners MAPKAPK2 and MAPKAPK3. Extension of the dose-response similarity comparison to the proteome wide level using TPP with compound concentration range (TPP-CCR) revealed not only the known MAPK14 interaction partners MAPKAPK2 and MAPKAPK3, but also the potentially new intracellular interaction partner MYLK. We are confident that dose-dependent small molecule treatment in combination with ITDR-CETSA or TPP-CCR similarity assessment will not only allow discrimination between primary and secondary effects, but will also provide a novel method to study PPI in living cells without perturbation by protein modification, which we named "small molecule arranged thermal proximity coaggregation" (smarTPCA).

Ion-Based Proteome-Integrated Solubility Alteration Assays for Systemwide Profiling of Protein-Molecule Interactions

Unbiased drug target engagement deconvolution and mechanism of action elucidation are major challenges in drug development. Modification-free target engagement methods, such as thermal proteome profiling, have gained increasing popularity in the last several years. However, these methods have limitations, and, in any case, new orthogonal approaches are needed. Here, we present a novel isothermal method for comprehensive characterization of protein solubility alterations using the effect on protein solubility of cations and anions in the Hofmeister series. We combine the ion-based protein precipitation approach with Proteome-Integrated Solubility Alteration (PISA) analysis and use this I-PISA assay to delineate the targets of several anticancer drugs both in cell lysates and intact cells. Finally, we demonstrate that I-PISA can detect solubility changes in minute amounts of sample, opening chemical proteomics applications to small and rare biological material.

Machine learning-based phenotypic screening for postmitotic growth inducers uncover vitamin D3 metabolites as small molecule ribosome agonists

Objectives

To restore tissue growth without increasing the risk for cancer during aging, there is a need to identify small molecule drugs that can increase cell growth without increasing cell proliferation. While there have been numerous high‐throughput drug screens for cell proliferation, there have been few screens for post‐mitotic anabolic growth.

Materials and Methods

A machine learning (ML)‐based phenotypic screening strategy was used to discover metabolites that boost muscle growth. Western blot, qRT‐PCR and immunofluorescence staining were used to evaluate myotube hypertrophy/maturation or protein synthesis. Mass spectrometry (MS)‐based thermal proteome profiling‐temperature range (TPP‐TR) technology was used to identify the protein targets that bind the metabolites. Ribo‐MEGA size exclusion chromatography (SEC) analysis was used to verify whether the ribosome proteins bound to calcitriol.

Results

We discovered both the inactive cholecalciferol and the bioactive calcitriol are amongst the top hits that boost post‐mitotic growth. A large number of ribosomal proteins' melting curves were affected by calcitriol treatment, suggesting that calcitriol binds to the ribosome complex directly. Purified ribosomes directly bound to pure calcitriol. Moreover, we found that calcitriol could increase myosin heavy chain (MHC) protein translation and overall nascent protein synthesis in a cycloheximide‐sensitive manner, indicating that calcitriol can directly bind and enhance ribosomal activity to boost muscle growth.

Conclusion

Through the combined strategy of ML‐based phenotypic screening and MS‐based omics, we have fortuitously discovered a new class of metabolite small molecules that can directly activate ribosomes to promote post‐mitotic growth.

ProSAP: a GUI software tool for statistical analysis and assessment of thermal stability data

The Cellular Thermal Shift Assay (CETSA) plays an important role in drug-target identification, and statistical analysis is a crucial step significantly affecting conclusion. We put forward ProSAP (Protein Stability Analysis Pod), an open-source, cross-platform and user-friendly software tool, which provides multiple methods for thermal proteome profiling (TPP) analysis, nonparametric analysis (NPA), proteome integral solubility alteration and isothermal shift assay (iTSA). For testing the performance of ProSAP, we processed several datasets and compare the performance of different algorithms. Overall, TPP analysis is more accurate with fewer false positive targets, but NPA methods are flexible and free from parameters. For iTSA, edgeR and DESeq2 identify more true targets than t-test and Limma, but when it comes to ranking, the four methods show not much difference. ProSAP software is available at https://github.com/hcji/ProSAP and https://zenodo.org/record/5763315.

Proteome-Wide Deconvolution of Drug Targets and Binding Sites by Lysine Reactivity Profiling

Recently, numerous efforts have been devoted to identifying drug targets and binding sites in complex proteomes, which is of great importance in modern drug discovery. In this study, we developed a robust lysine reactivity profiling method to systematically study drug-binding targets and binding sites at the proteome level. This method is based on the principle that binding of a drug to a specific region of target proteins will change the reactivity of lysine residues that are located at this region, and these changes can be detected with an enrichable and lysine reactive probe. Coupled with data-independent acquisition (DIA), the known target proteins and corresponding binding sites were successfully revealed from K562 cell lysates for three model drugs: geldanamycin, staurosporine, and dasatinib. In addition, the drug-induced conformational changes of certain targets were also revealed by our method during the screening of staurosporine. The screening sensitivity of our method revealed from the screening of stuarosporine and dasatinib was comparable with that of thermal proteome profiling (TPP) or machine learning-based limited proteolysis (LiP-Quant). Overall, 21 and 4 kinase targets, including adenosine 5'-triphosphate (ATP)-binding targets, were identified for staurosporine and dasatinib in K562 cell lysates, respectively. We found that target proteins identified by TPP, LiP-Quant, and our method were complementary, emphasizing that the development of new methods that probe different properties of proteins is of great importance in drug target deconvolution. We also envision further applications of our method in proteome-wide probing multiple events that involve lysine reactivity changes.

Characterization of a small molecule inhibitor of disulfide reductases that induces oxidative stress and lethality in lung cancer cells

Phenotype-based screening can identify small molecules that elicit a desired cellular response, but additional approaches are required to characterize their targets and mechanisms of action. Here, we show that a compound termed LCS3, which selectively impairs the growth of human lung adenocarcinoma (LUAD) cells, induces oxidative stress. To identify the target that mediates this effect, we use thermal proteome profiling (TPP) and uncover the disulfide reductases GSR and TXNRD1 as targets. We confirm through enzymatic assays that LCS3 inhibits disulfide reductase activity through a reversible, uncompetitive mechanism. Further, we demonstrate that LCS3-sensitive LUAD cells are sensitive to the synergistic inhibition of glutathione and thioredoxin pathways. Lastly, a genome-wide CRISPR knockout screen identifies NQO1 loss as a mechanism of LCS3 resistance. This work highlights the ability of TPP to uncover targets of small molecules identified by high-throughput screens and demonstrates the potential therapeutic utility of inhibiting disulfide reductases in LUAD.

Precipitate-Supported Thermal Proteome Profiling Coupled with Deep Learning for Comprehensive Screening of Drug Target Proteins

Although thermal proteome profiling (TPP) acts as a popular modification-free approach for drug target deconvolution, some key problems are still limiting screening sensitivity. In the prevailing TPP workflow, only the soluble fractions are analyzed after thermal treatment, while the precipitate fractions that also contain abundant information of drug-induced stability shifts are discarded; the sigmoid melting curve fitting strategy used for data processing suffers from discriminations for a part of human proteome with multiple transitions. In this study, a precipitate-supported TPP (PSTPP) assay was presented for unbiased and comprehensive analysis of protein-drug interactions at the proteome level. In PSTPP, only these temperatures where significant precipitation is observed were applied to induce protein denaturation and the complementary information contained in both supernatant fractions and precipitate fractions was used to improve the screening specificity and sensitivity. In addition, a novel image recognition algorithm based on deep learning was developed to recognize the target proteins, which circumvented the problems that exist in the sigmoid curve fitting strategy. PSTPP assay was validated by identifying the known targets of methotrexate, raltitrexed, and SNS-032 with good performance. Using a promiscuous kinase inhibitor, staurosporine, we delineated 99 kinase targets with a specificity up to 83% in K562 cell lysates, which represented a significant improvement over the existing thermal shift methods. Furthermore, the PSTPP strategy was successfully applied to analyze the binding targets of rapamycin, identifying the well-known targets, FKBP1A, as well as revealing a few other potential targets.

Assessing target engagement using proteome-wide solvent shift assays

Recent advances in mass spectrometry (MS) have enabled quantitative proteomics to become a powerful tool in the field of drug discovery, especially when applied toward proteome-wide target engagement studies. Similar to temperature gradients, increasing concentrations of organic solvents stimulate unfolding and precipitation of the cellular proteome. This property can be influenced by physical association with ligands and other molecules, making individual proteins more or less susceptible to solvent-induced denaturation. Herein, we report the development of proteome-wide solvent shift assays by combining the principles of solvent-induced precipitation (Zhang et al., 2020) with modern quantitative proteomics. Using this approach, we developed solvent proteome profiling (SPP), which is capable of establishing target engagement through analysis of SPP denaturation curves. We readily identified the specific targets of compounds with known mechanisms of action. As a further efficiency boost, we applied the concept of area under the curve analysis to develop solvent proteome integral solubility alteration (solvent-PISA) and demonstrate that this approach can serve as a reliable surrogate for SPP. We propose that by combining SPP with alternative methods, like thermal proteome profiling, it will be possible to increase the absolute number of high-quality melting curves that are attainable by either approach individually, thereby increasing the fraction of the proteome that can be screened for evidence of ligand binding.

Mapping protein carboxymethylation sites provides insights into their role in proteostasis and cell proliferation

Posttranslational mechanisms play a key role in modifying the abundance and function of cellular proteins. Among these, modification by advanced glycation end products has been shown to accumulate during aging and age-associated diseases but specific protein targets and functional consequences remain largely unexplored. Here, we devise a proteomic strategy to identify sites of carboxymethyllysine modification, one of the most abundant advanced glycation end products. We identify over 1000 sites of protein carboxymethylation in mouse and primary human cells treated with the glycating agent glyoxal. By using quantitative proteomics, we find that protein glycation triggers a proteotoxic response and indirectly affects the protein degradation machinery. In primary endothelial cells, we show that glyoxal induces cell cycle perturbation and that carboxymethyllysine modification reduces acetylation of tubulins and impairs microtubule dynamics. Our data demonstrate the relevance of carboxymethyllysine modification for cellular function and pinpoint specific protein networks that might become compromised during aging.

Thermal Proteome Profiling to Identify Protein-ligand Interactions in the Apicomplexan Parasite Toxoplasma gondii

Toxoplasma gondii is a single-celled eukaryotic parasite that chronically infects a quarter of the global population. In recent years, phenotypic screens have identified compounds that block parasite replication. Unraveling the pathways and molecular mechanisms perturbed by such compounds requires target deconvolution. In parasites, such deconvolution has been achieved via chemogenomic approaches-for example, directed evolution followed by whole-genome sequencing or genome-wide knockout screens. As a proteomic alternative that directly probes the physical interaction between compound and protein, thermal proteome profiling (TPP), also known as the cellular thermal shift assay (CETSA), recently emerged as a method to identify small molecule-target interactions in living cells and cell extracts in a variety of organisms, including unicellular eukaryotic pathogens. Ligand binding induces a thermal stability shift-stabilizing or destabilizing proteins that change conformationally in response to the ligand-that can be measured by mass spectrometry (MS). Cells are incubated with different concentrations of ligand and heated, causing thermal denaturation of proteins. The soluble protein is extracted and quantified with multiplexed, quantitative MS, resulting in thousands of thermal denaturation profiles. Proteins engaging the ligand can be identified by their compound-dependent thermal shift. The protocol provided here can be used to identify ligand-target interactions and assess the impact of environmental or genetic perturbations on the thermal stability of the proteome in T. gondii and other eukaryotic pathogens. Graphic abstract: Thermal proteome profiling for target identification in the apicomplexan parasite T. gondii.

Flavonoid 4,4'-dimethoxychalcone suppresses cell proliferation via dehydrogenase inhibition and oxidative stress aggravation

Flavonoids are natural polyphenolic compounds with a diverse array of biological activities and health-promoting effects. Recent studies have found that 4,4'-dimethoxychalcone (DMC) promoted longevity via autophagy; however, its targets are currently unknown. Herein, we employed an unbiased thermal proteome profiling (TPP) method and identified multiple targets of DMC, including ALDH1A3, ALDH2, and PTGES2. We further determined the dissociation constant (Kd) of DMC and ALDH1A3 to be 2.8 μM using microscale thermophoresis (MST) analysis, which indicated that DMC inhibited ALDH1A3 activity and aggravated cellular oxidative stress. DMC treatment significantly increased cellular reactive oxygen species (ROS) production and inhibited cancer cell growth. Quantitative proteomic analysis showed that DMC upregulated proteins associated with stress-responses and downregulated proteins associated with cell cycle progression, and this was confirmed using cell cycle analysis. Taken together, we showed that TPP is an effective tool with which to identify flavonoid targets and set a precedent for deciphering flavonoid function in the future. We have demonstrated that DMC inhibited cell proliferation via ROS-induced cell cycle arrest and is an anti-proliferative agent in cancer treatment.

Systematic analysis of chemical-protein interactions from zebrafish embryo by proteome-wide thermal shift assay, bridging the gap between molecular interactions and toxicity pathways

The molecular interaction between chemicals and proteins often promotes alteration of cellular function. One of the challenges of the toxicology is to predict the impact of exposure to chemicals. Assessing the impact of exposure implies to understand their mechanism of actions starting from identification of specific protein targets of the interaction. Current methods can mainly predict effects of characterized chemicals with knowledge of its targets, and mechanism of actions. Here, we show that proteome-wide thermal shift methods can identify chemical-protein interactions and the protein targets from bioactive chemicals. We analyzed the identified targets from a soluble proteome extracted from zebrafish embryo, that is a model system for toxicology. To evaluate the utility to predict mechanism of actions, we discussed the applicability in four cases: single chemicals, chemical mixtures, novel chemicals, and novel drugs. Our results showed that this methodology could identify the protein targets, discriminate between protein increasing and decreasing in solubility, and offering additional data to complement the map of intertwined mechanism of actions. We anticipate that the proteome integral solubility alteration (PISA) assay, as it is defined here for the unbiased identification of protein targets of chemicals could bridge the gap between molecular interactions and toxicity pathways. SIGNIFICANCE: One of the challenges of the environmental toxicology is to predict the impact of exposure to chemicals on environment and human health. Our phenotype should be explained by our genotype and the environmental exposure. Genomic methodologies can offer a deep analysis of human genome that alone cannot explain our risks of disease. We are starting to understand the key role of exposure to chemicals on our health and risks of disease. Here, we present a proteomic-based method for the identification of soluble proteins interacting with chemicals in zebrafish embryo and discuss the opportunities to complement the map of toxicity pathway perturbations. We anticipate that this PISA assay could bridge the gap between molecular interactions and toxicity pathways.

Utilizing thermal proteome profiling to identify the molecular targets of anti-leishmanial compounds

Here, we detail our optimized protocol for the identification of drug targets in Leishmania donovani using thermal proteome profiling. This approach is based on the principle that binding of a drug to its protein target can significantly alter the thermal stability of that protein. By monitoring changes in the thermal stability of proteins within drug-treated and untreated cell lysates, using mass spectrometry combined with tandem mass tag labeling, putative targets of the drug can be identified in an unbiased manner. For further details on the use and application of this protocol, please refer to Paradela et al. (2021).

Drug Target Identification in Tissues by Thermal Proteome Profiling

Drug target deconvolution can accelerate the drug discovery process by identifying a drug's targets (facilitating medicinal chemistry efforts) and off-targets (anticipating toxicity effects or adverse drug reactions). Multiple mass spectrometry-based approaches have been developed for this purpose, but thermal proteome profiling (TPP) remains to date the only one that does not require compound modification and can be used to identify intracellular targets in living cells. TPP is based on the principle that the thermal stability of a protein can be affected by its interactions. Recent developments of this approach have expanded its applications beyond drugs and cell cultures to studying protein-drug interactions and biological phenomena in tissues. These developments open up the possibility of studying drug treatment or mechanisms of disease in a holistic fashion, which can result in the design of better drugs and lead to a better understanding of fundamental biology. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The thermal proteome stability profile of Trypanosoma cruzi in epimastigote and trypomastigote life stages

Trypanosoma cruzi is a flagellate protozoa being the etiological agent of Chagas disease, a neglected tropical disease, which still poses a public health problem worldwide. The intricate molecular changes during T. cruzi-host interaction have been explored using different largescale omics techniques. However, protein stability is largely unknown. Thermal proteome profiling (TPP) methodology has the potential to characterize proteome-wide stability highlighting key proteins during T. cruzi infection and life stage transition from the invertebrate to the mammalian host. In the present work, T. cruzi epimastigotes and trypomastigotes cell lysates were subjected to TPP workflow and analyzed by quantitative large-scale mass spectrometry-based proteomics to fit a melting profile for each protein. A total of 2884 proteins were identified and associated to 1741 melting curves being 1370 in trypomastigotes (Tm_AVG 53.53 °C) and 1279 in epimastigotes (Tm_AVG 50.89 °C). A total of 453 proteins were identified with statistically different melting profiles between the two life stages. Proteins associated to pathogenesis and intracellular transport had regulated melting temperatures. Membrane and glycosylated proteins had a higher average Tm in trypomastigotes compared to epimastigotes. This study represents the first large-scale comparison of parasite protein stability between life stages. SIGNIFICANCE: Trypanosoma cruzi, a unicellular flagellate parasite, is the etiological agent of Chagas disease, endemic in South America and affecting more that 7 million people worldwide. There is an intense research to identify novel chemotherapeutic and diagnostic targets of Chagas disease. Proteomic approaches have helped in elucidating the quantitative proteome and PTMs changes of T. cruzi during life cycle transition and upon different biotic and abiotic stimuli. However, a comprehensive knowledge of the protein-protein interaction and protein conformation is still missing. In order to fill this gap, this manuscript elucidates the T. cruzi Y strain proteome-wide thermal stability map in the epimastigote and trypomastigote life stages. Comparison between life stages showed a higher average melting temperature stability for trypomastigotes than epimastigotes indicating a host temperature adaptation. Both presented a selective thermal stability shift for cellular compartments, molecular functions and biological processes based on the T. cruzi life stage. Membrane and glycosylated proteins presented a higher thermal stability in trypomastigotes when compared to the epimastigotes.

Sensitive Measurement of Drug-Target Engagement by a Cellular Thermal Shift Assay with Multiplex Proximity Extension Readout

The ability to monitor target engagement in cellular contexts is a key for successful drug discovery and also valuable in clinical routine. A cellular thermal shift assay (CETSA) provides realistic information about drug binding in cells and tissues, revealing drug-target engagement in clinically relevant samples. The CETSA combined with mass spectrometry (MS) detection can be applied in the early hit identification phase to generate target engagement data for large sets of proteins. However, the analysis is slow, requires substantial amounts of the sample material, and often misses proteins of specific interest. Here, we combined the CETSA and the multiplex proximity extension assay (PEA) for analysis of target engagement of a set of 67 proteins from small amounts of the sample material treated with kinase inhibitors. The results were concordant with the corresponding analyses read out via MS. Our approach allows analyses of large numbers of specific target proteins at high sensitivity in limited sample aliquots. Highly sensitive multiplex CETSA-PEA assays are therefore promising for monitoring drug-target engagement in small sample aliquots in the course of drug development and potentially in clinical settings.

Thermal proteome profiling identifies PIP4K2A and ZADH2 as off-targets of Polo-like kinase 1 inhibitor volasertib

Polo-like kinase 1 (PLK1) is an important cell cycle kinase and an attractive target for anticancer treatments. An ATP-competitive small molecular PLK1 inhibitor, volasertib, has reached phase III in clinical trials in patients with refractory acute myeloid leukemia as a combination treatment with cytarabine. However, severe side effects limited its use. The origin of the side effects is unclear and might be due to insufficient specificity of the drug. Thus, identifying potential off-targets to volasertib is important for future clinical trials and for the development of more specific drugs. In this study, we used thermal proteome profiling (TPP) to identify proteome-wide targets of volasertib. Apart from PLK1 and proteins regulated by PLK1, we identified about 200 potential volasertib off-targets. Comparison of this result with the mass-spectrometry analysis of volasertib-treated cells showed that phosphatidylinositol phosphate and prostaglandin metabolism pathways are affected by volasertib. We confirmed that PIP4K2A and ZADH2-marker proteins for these pathways-are, indeed, stabilized by volasertib. PIP4K2A, however, was not affected by another PLK1 inhibitor onvansertib, suggesting that PIP4K2A is a true off-target of volasertib. Inhibition of these proteins is known to impact both the immune response and fatty acid metabolism and could explain some of the side effects seen in volasertib-treated patients.

A Bayesian semi-parametric model for thermal proteome profiling

The thermal stability of proteins can be altered when they interact with small molecules, other biomolecules or are subject to post-translation modifications. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially determine drug targets and off-targets. Thermal proteome profiling is a highly multiplexed mass-spectrommetry method for monitoring the melting behaviour of thousands of proteins in a single experiment. In essence, thermal proteome profiling assumes that proteins denature upon heating and hence become insoluble. Thus, by tracking the relative solubility of proteins at sequentially increasing temperatures, one can report on the thermal stability of a protein. Standard thermodynamics predicts a sigmoidal relationship between temperature and relative solubility and this is the basis of current robust statistical procedures. However, current methods do not model deviations from this behaviour and they do not quantify uncertainty in the melting profiles. To overcome these challenges, we propose the application of Bayesian functional data analysis tools which allow complex temperature-solubility behaviours. Our methods have improved sensitivity over the state-of-the art, identify new drug-protein associations and have less restrictive assumptions than current approaches. Our methods allows for comprehensive analysis of proteins that deviate from the predicted sigmoid behaviour and we uncover potentially biphasic phenomena with a series of published datasets.

Inflect: Optimizing Computational Workflows for Thermal Proteome Profiling Data Analysis

The CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein-ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures (Tm) and relative melt shifts from proteomics abundance data. Here, we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impact the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and have made the R based program Inflect available for research community use through the CRAN repository [McCracken, N. Inflect: Melt Curve Fitting and Melt Shift Analysis. R package version 1.0.3, 2021]. The Inflect outputs include melt curves for each protein which passes filtering criteria in addition to a data matrix which is directly compatible with downstream packages such as UpsetR for replicate comparisons and identification of biologically relevant changes. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared toward specific applications.

Multiple unbiased approaches identify oxidosqualene cyclase as the molecular target of a promising anti-leishmanial

Phenotypic screening identified a benzothiophene compound with activity against Leishmania donovani, the causative agent of visceral leishmaniasis. Using multiple orthogonal approaches, oxidosqualene cyclase (OSC), a key enzyme of sterol biosynthesis, was identified as the target of this racemic compound and its enantiomers. Whole genome sequencing and screening of a genome-wide overexpression library confirmed that OSC gene amplification is associated with resistance to compound 1. Introduction of an ectopic copy of the OSC gene into wild-type cells reduced susceptibility to these compounds confirming the role of this enzyme in resistance. Biochemical analyses demonstrated the accumulation of the substrate of OSC and depletion of its product in compound (S)-1-treated-promastigotes and cell-free membrane preparations, respectively. Thermal proteome profiling confirmed that compound (S)-1 binds directly to OSC. Finally, modeling and docking studies identified key interactions between compound (S)-1 and the LdOSC active site. Strategies to improve the potency for this promising anti-leishmanial are proposed.

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Genetics and chemo-proteomics identify the target of a promising anti-leishmanial

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Biochemical assays confirm the direct inhibition of oxidosqualene cyclase in cells

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Docking and modeling studies identify key interactions between compound and target

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Strategies to improve the potency of this benzothiophene are proposed

Thermal Proteome Profiling in Zebrafish Reveals Effects of Napabucasin on Retinoic Acid Metabolism

Thermal proteome profiling (TPP) allows for the unbiased detection of drug-target protein engagements in vivo. Traditionally, 1 cell type is used for TPP studies, with the risk of missing important differentially expressed target proteins. The use of whole organisms would circumvent this problem. Zebrafish embryos are amenable to such an approach. Here, we used TPP on whole zebrafish embryo lysate to identify protein targets of napabucasin, a compound that may affect signal transducer and activator of transcription 3 (Stat3) signaling through an ill-understood mechanism. In zebrafish embryos, napabucasin induced developmental defects consistent with inhibition of Stat3 signaling. TPP profiling showed no distinct shift in Stat3 upon napabucasin treatment, but effects were detected on the oxidoreductase, Pora, which might explain effects on Stat3 signaling. Interestingly, thermal stability of several aldehyde dehydrogenases was affected. Moreover, napabucasin activated aldehyde dehydrogenase enzymatic activity in vitro. Aldehyde dehydrogenases have crucial roles in retinoic acid metabolism, and functionally, we validated napabucasin-mediated activation of the retinoic acid pathway in zebrafish in vivo. We conclude that TPP profiling in whole zebrafish embryo lysate is feasible and facilitates direct correlation of in vivo effects of small molecule drugs with their protein targets.