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

Spike-In Proteome Enhances Data-Independent Acquisition for Thermal Proteome Profiling

Target deconvolution is essential for elucidating the molecular mechanisms, therapeutic efficacy, and off-target toxicity of small-molecule drugs. Thermal proteome profiling (TPP) is a robust and popular method for identifying drug-protein interactions. Nevertheless, classical implementation of TPP using isobaric labeling of peptides is tedious, time-consuming, and costly. This prompts the adoption of a label-free approach with data-independent acquisition (DIA), but with substantial compromise in protein coverage and precision. To address these shortcomings, we improvised a spike-in proteome strategy for DIA with TPP to counteract the reduction in protein quantity following sample heating. Protein coverage, data completeness, and quantification precision are significantly improved as result. Additionally, a calibration algorithm was developed to correct for spike-in effects on fold changes. The integration of DIA-TPP with the matrix-augmented pooling strategy (MAPS) to increase experiment throughput demonstrates performance comparable to that of existing TMT-TPP-MAPS. With this spike-in proteome strategy, we also successfully identified the thermal stabilization of CA13 by dorzolamide hydrochloride as well as GSTZ1 and tyrosyl-DNA phosphodiesterase 1 of opicapone that eluded detection without spike-in proteome.

Exploring the anticancer mechanism of cardiac glycosides using proteome integral solubility alteration approach

BACKGROUND AND AIMS

Cardiac glycosides (CGs), traditionally used for heart failure, have shown potential as anti-cancer agents. This study aims to explore their multifaceted mechanisms in cancer cell biology using proteome integral solubility alteration (PISA), focusing on the interaction with key proteins implicated in cellular metabolism and mitochondrial function.

METHODS

We conducted lysate-based and intact-cell PISA assays on cancer cells treated with CGs (Digoxin, Digitoxin, Ouabain) to analyze protein solubility changes. This was followed by mass spectrometric analysis and bioinformatics to identify differentially soluble proteins (DSPs). Molecular docking simulations were performed to predict protein-CG interactions. Public data including gene expression changes upon CG treatment were re-analyzed for validation.

RESULTS

The PISA assays revealed CGs' broad-spectrum interactions, particularly affecting proteins like PKM2, ANXA2, SLC16A1, GOT2 and GLUD1. Molecular docking confirmed stable interactions between CGs and these DSPs. Re-analysis of public data supported the impact of CGs on cancer metabolism and cell signaling pathways.

CONCLUSION

Our findings suggest that CGs could be repurposed for cancer therapy by modulating cellular processes. The PISA data provide insights into the polypharmacological effects of CGs, warranting further exploration of their mechanisms and clinical potential.

Assessing Target Specificity of the Small Molecule Inhibitor MARIMASTAT to Snake Venom Toxins: A Novel Application of Thermal Proteome Profiling

New treatments that circumvent the pitfalls of traditional antivenom therapies are critical to address the problem of snakebite globally. Numerous snake venom toxin inhibitors have shown promising cross-species neutralization of medically significant venom toxins in vivo and in vitro. The development of high-throughput approaches for the screening of such inhibitors could accelerate their identification, testing, and implementation and thus holds exciting potential for improving the treatments and outcomes of snakebite envenomation worldwide. Energetics-based proteomic approaches, including thermal proteome profiling and proteome integral solubility alteration (PISA) assays, represent "deep proteomics" methods for high throughput, proteome-wide identification of drug targets and ligands. In the following study, we apply thermal proteome profiling and PISA methods to characterize the interactions between venom toxin proteoforms in Crotalus atrox (Western Diamondback Rattlesnake) and the snake venom metalloprotease (SVMP) inhibitor marimastat. We investigate its venom proteome-wide effects and characterize its interactions with specific SVMP proteoforms, as well as its potential targeting of non-SVMP venom toxin families. We also compare the performance of PISA thermal window and soluble supernatant with insoluble precipitate using two inhibitor concentrations, providing the first demonstration of the utility of a sensitive high-throughput PISA-based approach to assess the direct targets of small molecule inhibitors for snake venom.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

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.

High-throughput drug target discovery using a fully automated proteomics sample preparation platform

Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.

Identifying drug targets with thermal proteome profiling using IBT-16plex

RATIONALE

Thermal proteome profiling (TPP) has been widely used for the identification of drug targets for several years, and TMTpro-16plex has recently been evaluated for TPP of vehicle- and drug-treated samples in a single labeling process to reduce missing values and save instrument time. A novel isobaric labeling reagent, IBT-16plex, was developed with slightly better performance in protein identification and quantification than the commercially available TMTpro-16plex.

METHODS

In this study, we applied the newly developed IBT-16plex for target identification of methotrexate and panobinostat using TPP.

RESULTS

The known targets of these two drugs were successfully identified with elevated melting temperatures, and some known off-targets and potential new off-targets were also identified.

CONCLUSIONS

IBT-16plex can be a cost-effective replacement for TMTpro-16plex for TPP applications.

Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation

Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .

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.