Recent advances in proteome-wide label-free target deconvolution for bioactive small molecules

Celastrol induces DNA damage and cell death in BCR-ABL T315I-mutant CML by targeting YY1 and HMCES

BACKGROUND

Chronic myeloid leukemia (CML) is driven primarily by the constitutively active BCR-ABL fusion oncoprotein. Although the development of tyrosine kinase inhibitors has markedly improved the prognosis of CML patients, it remains a significant challenge to overcome drug-resistant mutations, such as the T315I mutation of BCR-ABL, and achieve treatment-free remission in the clinic.

PURPOSE

The identification of new intervention targets beyond BCR-ABL could provide new perspectives for future research and therapeutic intervention. A network pharmacology analysis was conducted to identify the most promising natural product with anti-CML activity. Celastrol was selected for further analysis to gain insights into its mechanism of action (MoA), with the aim of identifying potential new intervention targets for BCR-ABL T315I-mutant CML.

METHODS

Transcriptomic and proteomic analyses were conducted to systematically investigate the molecular MoA of celastrol in K562T315I cells. To identify the target proteins of celastrol, mass spectrometry-coupled cellular thermal shift assay (MS-CETSA) was carried out, followed by validations with genetic knockdown and overexpression, cell proliferation assay, comet assay, Western blotting, celastrol probe-based in situ labeling and pull-down assay, molecular docking, and biolayer interferometry.

RESULTS

Our multi-omics analyses revealed that celastrol primarily induces DNA damage accumulation and the unfolded protein response in K562T315I cells. Among the twelve most potential celastrol targets, experimental evidence demonstrated that the direct interaction of celastrol with YY1 and HMCES increases the levels of DNA damage, leading to cell death.

CONCLUSION

This study represents the first investigation utilizing a proteome-wide label-free target deconvolution approach, MS-CETSA, to identify the protein targets of celastrol. This study also develops a new systems pharmacology strategy. The findings provide new insights into the multifaceted mechanisms of celastrol and, more importantly, highlight the potential of targeting proteins in DNA damage and repair pathways, particularly YY1 and HMCES, to combat drug-resistant CML.

Cellular thermal shift assay: an approach to identify and assess protein target engagement

INTRODUCTION

A comprehensive and global knowledge of protein target engagement is of vital importance for mechanistic studies and in drug development. Since its initial introduction, the cellular thermal shift assay (CETSA) has proven to be a reliable and flexible technique that can be widely applied to multiple contexts and has profound applications in facilitating the identification and assessment of protein target engagement.

AREAS COVERED

This review introduces the principle of CETSA, elaborates on western blot-based CETSA and MS-based thermal proteome profiling (TPP) as well as the major applications and prospects of these approaches.

EXPERT OPINION

CETSA primarily evaluates a given ligand binding to a particular target protein in cells and tissues with the protein thermal stabilities analyzed by western blot. When coupling mass spectrometry with CETSA, thermal proteome profiling allows simultaneous proteome-wide experiment that greatly increased the efficiency of target engagement evaluation, and serves as a promising strategy to identify protein targets and off-targets as well as protein-protein interactions to uncover the biological effects. The CETSA approaches have broad applications and potentials in drug development and clinical research.

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.

Deep learning enables the discovery of a novel cuproptosis-inducing molecule for the inhibition of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers in the world. The therapeutic outlook for HCC patients has significantly improved with the advent and development of systematic and targeted therapies such as sorafenib and lenvatinib; however, the rise of drug resistance and the high mortality rate necessitate the continuous discovery of effective targeting agents. To discover novel anti-HCC compounds, we first constructed a deep learning-based chemical representation model to screen more than 6 million compounds in the ZINC15 drug-like library. We successfully identified LGOd1 as a novel anticancer agent with a characteristic levoglucosenone (LGO) scaffold. The mechanistic studies revealed that LGOd1 treatment leads to HCC cell death by interfering with cellular copper homeostasis, which is similar to a recently reported copper-dependent cell death named cuproptosis. While the prototypical cuproptosis is brought on by copper ionophore-induced copper overload, mechanistic studies indicated that LGOd1 does not act as a copper ionophore, but most likely by interacting with the copper chaperone protein CCS, thus LGOd1 represents a potentially new class of compounds with unique cuproptosis-inducing property. In summary, our findings highlight the critical role of bioavailable copper in the regulation of cell death and represent a novel route of cuproptosis induction.

Intracellular spatiotemporal metabolism in connection to target engagement

The metabolism in eukaryotic cells is a highly ordered system involving various cellular compartments, which fluctuates based on physiological rhythms. Organelles, as the smallest independent sub-cell unit, are important contributors to cell metabolism and drug metabolism, collectively designated intracellular metabolism. However, disruption of intracellular spatiotemporal metabolism can lead to disease development and progression, as well as drug treatment interference. In this review, we systematically discuss spatiotemporal metabolism in cells and cell subpopulations. In particular, we focused on metabolism compartmentalization and physiological rhythms, including the variation and regulation of metabolic enzymes, metabolic pathways, and metabolites. Additionally, the intricate relationship among intracellular spatiotemporal metabolism, metabolism-related diseases, and drug therapy/toxicity has been discussed. Finally, approaches and strategies for intracellular spatiotemporal metabolism analysis and potential target identification are introduced, along with examples of potential new drug design based on this.

Discovery and validation of PURA as a transcription target of 20(S)-protopanaxadiol: Implications for the treatment of cognitive dysfunction

Background

20(S)-protopanaxadiol (PPD), a ginsenoside metabolite, has prominent benefits for the central nervous system, especially in improving learning and memory. However, its transcriptional targets in brain tissue remain unknown.

Methods

In this study, we first used mass spectrometry-based drug affinity responsive target stability (DARTS) to identify the potential proteins of ginsenosides and intersected them with the transcription factor library. Second, the transcription factor PURA was confirmed as a target of PPD by biolayer interferometry (BLI) and molecular docking. Next, the effect of PPD on the transcriptional levels of target genes of PURA in brain tissues was determined by qRT-PCR. Finally, bioinformatics analysis was used to analyze the potential biological features of these target proteins.

Results

The results showed three overlapping transcription factors between the proteomics of DARTS and transcription factor library. BLI analysis further showed that PPD had a higher direct interaction with PURA than parent ginsenosides. Subsequently, BLI kinetic analysis, molecular docking, and mutations in key amino acids of PURA indicated that PPD specifically bound to PURA. The results of qRT-PCR showed that PPD could increase the transcription levels of PURA target genes in brain. Finally, bioinformatics analysis showed that these target proteins were involved in learning and memory function.

Conclusion

The above-mentioned findings indicate that PURA is a transcription target of PPD in brain, and PPD upregulate the transcription levels of target genes related to cognitive dysfunction by binding PURA, which could provide a chemical and biological basis for the study of treating cognitive impairment by targeting PURA.

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.

Indispensable role of microbes in anticancer drugs and discovery trends

Recent years have seen an increased focus on the advancement of naturally derived products for the treatment of cancer. Since the beginning of recorded history, nature has provided a variety of medicinal agents, and an overwhelming number of drugs that we have today are derived from natural sources. Such natural agents are prominently used to treat several diseases such as diabetes, malaria, Alzheimer's, pulmonary disorders, etc. with cancer being the highlight of this review. Due to the rapid development of resistance to chemotherapeutic drugs, the hunt for effective novel drugs is still a paramount concern in cancer treatment. Moreover, many chemotherapy drugs typically have high toxicity and adverse side effects, which necessitates the need to develop anti-tumor drugs that can be employed to treat deadly tumors with fewer negative effects on health and better efficacy. Isolation of several chemotherapeutic drugs has been conducted from a wide range of natural sources which include plants, microbes, fungi, and marine microorganisms. Considering the trends of previous decades, microbial diversity has grown to play a significant role in the formulation of pharmaceuticals and drugs, especially antibiotics and anti-cancer medications. Microbe-derived antitumor antibiotics such as anthracycline, epothilones, bleomycin, actinomycin, and staurosporine are amongst the widely used cancer chemotherapeutic agents. This review deals majorly with microbe-derived anticancer drugs taking into account their derivatives, mechanism of action, isolation procedures, limitations, and tumors targeted by them. This article also reports the phase of clinical study these drugs are undergoing. Moreover, it intends to portray the indispensable part that these microbes have been playing since time immemorial in the odyssey of chemotherapeutic agents. KEY POINTS: • Microbial diversity contributes heavily towards the formulation of anticancer drugs. • Polypeptides, carbohydrates, and alkaloids are prevalent microbe-based drug classes. • Microbe-derived anticancer agents target various sarcomas, carcinomas, and lymphomas.

Chip-DSF: A rapid screening strategy for drug protein targets

Identification of the drug target of lead compounds is an important means for rapid and efficient drug discovery. Protein chips are a high-throughput protein function analysis technology that has been widely used in screening drug protein targets in recent years. However, the verification of the results after high-throughput protein chip screening is still cumbersome. Based on our mature protein chip preparation platform, we prepared a protein chip containing 150 important high-frequency protein targets and used antibodies to prove the availability of the protein chip. To improve the accuracy of target screening, we combined the label-free differential scanning fluorimetry (DSF) with the protein chip, proposing the Chip-DSF strategy. Subsequently, we tested the method with small molecular ginsenoside-Rg2 (Rg2). The Chip-DSF strategy was used to successfully screen the potential target protein KRAS(G12C) of Rg2. Consistently, we found that Rg2 could inhibit NCI-H23 cell proliferation by inducing cell cycle arrest. Also, we found that Rg2 could reduce the amount of KRAS protein and inhibit the phosphorylation of KRAS downstream key signaling protein ERK1, RPS6, and P70S6K in NCI-H23 cells. Collectively, our Chip-DSF strategy could achieve rapid target verification which improved the accuracy and efficiency of target screening of protein chips.

Identification of antimalarial targets of chloroquine by a combined deconvolution strategy of ABPP and MS-CETSA

BACKGROUND

Malaria is a devastating infectious disease that disproportionally threatens hundreds of millions of people in developing countries. In the history of anti-malaria campaign, chloroquine (CQ) has played an indispensable role, however, its mechanism of action (MoA) is not fully understood.

METHODS

We used the principle of photo-affinity labeling and click chemistry-based functionalization in the design of a CQ probe and developed a combined deconvolution strategy of activity-based protein profiling (ABPP) and mass spectrometry-coupled cellular thermal shift assay (MS-CETSA) that identified the protein targets of CQ in an unbiased manner in this study. The interactions between CQ and these identified potential protein hits were confirmed by biophysical and enzymatic assays.

RESULTS

We developed a novel clickable, photo-affinity chloroquine analog probe (CQP) which retains the antimalarial activity in the nanomole range, and identified a total of 40 proteins that specifically interacted and photo-crosslinked with CQP which was inhibited in the presence of excess CQ. Using MS-CETSA, we identified 83 candidate interacting proteins out of a total of 3375 measured parasite proteins. At the same time, we identified 8 proteins as the most potential hits which were commonly identified by both methods.

CONCLUSIONS

We found that CQ could disrupt glycolysis and energy metabolism of malarial parasites through direct binding with some of the key enzymes, a new mechanism that is different from its well-known inhibitory effect of hemozoin formation. This is the first report of identifying CQ antimalarial targets by a parallel usage of labeled (ABPP) and label-free (MS-CETSA) methods.

Identification of Adenylate Kinase 5 as a Protein Target of Ginsenosides in Brain Tissues Using Mass Spectrometry-Based Drug Affinity Responsive Target Stability (DARTS) and Cellular Thermal Shift Assay (CETSA) Techniques

Ginseng is a very famous Chinese herbal medicine with various pharmacological effects. Ginsenosides, the main effective compounds of ginseng, show favorable biological activities in the central nervous system (CNS), but the protein targets of ginsenosides in brain tissues have not been clarified clearly. First, we screened proteins that interact with ginsenosides by mass spectrometry-based drug affinity responsive target stability (DARTS) and cellular thermal shift assay (CETSA). Then, we identified and confirmed adenylate kinase 5 (AK5) as a target protein of ginsenosides by biolayer interferometry (BLI), isothermal titration calorimetry (ITC), and molecular docking. Finally, an enzyme activity kit was used to determine the effect of 20(S)-protopanaxadiol (PPD), a ginseng saponin metabolite, on AK5 activities in vivo and in vitro. We screened out seven overlapping target proteins by proteomics of DARTS and CETSA. The BLI direct action assays showed that the direct interaction of PPD with AK5 was higher compared to the parental ginsenosides. Subsequently, BLI kinetic analysis and ITC assay showed that PPD specifically bound to AK5. Furthermore, key amino acid mutations predicted by molecular docking decreased the affinity between PPD and AK5. Enzyme activity assays showed that PPD increased AK5 activities in vivo and in vitro. The above-mentioned findings indicated that AK5 is a protein target of ginsenoside in the brain and PPD is considered to be a small-molecular activator of AK5, which can improve comprehension of the molecular mechanisms of ginseng pharmacological effects in the CNS and further develop AK5 activators based on the dammarane-type triterpenoid structure.