CETSA and thermal proteome profiling strategies for target identification and drug discovery of natural products
Graphical abstract
Introduction
Natural products (NPs), the metabolites synthesized by natural organisms during life activities, offer obvious advantages in chemical scaffold novelty, structural complexity, functional diversity, biocompatibility and pharmacokinetic characteristics in comparison with conventional synthetic small-molecule drugs (Atanasov et al., 2021; Clardy and Walsh, 2004). Therefore, NPs have long been the most valuable treasure trove of innovative drug research and development. Analysis has shown that among the small-molecule drugs approved by the Food and Drug Administration (FDA) from 01/1981 to 09/2019, 63.1% of the drugs were directly or indirectly derived from NPs or mimicked the skeleton structure and pharmacophore of NPs, highlighting the vital prominence of NPs in the field of novel drug discovery, both in the past and in the future (Newman and Cragg, 2020). Small-molecule drugs commonly achieve the desired pharmacological functions by binding to the biological macromolecules (mainly proteins) in organisms, and bioactive NPs are no exception (Chen et al., 2020; Schenone et al., 2013). Thus, the identification of protein targets (i.e., "target deconvolution") and the determination of the binding extent of drug targets (i.e., "target engagement") are the most critical steps in the discovery and development of novel NP-based drugs. In the initial stage of drug development, precisely identifying (on- and off-) protein targets of NPs using an unbiased approach followed by establishing a ternary model of "molecule-target-phenotype", is essential for a comprehensive understanding of therapeutic activity and underlying mechanisms, evaluation of off-target adverse effects, promotion of structure optimization and future drug design of NPs. In particular, bioactive NPs are often identified by phenotypic assays without known targets, and it is very common for NPs to bind to multiple protein targets instead of one target, i.e., to exhibit polypharmacology (Dai et al., 2020), which makes the interpretation of the true target or target spectrum of NPs responsible for the observed phenotype strictly challenging.
Fortunately, emerging new technologies for drug target identification offer endless possibilities for the elucidation of the mechanism of action (MoA) and adverse effects of NPs. Generally, the target deconvolution strategies for NPs are divided into two categories: (1) phenotype-based indirect strategies, including differentially expressed transcriptomics/proteomics, cell painting and genetic methods. However, these indirect strategies do not directly provide evidence of drug-target interactions but are based on the target hypothesis generated by multilevel analysis of NP-induced phenotypic changes and known information on the signaling network and a follow-up hypothesis-driven confirmatory study (Cui et al., 2022; Friman, 2020). (2) Direct strategies that allow the direct assessment of drug-target interactions, including chemical proteomics, protein arrays, reverse docking and biophysical approaches. Among these, chemical proteomics, which is a rapidly developed multidisciplinary approach integrating synthetic chemistry, cell biology and mass spectrometry (MS) technology in the past few decades, serves as the most powerful tool for the target identification of small-molecule drugs and bioactive NPs. Typically, chemical proteomics can be divided into two categories: compound-centric chemical proteomics (CCCP) and activity-based protein profiling (ABPP). In the CCCP protocol, the bioactive NPs (fish bait) are chemically immobilized on a matrix support (fishing rod), and then the target proteins that interact with NPs can be pulled out from cell or tissue lysates (Chen et al., 2020). ABPP relies on the design, synthesis and use of different types of NP-derived activity-based probes such as biotin-conjugated probes, click chemistry probes and photoaffinity probes, followed by target fishing and protein identification (Li et al., 2021). Although chemical proteomics-based approaches have made extensive applications and significant progress in the target identification of NPs, their shortcomings have gradually become clear. For example, these methods all require chemical modification of NPs, which may affect the bioactivity and protein binding specificity of NPs and result in false target identification. Moreover, it may be quite difficult or impossible to chemically modify some NPs with complex chemical structure or extremely low natural abundance (Chen et al., 2020; Lyu et al., 2020). In addition, nonspecific binding of NPs to nontarget proteins is another important issue hindering accurate target identification (Wang et al., 2016).
Recently, a series of emerging label-free (or modification-free) approaches for target deconvolution and target engagement has attracted widespread attention, including the drug affinity responsive target stability (DARTS) method, pulse proteolysis (PP), cellular thermal shift assay (CETSA), stability of proteins from rates of oxidation (SPROX) method, solvent-induced protein precipitation (SIP) method, and chemical denaturation and protein precipitation (CPP) method. These approaches evaluate the direct interaction between drugs and their protein targets by detecting the changes in biophysical properties of proteins upon drug binding, such as measuring changes in proteolysis susceptibility, thermal stability, oxidation stability and chemical denaturant-induced stability. The application of these label-free methods to target identification has been reviewed in detail recently (Cui et al., 2022; Dai et al., 2020; Lyu et al., 2020; Sun et al., 2021). Compared to CCCP and ABPP methods, these label-free methods may be more suitable for target identification of NPs since they do not require structural modification of NPs or synthesis of NP-derived probes, thus ensuring faster and more robust target identification of NPs, especially for the bioactive NPs possessing complex structure or lacking chemical modification space. In addition, another advantage is that they can be applied to target identification of NP mixtures or medicinal plant extracts, offering great possibilities for the interpretation of synergistic effects of multiple NPs (Cui et al., 2022; Dai et al., 2020). Among these label-free approaches, CETSA, first proposed by Pär Nordlund's group in 2013, is a novel, stringent, label-free biophysical assay based on the principle of ligand-induced thermal stabilization of target proteins, which allows in situ assessment of ligand-target engagement (Molina et al., 2013). In contrast to other label-free methods, CETSA is the only broadly applicable method that can be directly implemented in cell lysates, intact living cells and even tissues. CETSA and its derivative strategies have shown great application potential in various stages of drug development, including target identification/validation, lead generation, lead optimization, and even preclinical and clinical development. Recently, the technical developments, experimental setup, target deconvolution application and future perspectives of an MS-based CETSA approach named thermal proteome profiling (TPP) have been discussed in a few reviews (Friman, 2020; Mateus et al., 2020, 2022). In addition, the potential of MS-CETSA/TPP approaches to investigate protein interaction states and horizontal cell biology has been highlighted in other reviews (Dai et al., 2019; Prabhu et al., 2020). In recent years, the application of CETSA in NP studies has received increasing attention due to its simplicity, universality, accuracy and user-friendliness. To our knowledge, a comprehensive review covering the topic of different CETSA strategies and NPs has not been reported to date. Therefore, we conducted a literature survey (2013 to 2022) using Web of Science and PubMed databases with the keywords “CETSA”, “cellular thermal shift assay”, “thermal proteome profiling” and “MS-CETSA”. The collected literature was further manually screened according to the criteria of whether the CETSA-derived strategies were used for target validation, target identification or drug discovery of NPs. This review focuses on the principles of CETSA and its derivative methods, as well as recent advances in CETSA strategies in NPs’ studies, highlighting the important role of CETSA strategies in NP-based drug research and development.
Section snippets
Basic principles of CETSA and its derivative strategies
In general, proteins unfold, denature and precipitate with increasing heating temperature. However, ligand binding to a target protein can improve the thermal stability of the protein, making the protein that is engaged by the ligand be less prone to denaturation and aggregation at the same temperature than the native protein (Dai et al., 2020; Molina et al., 2013). This phenomenon could be explained by the fact that the ligand‒protein complex has a lower energy state than native protein and
Classic WB-CETSA strategy for target validation of bioactive NPs
Currently, many indirect and direct strategies have been used to disclose the targets of NPs linked to their phenotypes. It must be noted that the protein target information obtained by either indirect or direct strategies is "potential" or "putative"; therefore the follow-up target validation is highly required to exclude false-positive targets and confirm true targets. Biochemical assays have always been common methods for target validation (Ren et al., 2021). However, these assays are easily
Thermal proteome profiling (TPP) strategy for target identification of bioactive NPs
Currently, WB-CETSA is considered a simple and reliable strategy for the assessment of cellular target engagement of NPs. Nevertheless, this strategy is established based on the known target protein information and available antibodies, and it mainly focuses on low-throughput determination of a single predefined protein. WB-CETSA cannot achieve the unbiased discovery of unexpected targets of NPs by obtaining global data at the cellular proteome level. In recent decades, MS-based quantitative
High-throughput (HT)-CETSA strategy for drug lead discovery from NPs
Drug discovery campaigns usually begin with a high throughput screen (HTS) that aims to rapidly identify hit compounds possessing the potential to be developed as drugs against proteins of interest. Classic WB-CETSA is a powerful tool for detecting target engagement of candidate drug molecules, which commonly uses Western blot detection as a readout. However, it is not suitable for large-scale target-based drug screening due to its low-throughput and time-consuming characteristics. The
CETSA strategies for target discovery of Chinese medicine
Traditional Chinese medicines (TCMs) or TCM formulas have unique advantages in the treatment of complex diseases due to the complexity of their chemical components, the diversity of their targets and the low side effects. Target discovery has been thought to be the core of elucidating MoAs of TCMs and the key to build the association between chemical components and phenotypic efficacy of TCMs. However, it is the "multi-component, multi-target and multi-level" nature of TCMs that leads to many
Pros, cons and future perspectives of CETSA strategies for NP studies
The efficacy of a drug depends primarily on the extent of its target engagement, while adverse effects are often caused by toxicity-prone off-target binding. From initial hit discovery to preclinical and clinical investigation, target engagement of drugs should be monitored and controlled. The CETSA approach invented in 2013 offers a powerful tool for the measurement of direct cellular target engagement in physiologically relevant contexts, which is based on the principle of ligand-induced
CRediT authorship contribution statement
Yanbei Tu: Conceptualization, Writing – original draft, Writing – review & editing. Lihua Tan: Visualization, Writing – original draft. Hongxun Tao: Writing – review & editing. Yanfang Li: Supervision, Writing – review & editing. Hanqing Liu: Supervision, Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 82204724); the Senior Talent Foundation of Jiangsu University (Grant No. 5501290014); and the Science and Technology Department of Sichuan Province in China (Grant No. 2022YFS0433).
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These authors contributed equally to this work.