Thermodynamic analysis of protein-ligand interactions in complex biological mixtures using a shotgun proteomics approach

Identification of protein partners for small molecules reshapes the understanding of nonalcoholic steatohepatitis and drug discovery

AIMS

Nonalcoholic steatohepatitis (NASH) is the severe subtype of nonalcoholic fatty diseases (NAFLD) with few options of treatment. Patients with NASH exhibit partial responses to the current therapeutics, and adverse effects. Identification of the binding proteins for the drugs is essential to understanding the mechanism and adverse effects of the drugs, and fuels the discovery of potent and safe drugs. This paper aims to critically discuss recent advances in covalent and noncovalent approaches for identifying binding proteins that mediate NASH progression, along with an in-depth analysis of the mechanisms by which these targets regulate NASH.

MATERIALS AND METHODS

A literature search was conducted to identify the relevant studies in the database of PubMed and American Chemical Society. The search covered articles published from January 1990 to July 2024, using the search terms of with the keywords such as NASH, benzophenone, diazirine, photo-affinity labeling, thermal protein profiling, CETSA, target identification.

KEY FINDINGS

The covalent approaches utilize drugs modified with diazirine and benzophenone to covalently crosslink with the target proteins, which facilitates the purification and identification of target proteins. In addition, they map the binding sites in the target proteins. By contrast, noncovalent approaches identify the binding targets of unmodified drugs in the intact cell proteome. The advantages and limitations of both approaches have been compared, along with a comprehensive analysis of recent innovations that further enhance the efficiency and specificity.

SIGNIFICANCE

The analyses of the applicability of these approaches provide novel tools to delineate NASH pathogenesis and promotes drug discovery.

Recent advances in identifying protein targets of bioactive natural products

Background

Natural products exhibit structural complexity, diversity, and historical therapeutic significance, boasting attractive functions and biological activities that have significantly influenced drug discovery endeavors. The identification of target proteins of active natural compounds is crucial for advancing novel drug innovation. Currently, methods for identifying targets of natural products can be categorized into labeling and label-free approaches based on whether the natural bioactive constituents are modified into active probes. In addition, there is a new avenue for rapidly exploring the targets of natural products based on their innate functions.

Aim

This review aimed to summarize recent advancements in both labeling and label-free approaches to the identification of targets for natural products, as well as the novel target identification method based on the natural functions of natural products.

Methods

We systematically collected relevant articles published in recent years from PubMed, Web of Science, and ScienceDirect, focusing on methods employed for identifying protein targets of bioactive natural products. Furthermore, we systematically summarized the principles, procedures, and successful cases, as well as the advantages and limitations of each method.

Results

Labeling methods allow for the direct labeling of target proteins and the exclusion of indirectly targeted proteins. However, these methods are not suitable for studying post-modified compounds with abolished activity, chemically challenging synthesis, or trace amounts of natural active compounds. Label-free methods can be employed to identify targets of any natural active compounds, including trace amounts and multicomponent mixtures, but their reliability is not as high as labeling methods. The structural complementarity between natural products and their innate receptors significantly increase the opportunities for finding more promising structural analogues of the natural products, and natural products may interact with several structural analogues of receptors in humans.

Conclusion

Each approach presents benefits and drawbacks. In practice, a combination of methods is employed to identify targets of natural products. And natural products' innate functions-based approach is a rapid and selective strategy for target identification. This review provides valuable references for future research in this field, offering insights into techniques and methodologies.

Thermostability-assisted limited proteolysis-coupled mass spectrometry for capturing drug target proteins and sites

BACKGROUND

Identifying drug-binding targets and their corresponding sites is crucial for drug discovery and mechanism studies. Limited proteolysis-coupled mass spectrometry (LiP-MS) is a sophisticated method used for the detection of compound and protein interactions. However, in some cases, LiP-MS cannot identify the target proteins due to the small structure changes or the lack of enrichment of low-abundant protein. To overcome this drawback, we developed a thermostability-assisted limited proteolysis-coupled mass spectrometry (TALiP-MS) approach for efficient drug target discovery.

RESULTS

We proved that the novel strategy, TALiP-MS, could efficiently identify target proteins of various ligands, including cyclosporin A (a calcineurin inhibitor), geldanamycin (an HSP90 inhibitor), and staurosporine (a kinase inhibitor), with accurately recognizing drug-binding domains. The TALiP protocol increased the number of target peptides detected in LiP-MS experiments by 2- to 8-fold. Meanwhile, the TALiP-MS approach can not only identify both ligand-binding stability and destabilization proteins but also shows high complementarity with the thermal proteome profiling (TPP) and machine learning-based limited proteolysis (LiP-Quant) methods. The developed TALiP-MS approach was applied to identify the target proteins of celastrol (CEL), a natural product known for its strong antioxidant and anti-cancer angiogenesis effect. Among them, four proteins, MTHFD1, UBA1, ACLY, and SND1 were further validated for their strong affinity to CEL by using cellular thermal shift assay. Additionally, the destabilized proteins induced by CEL such as TAGLN2 and CFL1 were also validated.

SIGNIFICANCE

Collectively, these findings underscore the efficacy of the TALiP-MS method for identifying drug targets, elucidating binding sites, and even detecting drug-induced conformational changes in target proteins in complex proteomes.

Stability-Based Proteomics for Investigation of Structured RNA-Protein Interactions

RNA-protein interactions are essential to RNA function throughout biology. Identifying the protein interactions associated with a specific RNA, however, is currently hindered by the need for RNA labeling or costly tiling-based approaches. Conventional strategies, which commonly rely on affinity pull-down approaches, are also skewed to the detection of high affinity interactions and frequently miss weaker interactions that may be biologically important. Reported here is the first adaptation of stability-based mass spectrometry methods for the global analysis of RNA-protein interactions. The stability of proteins from rates of oxidation (SPROX) and thermal protein profiling (TPP) methods are used to identify the protein targets of three RNA ligands, the MALAT1 triple helix (TH), a viral stem loop (SL), and an unstructured RNA (PolyU), in LNCaP nuclear lysate. The 315 protein hits with RNA-induced conformational and stability changes detected by TPP and/or SPROX were enriched in previously annotated RNA-binding proteins and included new proteins for hypothesis generation. Also demonstrated are the orthogonality of the SPROX and TPP approaches and the utility of the domain-specific information available with SPROX. This work establishes a novel platform for the global discovery and interrogation of RNA-protein interactions that is generalizable to numerous biological contexts and RNA targets.

Modulation of protein-saccharide interactions by deep-sea osmolytes under high pressure stress

Deep-sea organisms must cope with high hydrostatic pressures (HHP) up to the kbar regime to control their biomolecular processes. To alleviate the adverse effects of HHP on protein stability most organisms use high amounts of osmolytes. Little is known about the effects of these high concentrations on ligand binding. We studied the effect of the deep-sea osmolytes trimethylamine-N-oxide, glycine, and glycine betaine on the binding between lysozyme and the tri-saccharide NAG3, employing experimental and theoretical tools to reveal the combined effect of osmolytes and HHP on the conformational dynamics, hydration changes, and thermodynamics of the binding process. Due to their different chemical makeup, these cosolutes modulate the protein-sugar interaction in different ways, leading to significant changes in the binding constant and its pressure dependence. These findings suggest that deep-sea organisms may down- and up-regulate reactions in response to HHP stress by altering the concentration and type of the intracellular osmolyte.

Effects of Crowding and Cosolutes on Biomolecular Function at Extreme Environmental Conditions

The extent of the effect of cellular crowding and cosolutes on the functioning of proteins and cells is manifold and includes the stabilization of the biomolecular systems, the excluded volume effect, and the modulation of molecular dynamics. Simultaneously, it is becoming increasingly clear how important it is to take the environment into account if we are to shed light on biological function under various external conditions. Many biosystems thrive under extreme conditions, including the deep sea and subseafloor crust, and can take advantage of some of the effects of crowding. These relationships have been studied in recent years using various biophysical techniques, including neutron and X-ray scattering, calorimetry, FTIR, UV-vis and fluorescence spectroscopies. Combining knowledge of the structure and conformational dynamics of biomolecules under extreme conditions, such as temperature, high hydrostatic pressure, and high salinity, we highlight the importance of considering all results in the context of the environment. Here we discuss crowding and cosolute effects on proteins, nucleic acids, membranes, and live cells and explain how it is possible to experimentally separate crowding-induced effects from other influences. Such findings will contribute to a better understanding of the homeoviscous adaptation of organisms and the limits of life in general.

Uncovering SOD3 and GPX4 as new targets of Benzo[α]pyrene-induced hepatotoxicity through Metabolomics and Chemical Proteomics

Benzo[α]pyrene (Bap) is recognized as a ubiquitous environmental pollutant among the polycyclic aromatic hydrocarbons (PAHs) class. Previous studies have shown that the hepatotoxicity of Bap is mainly caused by its metabolites, although it remains unclear whether Bap itself induces such damage. This study integrated metabolomics and chemical proteomics approaches to comprehensively identify the potential target proteins affected by Bap in liver cells. The results from the metabolomics showed that the significant changed metabolites were related with cellular redox homeostasis. CEllular Thermal Shift Assay (CETSA) showed that Bap induced protein thermal displacement of superoxide dismutase 3 (SOD3) and glutathione peroxidase 4 (GPX4), which are closely related to oxidative homeostasis. Further validation through in vitro CETSA and drug affinity response target stability (DARTS) revealed that Bap directly affected the stability of SOD3 and GPX4 proteins. The binding affinities of Bap to the potential target proteins were further evaluated using molecular docking, while the isothermal titration calorimetry (ITC) interaction measurements indicated nanomolar-level Kd values. Importantly, we found that Bap weakened the antioxidant capacity by destroying the activities of SOD3 and GPX4, which provided a new understanding of the mechanism of hepatotoxicity induced by Bap. Moreover, our provided workflow integrating metabolomics and label-free chemical proteomics, can be regarded as a practical way to identify the targets and inter-mechanisms for the various environmental compounds.

Comparative Analysis of Protein Folding Stability-Based Profiling Methods for Characterization of Biological Phenotypes

Recently, a new suite of mass spectrometry-based proteomic methods has been developed that enables evaluation of protein folding stability on the proteomic scale. These methods utilize chemical and thermal denaturation approaches (SPROX and TPP, respectively) as well as proteolysis strategies (DARTS, LiP, and PP) to assess protein folding stability. The analytical capabilities of these technique have been well-established for protein target discovery applications. However, less is known about the relative advantages and disadvantages of using these different strategies to characterize biological phenotypes. Reported here is a comparative study of SPROX, TPP, LiP, and conventional protein expression level measurements using both a mouse model of aging and a mammalian cell culture model of breast cancer. Analyses on proteins in brain tissue cell lysates derived from 1- and 18-month-old mice (n = 4-5 at each time point) and on proteins in cell lysates derived from the MCF-7 and MCF-10A cell lines revealed a majority of the differentially stabilized protein hits in each phenotype analysis had unchanged expression levels. In both phenotype analyses, TPP generated the largest number and fraction of differentially stabilized protein hits. Only a quarter of all the protein hits identified in each phenotype analysis had a differential stability that was detected using multiple techniques. This work also reports the first peptide-level analysis of TPP data, which was required for the correct interpretation of the phenotype analyses performed here. Studies on selected protein stability hits also uncovered phenotype-related functional changes.

Challenges and Perspectives in Target Identification and Mechanism Illustration for Chinese Medicine

Chinese medicine (CM) is an important resource for human life understanding and discovery of drugs. However, due to the unclear pharmacological mechanism caused by unclear target, research and international promotion of many active components have made little progress in the past decades of years. CM is mainly composed of multi-ingredients with multi-targets. The identification of targets of multiple active components and the weight analysis of multiple targets in a specific pathological environment, that is, the determination of the most important target is the main obstacle to the mechanism clarification and thus hinders its internationalization. In this review, the main approach to target identification and network pharmacology were summarized. And BIBm (Bayesian inference modeling), a powerful method for drug target identification and key pathway determination was introduced. We aim to provide a new scientific basis and ideas for the development and international promotion of new drugs based on CM.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Metabolization and sequestration of plant specialized metabolites in insect herbivores: Current and emerging approaches

Herbivorous insects encounter diverse plant specialized metabolites (PSMs) in their diet, that have deterrent, anti-nutritional, or toxic properties. Understanding how they cope with PSMs is crucial to understand their biology, population dynamics, and evolution. This review summarizes current and emerging cutting-edge methods that can be used to characterize the metabolic fate of PSMs, from ingestion to excretion or sequestration. It further emphasizes a workflow that enables not only to study PSM metabolism at different scales, but also to tackle and validate the genetic and biochemical mechanisms involved in PSM resistance by herbivores. This review thus aims at facilitating research on PSM-mediated plant-herbivore interactions.

Discovery of the Xenon-Protein Interactome Using Large-Scale Measurements of Protein Folding and Stability

The intermolecular interactions of noble gases in biological systems are associated with numerous biochemical responses, including apoptosis, inflammation, anesthesia, analgesia, and neuroprotection. The molecular modes of action underlying these responses are largely unknown. This is in large part due to the limited experimental techniques to study protein-gas interactions. The few techniques that are amenable to such studies are relatively low-throughput and require large amounts of purified proteins. Thus, they do not enable the large-scale analyses that are useful for protein target discovery. Here, we report the application of stability of proteins from rates of oxidation (SPROX) and limited proteolysis (LiP) methodologies to detect protein-xenon interactions on the proteomic scale using protein folding stability measurements. Over 5000 methionine-containing peptides and over 5000 semi-tryptic peptides, mapping to ∼1500 and ∼950 proteins, respectively, in the yeast proteome, were assayed for Xe-interacting activity using the SPROX and LiP techniques. The SPROX and LiP analyses identified 31 and 60 Xe-interacting proteins, respectively, none of which were previously known to bind Xe. A bioinformatics analysis of the proteomic results revealed that these Xe-interacting proteins were enriched in those involved in ATP-driven processes. A fraction of the protein targets that were identified are tied to previously established modes of action related to xenon's anesthetic and organoprotective properties. These results enrich our knowledge and understanding of biologically relevant xenon interactions. The sample preparation protocols and analytical methodologies developed here for xenon are also generally applicable to the discovery of a wide range of other protein-gas interactions in complex biological mixtures, such as cell lysates.

Chemoproteomic-enabled characterization of small GTPase Rab1a as a target of an N-arylbenzimidazole ligand's rescue of Parkinson's-associated cell toxicity

The development of phenotypic models of Parkinson's disease (PD) has enabled screening and identification of phenotypically active small molecules that restore complex biological pathways affected by PD toxicity.

The Role of Natural Products as Sources of Therapeutic Agents for Innovative Drug Discovery

Emerging threats to human health require a concerted effort in search of both preventive and treatment strategies, placing natural products at the center of efforts to obtain new therapies and reduce disease spread and associated mortality. The therapeutic value of compounds found in plants has been known for ages, resulting in their utilization in homes and in clinics for the treatment of many ailments ranging from common headache to serious conditions such as wounds. Despite the advancement observed in the world, plant based medicines are still being used to treat many pathological conditions or are used as alternatives to modern medicines. In most cases, these natural products or plant-based medicines are used in an un-purified state as extracts. A lot of research is underway to identify and purify the active compounds responsible for the healing process. Some of the current drugs used in clinics have their origins as natural products or came from plant extracts. In addition, several synthetic analogues are natural product-based or plant-based. With the emergence of novel infectious agents such as the SARS-CoV-2 in addition to already burdensome diseases such as diabetes, cancer, tuberculosis and HIV/AIDS, there is need to come up with new drugs that can cure these conditions. Natural products offer an opportunity to discover new compounds that can be converted into drugs given their chemical structure diversity. Advances in analytical processes make drug discovery a multi-dimensional process involving computational designing and testing and eventual laboratory screening of potential drug candidates. Lead compounds will then be evaluated for safety, pharmacokinetics and efficacy. New technologies including Artificial Intelligence, better organ and tissue models such as organoids allow virtual screening, automation and high-throughput screening to be part of drug discovery. The use of bioinformatics and computation means that drug discovery can be a fast and efficient process and enable the use of natural products structures to obtain novel drugs. The removal of potential bottlenecks resulting in minimal false positive leads in drug development has enabled an efficient system of drug discovery. This review describes the biosynthesis and screening of natural products during drug discovery as well as methods used in studying natural products.

Analysis of Brain Protein Stability Changes in Mouse Models of Normal Aging and α-Synucleinopathy Reveals Age- and Disease-Related Differences

Here, we utilize the stability of proteins from rates of oxidation (SPROX) technique, to profile the thermodynamic stabilities of proteins in brain tissue cell lysates from Huα-Syn(A53T) transgenic mice at three time points including at 1 month (n = 9), at 6 months (n = 7), and at the time (between 9 and 16 months) a mouse became symptomatic (n = 8). The thermodynamic stability profiles generated here on 332 proteins were compared to thermodynamic stability profiles generated on the same proteins from similarly aged wild-type mice using a two-way unbalanced analysis of variance (ANOVA) analysis. This analysis identified a group of 22 proteins with age-related protein stability changes and a group of 11 proteins that were differentially stabilized in the Huα-Syn(A53T) transgenic mouse model. A total of 9 of the 11 proteins identified here with disease-related stability changes have been previously detected in human cerebral spinal fluid and thus have potential utility as biomarkers of Parkinson's disease (PD). The differential stability observed for one protein, glutamate decarboxylase 2 (Gad2), with an age-related change in stability, was consistent with the differential presence of a known, age-related truncation product of this protein, which is shown here to have a higher folding stability than full-length Gad2. Mass spectrometry data were deposited at ProteomeXchange (PXD016985).

Hydroxyl Radical Protein Footprinting: A Mass Spectrometry-Based Structural Method for Studying the Higher Order Structure of Proteins

Hydroxyl radical protein footprinting (HRPF) coupled to mass spectrometry has been successfully used to investigate a plethora of protein-related questions. The method, which utilizes hydroxyl radicals to oxidatively modify solvent-accessible amino acids, can inform on protein interaction sites and regions of conformational change. Hydroxyl radical-based footprinting was originally developed to study nucleic acids, but coupling the method with mass spectrometry has enabled the study of proteins. The method has undergone several advancements since its inception that have increased its utility for more varied applications such as protein folding and the study of biotherapeutics. In addition, recent innovations have led to the study of increasingly complex systems including cell lysates and intact cells. Technological advances have also increased throughput and allowed for better control of experimental conditions. In this review, we provide a brief history of the field of HRPF and detail recent innovations and applications in the field.

Currently Available Strategies for Target Identification of Bioactive Natural Products

In recent years, biologically active natural products have gradually become important agents in the field of drug research and development because of their wide availability and variety. However, the target sites of many natural products are yet to be identified, which is a setback in the pharmaceutical industry and has seriously hindered the translation of research findings of these natural products as viable candidates for new drug exploitation. This review systematically describes the commonly used strategies for target identification via the application of probe and non-probe approaches. The merits and demerits of each method were summarized using recent examples, with the goal of comparing currently available methods and selecting the optimum techniques for identifying the targets of bioactive natural products.

A Comparison of Two Stability Proteomics Methods for Drug Target Identification in OnePot 2D Format

Stability proteomics techniques that do not require drug modifications have emerged as an attractive alternative to affinity purification methods in drug target engagement studies. Two representative techniques include the chemical-denaturation-based SPROX (Stability of Proteins from Rates of Oxidation), which utilizes peptide-level quantification and thermal-denaturation-based TPP (Thermal Proteome Profiling), which utilizes protein-level quantification. Recently, the "OnePot" strategy was adapted for both SPROX and TPP to increase the throughput. When combined with the 2D setup which measures both the denaturation and the drug dose dimensions, the OnePot 2D format offers improved analysis specificity with higher resource efficiency. However, a systematic evaluation of the OnePot 2D format and a comparison between SPROX and TPP are still lacking. Here, we performed SPROX and TPP to identify protein targets of a well-studied pan-kinase inhibitor staurosporine with K562 lysate, in curve-fitting and OnePot 2D formats. We found that the OnePot 2D format provided ∼10× throughput, achieved ∼1.6× protein coverage and involves more straightforward data analysis. We also compared SPROX with the current "gold-standard" stability proteomics technique TPP in the OnePot 2D format. The protein coverage of TPP is ∼1.5 fold of SPROX; however, SPROX offers protein domain-level information, identifies comparable numbers of kinase hits, has higher signal (R value), and requires ∼3× less MS time. Unique SPROX hits encompass higher-molecular-weight proteins, compared to the unique TPP hits, and include atypical kinases. We also discuss hit stratification and prioritization strategies to promote the efficiency of hit followup.

Target identification of anticancer natural products using a chemical proteomics approach

In recent years, there has been a strong demand worldwide for the identification and development of potential anticancer drugs based on natural products. Natural products have been explored for their diverse biological and therapeutic applications from ancient time. In order to enhance the efficacy and selectivity and to minimize the undesired side effects of anti cancer natural products (ANPs), it is essential to understand their target proteins and their mechanistic pathway. Chemical proteomics is one of the most powerful tools to connect ANP target identification and quantification where labeling and non-labeling based approaches have been used. Herein, we have discussed the various strategies to systemically develop selective ANP based chemical probes to characterise their specific and non-specific target proteins using a chemical proteomic approach in various cancer cell lysates.

Application of omics- and multi-omics-based techniques for natural product target discovery

Natural products continue to be an unparalleled source of pharmacologically active lead compounds because of their unprecedented structures and unique biological activities. Natural product target discovery is a vital component of natural product-based medicine translation and development and is required to understand and potentially reduce mechanisms that may be associated with off-target side effects and toxicity. Omics-based techniques, including genomics, transcriptomics, proteomics, metabolomics, and bioinformatics, have become recognized as effective tools needed to construct innovative strategies to discover natural product targets. Although considerable progress has been made, the successful discovery of natural product targets remains a challenging time-consuming process that has come to increasingly rely on the effective integration of multi-omics-based technologies to create emerging panomics (a.k.a., integrative omics, pan-omics, multiomics)-based strategies. This review summarizes a series of successful studies regarding the application of integrative omics-based methods in natural product target discovery. The advantages and disadvantages of each technique are discussed, with a particular focus on the systematic integration of multi-omics strategies. Further, emerging micro-scale single-cell-based techniques are introduced, especially to deal with minute natural product samples.

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

Small-molecule drugs modulate biological processes and disease states through engagement of target proteins in cells. Assessing drug-target engagement on a proteome-wide scale is of utmost importance in better understanding the molecular mechanisms of action of observed beneficial and adverse effects, as well as in developing next generation tool compounds and drugs with better efficacies and specificities. However, systematic assessment of drug-target engagement has been an arduous task. With the continuous development of mass spectrometry-based proteomics instruments and techniques, various chemical proteomics approaches for drug target deconvolution (i.e., the identification of molecular target for drugs) have emerged. Among these, the label-free target deconvolution approaches that do not involve the chemical modification of compounds of interest, have gained increased attention in the community. Here we provide an overview of the basic principles and recent biological applications of the most important label-free methods including the cellular thermal shift assay, pulse proteolysis, chemical denaturant and protein precipitation, stability of proteins from rates of oxidation, drug affinity responsive target stability, limited proteolysis, and solvent-induced protein precipitation. The state-of-the-art technical implications and future outlook for the label-free approaches are also discussed.

Protein Folding Stability Changes Across the Proteome Reveal Targets of Cu Toxicity in E. coli

The ability of metal ionophores to induce cellular metal hyperaccumulation endows them with potent antimicrobial activity; however, the targets and mechanisms behind these outcomes are not well understood. This work describes the first utilization of proteome-wide measurements of protein folding stability in combination with protein expression level analysis to identify protein targets of copper, thereby providing new insight into ionophore-induced copper toxicity in E. coli. The protein folding stability analysis employed a one-pot protocol for pulse proteolysis (PP) in combination with a semi-tryptic peptide enrichment strategy for proteolysis procedures (STEPP) to generate stability profiles for proteins in cell lysates derived from E. coli exposed to copper with and without two ionophores, the antimicrobial agent pyrithione and its β-lactamase-activated prodrug, PcephPT. As part of this work, the above cell lysates were also subject to protein expression level analysis using conventional quantitative bottom-up proteomic methods. The protein folding stability and expression level profiles generated here enabled the effects of ionophore vs copper to be distinguished and revealed copper-driven stability changes in proteins involved in processes spanning metabolism, translation, and cell redox homeostasis. The 159 differentially stabilized proteins identified in this analysis were significantly more numerous (∼3×) than the 53 proteins identified with differential expression levels. These results illustrate the unique information that protein stability measurements can provide to decipher metal-dependent processes in drug mode of action studies.

Target identification and validation of natural products with label-free methodology: A critical review from 2005 to 2020

Natural products (NPs) have been an important source of therapeutic drugs in clinic use and contributed many chemical probes for research. The usefulness of NPs is however often marred by the incomplete understanding of their direct cellular targets. A number of experimental methods for drug target identification have been developed over the years. One class of methods, termed "label-free" methodology, exploits the energetic and biophysical features accompanying the association of macromolecules with drugs and other compounds in their native forms. Herein we review the working principles, assay implementations, and key applications of the most important approaches, and also give examples where they have been applied to NPs. We also assess the key advantages and limitations of each method. Furthermore, we address when and how the label-free methodology can be particularly useful considering some of the unique features of NP chemistry and bioactivation.

Towards a functional understanding of the plant metabolome

Plants are true organic chemists-the chemical diversity of plant metabolomes goes hand in hand with functional diversity. New, often unexpected roles are being reported for both evolutionarily conserved and well-characterised central metabolites such as amino acids, nucleotides, and sugars, and for specialized/secondary metabolites such as carotenoids, glucosinolates, and terpenoids. Our review aims to highlight recent studies reporting novel roles of metabolites and to emphasize the importance of cell-wide identification of metabolite-protein complexes for the comprehensive, functional understanding of the plant metabolome.

Target identification of natural medicine with chemical proteomics approach: probe synthesis, target fishing and protein identification

Natural products are an important source of new drugs for the treatment of various diseases. However, developing natural product-based new medicines through random moiety modification is a lengthy and costly process, due in part to the difficulties associated with comprehensively understanding the mechanism of action and the side effects. Identifying the protein targets of natural products is an effective strategy, but most medicines interact with multiple protein targets, which complicate this process. In recent years, an increasing number of researchers have begun to screen the target proteins of natural products with chemical proteomics approaches, which can provide a more comprehensive array of the protein targets of active small molecules in an unbiased manner. Typically, chemical proteomics experiments for target identification consist of two key steps: (1) chemical probe design and synthesis and (2) target fishing and identification. In recent decades, five different types of chemical proteomic probes and their respective target fishing methods have been developed to screen targets of molecules with different structures, and a variety of protein identification approaches have been invented. Presently, we will classify these chemical proteomics approaches, the application scopes and characteristics of the different types of chemical probes, the different protein identification methods, and the advantages and disadvantages of these strategies.

Mass spectrometry-based methods for structural biology on a proteome-wide scale

Mass spectrometry (MS) has long been used to study proteins mainly via sequence identification and quantitation of expression abundance. In recent years, MS has emerged as a tool for structural biology. Intact protein structural analysis has been enabled by the development of methods such as native MS, top-down proteomics, and ion mobility MS. Other MS-based structural methods include affinity purification MS, chemical cross-linking, and protein footprinting. These methods have enabled the study of protein–protein and protein–ligand interactions and regions of conformational change. The coupling of MS with liquid chromatography has permitted the analysis of complex samples. This bottom-up proteomics workflow enables the study of protein structure in the native cellular environment and provides structural information across the proteome. It has been demonstrated that the crowded environment of the cell affects protein binding interactions and affinities. Performing studies in this complex environment is essential for understanding the functional roles of proteins. MS-based structural methods permit analysis of samples such as cell lysates, intact cells, and tissue to provide a more physiological view of protein structure. This mini-review discusses the various MS-based methods that can be used for proteome-wide structural studies and highlights some of their application.

Comparative Analysis of Mass-Spectrometry-Based Proteomic Methods for Protein Target Discovery Using a One-Pot Approach

Recently, several mass-spectrometry- and protein-denaturation-based proteomic methods have been developed to facilitate protein target discovery efforts in drug mode-of-action studies. These methods, which include the stability of proteins from rates of oxidation (SPROX), pulse proteolysis (PP), chemical denaturation and protein precipitation (CPP), and thermal proteome profiling (TPP) techniques, have been used in an increasing number of applications in recent years. However, while the advantages and disadvantages to using these different techniques have been reviewed, the analytical characteristics of these methods have not been directly compared. Reported here is such a direct comparison using the well-studied immunosuppressive drug, cyclosporine A (CsA), and the proteins in a yeast cell lysate. Also described is a one-pot strategy that can be utilized with each technique to streamline data acquisition and analysis. We find that there are benefits to utilizing all four strategies for protein target discovery including increased proteomic coverage and reduced false positive rates that approach 0%. Moreover, the one-pot strategy described here makes such an experiment feasible, because of the 10-fold reduction in reagent costs and instrument time it affords.

A one-pot analysis approach to simplify measurements of protein stability and folding kinetics

To achieve a good understanding of the characteristics of a protein, it is important to study its stability and folding kinetics. Investigations of protein stability have been recently applied to drug-target identification, drug screening, and proteomic studies. The efficiency of the experiments performed to study protein stability and folding kinetics is now a crucial factor that needs to be optimized for these potential applications. However, the standard procedures used to carry out these experiments are usually complicated and time consuming. Large number of measurements is the bottleneck that limits the application of protein folding to large-scale experiments. To overcome this limitation, we developed a method denoted as "one-pot analysis" which is based on taking a single measurement from a mixture of samples rather than from every sample. We combined one-pot analysis with pulse proteolysis to determine the effects of the binding of maltose to maltose-binding protein on the protein folding properties. After carrying out a simple optimization, we demonstrated that protein stability or unfolding kinetics could be measured accurately with just one detection measurement. We then further applied the optimized conditions to cellular thermal shift assay (CETSA). Combining one-pot analysis with CETSA led to a successful determination of the effects of the binding of methotrexate to dihydrofolate reductase in HCT116 cancer cells. Our results demonstrated the applicability of one-pot analysis to energetics-based methods for studying protein folding. We expect the combination of one-pot analysis and energetics-based methods to significantly benefit studies such as drug-target identification, proteomic investigations, and drug screening.

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.

Screening Strategies and Methods for Better Off-Target Liability Prediction and Identification of Small-Molecule Pharmaceuticals

Pharmaceutical discovery and development is a long and expensive process that, unfortunately, still results in a low success rate, with drug safety continuing to be a major impedance. Improved safety screening strategies and methods are needed to more effectively fill this critical gap. Recent advances in informatics are now making it possible to manage bigger data sets and integrate multiple sources of screening data in a manner that can potentially improve the selection of higher-quality drug candidates. Integrated screening paradigms have become the norm in Pharma, both in discovery screening and in the identification of off-target toxicity mechanisms during later-stage development. Furthermore, advances in computational methods are making in silico screens more relevant and suggest that they may represent a feasible option for augmenting the current screening paradigm. This paper outlines several fundamental methods of the current drug screening processes across Pharma and emerging techniques/technologies that promise to improve molecule selection. In addition, the authors discuss integrated screening strategies and provide examples of advanced screening paradigms.

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

Oxidation of protein-bound methionine in Photofrin-photodynamic therapy-treated human tumor cells explored by methionine-containing peptide enrichment and quantitative proteomics approach

In Photofrin-mediated photodynamic therapy (PDT), cell fate can be modulated by the subcellular location of Photofrin. PDT triggers oxidative damage to target cells, including the methionine (Met) oxidation of proteins. Here, we developed a new Met-containing peptide enrichment protocol combined with SILAC-based quantitative proteomics, and used this approach to explore the global Met oxidation changes of proteins in PDT-treated epidermoid carcinoma A431 cells preloaded with Photofrin at the plasma membrane, ER/Golgi, or ubiquitously. We identified 431 Met-peptides corresponding to 302 proteins that underwent severe oxidation upon PDT and observed overrepresentation of proteins related to the cell surface, plasma membrane, ER, Golgi, and endosome under all three conditions. The most frequently oxidized Met-peptide sequence was "QAMXXMM-E/G/M-S/G-A/G/F-XG". We also identified several hundred potential Photofrin-binding proteins using affinity purification coupled with LC-MS/MS, and confirmed the bindings of EGFR and cathepsin D with Photofrin. The enzyme activities of both proteins were significantly reduced by Photofrin-PDT. Our results shed light on the global and site-specific changes in Met-peptide oxidation among cells undergoing Photofrin-PDT-mediated oxidative stress originating from distinct subcellular sites, and suggest numerous potential Photofrin-binding proteins. These findings provide new insight into the molecular targets through which Photofrin-PDT has diverse effects on target cells.

Discovery of Nicotinamide Adenine Dinucleotide Binding Proteins in the Escherichia coli Proteome Using a Combined Energetic- and Structural-Bioinformatics-Based Approach

Protein-ligand interaction plays a critical role in regulating the biochemical functions of proteins. Discovering protein targets for ligands is vital to new drug development. Here, we present a strategy that combines experimental and computational approaches to identify ligand-binding proteins in a proteomic scale. For the experimental part, we coupled pulse proteolysis with filter-assisted sample preparation (FASP) and quantitative mass spectrometry. Under denaturing conditions, ligand binding affected protein stability, which resulted in altered protein abundance after pulse proteolysis. For the computational part, we used the software Patch-Surfer2.0. We applied the integrated approach to identify nicotinamide adenine dinucleotide (NAD)-binding proteins in the Escherichia coli proteome, which has over 4200 proteins. Pulse proteolysis and Patch-Surfer2.0 identified 78 and 36 potential NAD-binding proteins, respectively, including 12 proteins that were consistently detected by the two approaches. Interestingly, the 12 proteins included 8 that are not previously known as NAD binders. Further validation of these eight proteins showed that their binding affinities to NAD computed by AutoDock Vina are higher than their cognate ligands and also that their protein ratios in the pulse proteolysis are consistent with known NAD-binding proteins. These results strongly suggest that these eight proteins are indeed newly identified NAD binders.

Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using Limited Proteolysis

Conformational changes in proteins can lead to disease. Thus, methods for identifying conformational changes in proteins can further improve our understanding and facilitate detection of disease states. Here we combine limited proteolysis (LiP) with Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) to characterize breast cancer-related conformational changes in proteins on the proteomic scale. Studied here are the conformational properties of proteins in two cell culture models of breast cancer, including the MCF-10A and MCF-7 cell lines. The SILAC-LiP approach described here identified ∼200 proteins with cell-line-dependent conformational changes, as determined by their differential susceptibility to proteolytic digestion using the nonspecific protease, proteinase K. The protease susceptibility profiles of the proteins in these cell lines were compared to thermodynamic stability and expression level profiles previously generated for proteins in these same breast cancer cell lines. The comparisons revealed that there was little overlap between the proteins with protease susceptibility changes and the proteins with thermodynamic stability and/or expression level changes. Thus, the large-scale conformational analysis described here provides unique insight into the molecular basis of the breast cancer phenotypes in this study.

Discovery of Age-Related Protein Folding Stability Differences in the Mouse Brain Proteome

Described here is the application of thermodynamic stability measurements to study age-related differences in the folding and stability of proteins in a rodent model of aging. Thermodynamic stability profiles were generated for 809 proteins in brain cell lysates from mice, aged 6 (n = 7) and 18 months (n = 9) using the Stability of Proteins from Rates of Oxidation (SPROX) technique. The biological variability of the protein stability measurements was low and within the experimental error of SPROX. A total of 83 protein hits were detected with age-related stability differences in the brain samples. Remarkably, the large majority of the brain protein hits were destabilized in the old mice, and the hits were enriched in proteins that have slow turnover rates (p < 0.07). Furthermore, 70% of the hits have been previously linked to aging or age-related diseases. These results help validate the use of thermodynamic stability measurements to capture relevant age-related proteomic changes and establish a new biophysical link between these proteins and aging.

Thermodynamic Analysis of the Geldanamycin-Hsp90 Interaction in a Whole Cell Lysate Using a Mass Spectrometry-Based Proteomics Approach

Geldanamycin is a natural product with well-established and potent anti-cancer activities. Heat shock protein 90 (Hsp90) is the known target of geldanamycin, which directly binds to Hsp90's N-terminal ATP binding domain and inhibits Hsp90's ATPase activity. The affinity of geldanamycin for Hsp90 has been measured in multiple studies. However, there have been large discrepancies between the reported dissociation constants (i.e., Kd values), which have ranged from low nanomolar to micromolar. Here the stability of proteins from rates of oxidation (SPROX) technique was used in combination with an isobaric mass tagging strategy to measure the binding affinity of geldanamycin to unpurified Hsp90 in an MCF-7 cell lysate. The Kd values determined here were dependent on how long geldanamycin was equilibrated with the lysate prior to SPROX analysis. The Kd values determined using equilibration times of 0.5 and 24 h were 1 and 0.03 μM, respectively. These Kd values, which are similar to those previously reported in a geldanamycin-Hsp90 binding study that involved the use of a fluorescently labeled geldanamycin analogue, establish that the slow-tight binding behavior previously observed for the fluorescently labeled geldanamycin analogue is not an artifact of the fluorescent label, but rather an inherent property of the geldanamycin-Hsp90 binding interaction. The slow-tight binding property of this complex may be related to time-dependent conformational changes in Hsp90 and/or to time-dependent chemical changes in geldanamycin, both of which have been previously proposed to explain the slow-tight binding behavior of the geldanamycin-Hsp90 complex. Graphical Abstract ᅟ.

Discovery of Manassantin A Protein Targets Using Large-Scale Protein Folding and Stability Measurements

Manassantin A is a natural product that has been shown to have anticancer activity in cell-based assays, but has a largely unknown mode-of-action. Described here is the use of two different energetics-based approaches to identify protein targets of manassantin A. Using the stability of proteins from rates of oxidation technique with an isobaric mass tagging strategy (iTRAQ-SPROX) and the pulse proteolysis technique with a stable isotope labeling with amino acids in cell culture strategy (SILAC-PP), over 1000 proteins in a MDA-MB-231 cell lysate grown under hypoxic conditions were assayed for manassantin A interactions (both direct and indirect). A total of 28 protein hits were identified with manassantin A-induced thermodynamic stability changes. Two of the protein hits (filamin A and elongation factor 1α) were identified using both experimental approaches. The remaining 26 hit proteins were only assayed in either the iTRAQ-SPROX or the SILAC-PP experiment. The 28 potential protein targets of manassantin A identified here provide new experimental avenues along which to explore the molecular basis of manassantin A's mode of action. The current work also represents the first application iTRAQ-SPROX and SILAC-PP to the large-scale analysis of protein-ligand binding interactions involving a potential anticancer drug with an unknown mode-of-action.

Label-free technologies for target identification and validation

Chemical probes have been instrumental in revealing new targets and confirming target engagement. However, substantial effort and resources are required to design and synthesize these probes. In contrast, label-free technologies have the advantage of bypassing the need for chemical probes. Here we highlight the recent developments in label-free methods and discuss the pros and cons of each approach.

Advances in identification and validation of protein targets of natural products without chemical modification

This review focuses on and reports case studies of the latest advances in target protein identification methods for label-free natural products. The integration of newly developed technologies will provide new insights and highlight the value of natural products for use as biological probes and new drug candidates.

Screening of the binding of small molecules to proteins by desorption electrospray ionization mass spectrometry combined with protein microarray

The interaction between bioactive small molecule ligands and proteins is one of the important research areas in proteomics. Herein, a simple and rapid method is established to screen small ligands that bind to proteins. We designed an agarose slide to immobilize different proteins. The protein microarrays were allowed to interact with different small ligands, and after washing, the microarrays were screened by desorption electrospray ionization mass spectrometry (DESI MS). This method can be applied to screen specific protein binding ligands and was shown for seven proteins and 34 known ligands for these proteins. In addition, a high-throughput screening was achieved, with the analysis requiring approximately 4 s for one sample spot. We then applied this method to determine the binding between the important protein matrix metalloproteinase-9 (MMP-9) and 88 small compounds. The molecular docking results confirmed the MS results, demonstrating that this method is suitable for the rapid and accurate screening of ligands binding to proteins. Graphical Abstract ᅟ.

Global analysis of protein folding thermodynamics for disease state characterization

Current methods for the large-scale characterization of disease states generally rely on the analysis of gene and/or protein expression levels. These existing methods fail to detect proteins with disease-related functions and unaltered expression levels. Here we describe the large-scale use of thermodynamic measurements of protein folding and stability for the characterization of disease states. Using the Stable Isotope Labeling with Amino Acids in Cell Culture and Stability of Proteins from Rates of Oxidation (SILAC-SPROX) technique, we assayed ∼800 proteins for protein folding and stability changes in three different cell culture models of breast cancer including the MCF-10A, MCF-7, and MDA-MB-231 cell lines. The thermodynamic stability profiles generated here created distinct molecular markers to differentiate the three cell lines, and a significant fraction (∼45%) of the differentially stabilized proteins did not have altered expression levels. Thus, the differential thermodynamic profiling strategy reported here created novel molecular signatures of breast cancer and provided additional insight into the molecular basis of the disease. Our results establish the utility of protein folding and stability measurements for the study of disease processes, and they suggest that such measurements may be useful for biomarker discovery in disease.

SILAC-pulse proteolysis: A mass spectrometry-based method for discovery and cross-validation in proteome-wide studies of ligand binding

Reported here is the use of stable isotope labeling with amino acids in cell culture (SILAC) and pulse proteolysis (PP) for detection and quantitation of protein-ligand binding interactions on the proteomic scale. The incorporation of SILAC into PP enables the PP technique to be used for the unbiased detection and quantitation of protein-ligand binding interactions in complex biological mixtures (e.g., cell lysates) without the need for prefractionation. The SILAC-PP technique is demonstrated in two proof-of-principle experiments using proteins in a yeast cell lysate and two test ligands including a well-characterized drug, cyclosporine A (CsA), and a non-hydrolyzable adenosine triphosphate (ATP) analogue, adenylyl imidodiphosphate (AMP-PNP). The well-known tight-binding interaction between CsA and cyclophilin A was successfully detected and quantified in replicate analyses, and a total of 33 proteins from a yeast cell lysate were found to have AMP-PNP-induced stability changes. In control experiments, the method's false positive rate of protein target discovery was found to be in the range of 2.1% to 3.6%. SILAC-PP and the previously reported stability of protein from rates of oxidation (SPROX) technique both report on the same thermodynamic properties of proteins and protein-ligand complexes. However, they employ different probes and mass spectrometry-based readouts. This creates the opportunity to cross-validate SPROX results with SILAC-PP results, and vice-versa. As part of this work, the SILAC-PP results obtained here were cross-validated with previously reported SPROX results on the same model systems to help differentiate true positives from false positives in the two experiments.

Energetics-based methods for protein folding and stability measurements

Over the past 15 years, a series of energetics-based techniques have been developed for the thermodynamic analysis of protein folding and stability. These techniques include Stability of Unpurified Proteins from Rates of amide H/D Exchange (SUPREX), pulse proteolysis, Stability of Proteins from Rates of Oxidation (SPROX), slow histidine H/D exchange, lysine amidination, and quantitative cysteine reactivity (QCR). The above techniques, which are the subject of this review, all utilize chemical or enzymatic modification reactions to probe the chemical denaturant- or temperature-induced equilibrium unfolding properties of proteins and protein-ligand complexes. They employ various mass spectrometry-, sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE)-, and optical spectroscopy-based readouts that are particularly advantageous for high-throughput and in some cases multiplexed analyses. This has created the opportunity to use protein folding and stability measurements in new applications such as in high-throughput screening projects to identify novel protein ligands and in mode-of-action studies to identify protein targets of a particular ligand.