Chemoproteomics

Context . Separate samples are labeled using individual isobaric tandem mass tags (TMTs), then labeled samples are pooled. The sample origin of each peptide can be discerned from the TMT attached to it. Labeled peptides are then detected and fragmented by LC-MS/MS, and quantified by comparing relative amounts of TMT fragments in each mass spectrum. The conclusion of the Human Genome Project was followed with hope for a new paradigm in treating disease. Many fatal and intractable diseases were able to be mapped to specific genes, providing a starting point to better understand the roles of their protein products in illness. Drug discovery has made use of animal knock-out models that highlight the impact of a protein's absence, particularly in the development of disease, and medicinal chemists have leveraged computational chemistry to generate high affinity compounds against disease-causing proteins. One potential source of drug failure is the disconnect between early and late drug discovery. In addition to proteomic analysis, the detection of post-translational modifications, like phosphorylation, glycosylation, acetylation, and recently ubiquitination, which give insight into the functional state of a cell, is also possible. The vast majority of proteomic studies are analyzed using high-resolution orbitrap mass spectrometers and samples are processed using a generalizable workflow. A standard procedure begins with sample lysis, in which proteins are extracted into a denaturing buffer containing salts, an agent that reduces disulfide bonds, such as dithiothreitol, and an alkylating agent that caps thiol groups, such as iodoacetamide. Denatured proteins are proteolysed, often with trypsin, and then separated from other mixture components prior to analysis via LC-MS/MS. For more accurate quantification, different samples can be reacted with isobaric tandem mass tags (TMTs), a form of chemical barcode that allows for sample multiplexing, and then pooled. == Solution-based approaches ==

probe'''. A covalent warhead and reporter tag are connected by a linker group. The warhead covalently bonds with the active site of an enzyme and the reporter tag is used to enrich or detect the labeled protein. Fluorophosphonate-biotin is an example of an activity-based probe that targets serine hydrolases. It is connected to a biotinylated enrichment handle by an alkane chain. Broad proteomic and transcriptomic profiling has led to innumerable advances in the biomedical space, but the characterization of RNA and protein expression is limited in its ability to inform on the functional characteristics of proteins. Given that transcript and protein expression information leave gaps in knowledge surrounding the effects of post-translational modifications and protein-protein interactions on enzyme activity, and that enzyme activity varies across cell types, disease states, and physiological conditions, specialized tools are required to profile enzyme activity across contexts. Additionally, many identified enzymes have not been sufficiently characterized to yield actionable mechanisms on which to base functional assays. Without a basis for a functional biochemical readout, chemical tools are required to detect drug-protein interactions. Activity-based protein profiling Activity-based protein profiling (ABPP, also activity-based proteomics) is a technique that was developed to monitor the availability of enzymatic active sites to their endogenous ligands. The probe is typically an analog of the drug whose mechanism is being studied, so covalent labeling of an enzyme is indicative of drug binding. ABPP probes are designed with three key functional units: (1) a site-directed covalent warhead (reactive group); (2) a reporter tag, such as biotin or rhodamine; and (3) a linker group. The site-directed covalent warhead, also called a covalent modifier, is an electrophile that covalently modifies a serine, cysteine, or lysine residue in the enzyme's active site and prevents future interactions with other ligands. The drug scaffold is typically an analog of a drug whose mechanism is being studied, and, importantly, binds to the target reversibly, which better mimics the interaction between most drugs and their targets. There are several varieties of photoreactive groups, but they are fundamentally different from ABPP probes: while ABPP specifically labels nucleophilic amino acids in a target's active site, photoaffinity labeling is non-specific, and thus is applicable to labeling a wider range of targets. The identification tag will vary depending on the type of analysis being done: biotin and click chemistry handles are suitable for enrichment of labeled proteins prior to mass spectrometry based identification, while fluorescent dyes are used when using a gel-based imaging method, such as SDS-PAGE, to validate interaction with a target. Because photoaffinity probes are multifunctional, they are difficult to design. Chemists incorporate the same principles of structure-activity relationship modeling into photoaffinity probes that apply to drugs, but must do so without compromising the drug scaffold's activity or the photoreactive group's ability to bond. Since photoreactive groups bond indiscriminately, improper design can cause the probe to label itself or non-target proteins. The probe must remain stable in storage, across buffers, at various pH levels, and in living systems to ensure that labeling occurs only when exposed to light. Activation by light must also be fine-tuned, as radiation can damage cells. == Immobilization-based approaches ==

mixtures are incubated with the ligand and bound targets are detected downstream. (1A) Ligands are attached to a solid support, such as a microbead or chromatography column, via derivatization. (1B) Ligands bind targets in solution, and are then pulled down by an enrichment handle, such as biotin. (1C) Ligands contain a cross-linking group, which is activated, often with light, labeling the target. An enrichment handle is used to pull down the labeled target. (2) After attachment, the target can be eluted from the ligand or trypsinized directly on-bead. Trypsinized peptides are analyzed via LC-MS/MS. Immobilization-based chemoproteomic techniques encompass variations on microbead-based affinity pull-down, which is similar to immunoprecipitation, and affinity chromatography. In both cases, a solid support is used as an immobilization surface bearing a bait molecule. The bait molecule can be a potential drug if the investigator is trying to identify targets, or a target, such as an immobilized enzyme, if the investigator is screening for small molecules. The bait is exposed to a mixture of potential binding partners, which can be identified after removing non-binding components. Microbead-based immobilization Microbead-based immobilization is a modular technique in that it allows the investigator to decide whether they wish to fish for protein targets from the proteome or drug-like compounds from chemical libraries. The macroscopic properties of microbeads make them amenable to relatively low labor enrichment applications, since they are easily to visualize and their bulk mass is readily removable protein solutions. Microbeads were historically made of inert polymers, such as agarose and dextran, that are functionalized to attach a bait of choice. In the case of using proteins as bait, amine functional groups are common linkers to facilitate attachment. More modern approaches have benefitted from the popularization of dynabeads, a type of magnetic microbead, which enable magnetic separation of bead-immobilized analytes from treated samples. Magnetic beads exhibit superparamagnetic properties, which make them very easy to remove from solution using an external magnet. In a simplified workflow, magnetic beads are used to immobilize a protein target, then the beads are mixed with a chemical library to screen for potential ligands. High-affinity ligands bind to the immobilized target and resist removal by washing, so they are enriched in the sample. Conversely, a ligand of interest can be immobilized and screened against proteome proteins by incubation with a lysate. Affinity chromatography is performed following one of two basic formats: ligand immobilization or target immobilization. Under the ligand immobilization format, a ligand of interest - often a drug lead - is immobilized within a chromatography column and acts as the stationary phase. A complex sample consisting of many proteins, such as a cell lysate, is passed through the column and the target of interest binds to the immobilized ligand while other sample components pass through the column unretained. Under the target immobilization format, a target of interest - often a disease-relevant protein - is immobilized within a chromatography column and acts as the stationary phase. Pooled compound libraries are then passed through the column in an application buffer, ligands are retained through binding interactions with the stationary phase, and other compounds pass through the column unretained. In both cases, retained analytes can be eluted from the column and identified using mass spectrometry. A table of elution strategies is provided below. == Derivatization-free approaches ==

While the approaches above have shown success, they are inherently limited by their need for derivatization, which jeopardizes the affinity of the interaction that derivatized compounds are said to emulate and introduces steric hindrance. The stability-based methods below are thought to work due to ligand-induced shifts in equilibrium concentrations of protein conformational states. A single protein type in solution may be represented by individual molecules in a variety of conformations, with many of them different from one another despite being identical in amino acid sequence. Upon binding a drug, the majority of ligand-bound protein enters an energetically favorable conformation, and moves away from the unpredictable distribution of less stable conformers. Thus, ligand binding is said to stabilize proteins, making them resistant to thermal, enzymatic and chemical degradation. Some examples of stability-based derivatization-free approaches follow. Thermal proteome profiling (TPP) Thermal proteome profiling (also, Cellular Thermal Shift Assay) is recently popularized strategy to infer ligand-protein interactions from shifts in protein thermal stability induced by ligand binding. In a typical assay setup, protein-containing samples are exposed to a ligand of choice, then those samples are aliquoted and heated to separate individual temperature points. Upon binding to a ligand, a protein's thermal stability is expected to increase, so ligand-bound proteins will be more resistant to thermal denaturation. After heating, the amount of non-denatured protein remaining is analyzed using quantitative proteomics and stability curves are generated. Upon comparison to an untreated stability curve, the treated curve is expected to shift to the right, indicating that ligand-induced stabilization occurred. Historically, thermal proteome profiling has been assessed using a western blot against a known target of interest. With the advent of high resolution Orbitrap mass spectrometers, this type of experiment can be executed on a proteome-wide scale and stability curves can be generated for thousands of proteins at once. Thermal proteome profiling has been successfully performed in vitro, in situ, and in vivo. When coupled with mass spectrometry, this technique is referred to as the Mass Spectrometry Cellular Thermal Shift Assay (MS-CETSA). and the extent of protein digestion can either be visualized on a gel or measured by mass spectrometry. Drug binding is expected to result in an increase in signal of the stabilized protein. Drug affinity responsive target stability (DARTS) The Drug Affinity Responsive Target Stability assay follows a similar basic assumption to TPP – that protein stability is increased by ligand binding. In DARTS, however, protein stability is assessed in response to digestion by a protease. Briefly, a sample of cell lysate is incubated with a small molecule of interest, the sample is split into aliquots, and each aliquot goes through limited proteolysis after addition of protease. Limited proteolysis is critical, since complete proteolysis would render even a ligand-bound protein completely digested. Samples are then analyzed via SDS-PAGE to assess differences in extent of digestion, and bands are then excised and analyzed via mass spectrometry to confirm the identities of proteins that are resist proteolysis. Alternatively, if the target is already suspected and is being tested for validation, a western blot protocol can be used to identify protein directly. . Hydrogen peroxide is added to oxidize exposed methionine residues. Drug binding is expected to protect methionine from oxidation by stabilizing the folded form of a protein. Extent of oxidation can be monitored by mass spectrometry and used to generate stability curves. Stability of proteins from rates of oxidation (SPROX) Stability of Proteins from Rates of Oxidation also rests upon the assumption that ligand binding confers protection to proteins from manners of degradation, this time from oxidation of methionine residues. In SPROX, a lysate is split and treated with drug or a DMSO control, then each group is further aliquoted into separate samples with increasing concentrations of the chaotrope and denaturant guanidinium hydrochloride (GuHCl). Depending on the concentration of GuHCl, proteins will unfold to varying degrees. Each sample is then reacted with hydrogen peroxide, which oxidizes methionine residues. Proteins that are stabilized by the drug will remain folded at higher concentrations of GuHCl and will experience less methionine oxidation. Oxidized methionine residues can be quantified via LC-MS/MS and used to generate methionine stability curves, which are a proxy for drug binding. There are drawbacks to the SPROX assay, namely that the only relevant peptides from SPROX samples are those with methionine residues, which account for approximately one-third of peptides, and for which there are currently no viable enrichment techniques. Only those methionines that are exposed to oxidation provide meaningful information, and not all differences in methionine oxidation are consistent with protein stabilization. Without enrichment, LC-MS/MS analysis of these peptides is challenging, as the contribution of other sample components to mass spectrometer noise can drown out relevant signal. Therefore, SPROX samples require fractionation to concentrate peptides of interest prior to LC-MS/MS analysis. the general technique follows a simple scheme. Protein targets are incubated with small molecules to allow for the formation of stable ligand-protein complexes, unbound small molecules are removed from the mixture, and the components of remaining ligand-protein complexes are analyzed using mass spectrometry. Because small molecules can be directly identified by their exact mass, no derivatization is needed to confirm the validity of a hit. Samples are also passed through porous beads, but centrifugation is used to move the sample through the column. == Computational approaches ==

Molecular docking simulations The development and application of bench-top chemoproteomics assays is often time consuming and cost-prohibitive. Molecular docking simulations have emerged as relatively low-cost, high-throughput means for ranking the strength of small molecule-protein interactions. Molecular docking requires accurate modeling of both ligand and protein conformation at atomic resolution, and is therefore aided by empirical determination of protein structure, often through orthogonal methods such as x-ray crystallography and cryogenic electron microscopy. Molecular docking strategies are categorized by the type of information that is already known about the ligand and protein of interest. Ligand-based methods When a bioactive ligand with a known structure is to be screened against a protein with limited structural information, modeling is done with regard to ligand structure. Pharmacophore modeling identifies key electronic and structural features that are associated with therapeutic activity across similarly bioactive structural analogs, and accordingly requires large libraries with corresponding experimental data to enhance predictive power. Compound structures are superimposed virtually and common elements are scored on the basis of their tendency toward bioactivity. The move away from lock-and-key based modeling toward induced-fit based modeling has improved binding predictions but has also given rise to the challenge of modeling ligand flexibility, which requires building a database of conformational models and uses large amounts of data storage space. Another approach is the so-called on-the-fly method, in which conformational models are tested during the process of pharmacophore modeling, without a database; this method requires significantly less storage space at the cost of high computing time. Structure-based methods Ideally, the structure of a drug target is known, which allows for structure-based pharmacophore modeling. A structure-based model integrates key structural properties of the protein's binding site, such as the spatial distribution of interaction points, with features identified from ligand based pharmacophore models to generate a holistic simulation of the ligand-protein interaction. A major challenge in structure-based modeling is to narrow down pharmacophore features, of which many are initially identified, to a set of high priority features, as modeling too many features is a computational challenge. Another challenge is the incompatibility of pharmacophore modeling with quantitative structure-activity relationship (QSAR) profiling. Accurate QSAR models rely on inclusion of many potential targets, not just the therapeutic target. For example, important pharmacophores may yield high-affinity interactions with therapeutic targets, but they may also lead to undesirable off-target activity, and they may also be substrates of metabolic enzymes, such as Cytochrome P450s. Therefore, pharmacophore modeling against therapeutic targets is only one component of the compound's total structure-activity relationship. == Applications ==

Druggability are heterobifunctional small molecules that contain a functional group that binds a target and another functional group that recruits an E3 ubiquitin ligase. Binding to both proteins induces proximity-based ubiquitination of the target by the E3 ubiquitin ligase, leading to target degradation. Chemoproteomic strategies have been used to expand the scope of druggable targets. While historically successful drugs target well-defined binding pockets of druggable proteins, these define only about 15% of the annotated proteome. In this context, a phenotypic screen is usually employed to identify drugs with a desired effect in vitro, such as inhibition of viral plaque formation. If a drug produces a positive test, the next step is to determine whether it is acting on a known or novel target. Chemoproteomics is thus a follow-up to phenotypic screening. In the case of COVID-19, Friman et al investigated off-target effects of the broad-spectrum antiviral Remdesivir, which was among the first repurposed drugs to be used in the pandemic. Remdesivir was tested via thermal proteome profiling in a HepG2 cellular thermal shift assay, along with the controversial drug hydroxychloroquine, and investigators discovered TRIP13 as a potential off-target of Remdesivir. High-throughput screening Approved drugs are never identified as hits in high-throughput screens because the chemical libraries used in screening have not been optimized against any targets. However, methods like affinity chromatography and affinity selection-mass spectrometry are workhorses of the pharmaceutical industry, and AS-MS particularly has been documented to produce a significant number of hits across many classes of difficult-to-drug proteins. This is due in large part to the sheer volume of ligands that can be screened in a single assay. Researchers at the iHuman Institute at ShanghaiTech University employed of scheme in which 20,000 compounds per pool were screened against A2AR, a difficult G-protein coupled receptor to drug, with a 0.12% hit rate, leading to several high affinity ligands. ==See also==