Chemoproteomics assays can be stratified into three basic types. Solution-based approaches involve the use of drug analogs that chemically modify target proteins in
lead optimization. Several targets of high profile drugs have been identified using chemoproteomics, and the continued improvement of mass spectrometersensitivity and chemical probe technology indicates that chemoproteomics will play a large role in future drug discovery
.
Background
Context
An example quantitative proteomics workflow. Protein extracts from different samples are extracted and digested using trypsin. 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. This image was adapted from BioRender.com.
The conclusion of
overexpression systems are simplistic. Spatially and temporally conditional knock-out/knock-in systems have improved the level of nuance in in vivo analysis of protein function, but still fail to completely parallel the systemic breadth of pharmacological action.[3] For example, drugs often act through multiple mechanisms, and often work best by engaging targets partially.[3] Chemoproteomic tools offer a solution to bridge the gap between a genetic understanding of disease and a pharmacological understanding of drug action
by identifying the many proteins involved in therapeutic success.
Basic tools
The chemoproteomic toolkit is anchored by
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.[5]
Under the assumption that enzymes vary in their structure, function, and associations depending on a system's
affinity to their targets will prevent binding of the probe, and the degree of probe binding can be used as an indication of compound affinity. Because ABPP probes label classes of enzymes, this approach can also be used to profile drug selectivity, as highly selective compounds will ideally outcompete probes at only a small number of proteins.[8]
A prototypical photoaffinity probe. A drug scaffold acts as the first interaction site between probe and protein. A photoreactive group, here an arylazide, can be activated by light to form a reactive intermediate that bonds with a non-specific site on the protein. A tag can then be used to enrich and identify or image and detect the target. This image was made using BioRender.com.
Photoaffinity labeling
Unlike ABPP, which results in protein labeling upon probe binding,
fluorescent dyes are used when using a gel-based imaging method, such as SDS-PAGE, to validate interaction with a target.[7][9]
Phenylazide, a photoreactive group commonly used in photoaffinity labeling.
Because photoaffinity probes are multifunctional, they are difficult to design. Chemists incorporate the same principles of
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.[9]
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.[10] The bait is exposed to a mixture of potential binding partners, which can be identified after removing non-binding components.
Hybrid solution- and immobilization-based strategies have been applied, in which
induced fit. Another drawback is non-specific adsorption of both proteins and small molecules to the bead surface, which has the potential to generate false positives.[10]
Affinity chromatography
Affinity chromatography emerged in the 1950s as a rarely used method used to purify enzymes; it has since seen mainstream use and is the oldest among chemoproteomic approaches.
stationary phase, and other compounds pass through the column unretained.[14] In both cases, retained analytes can be eluted
from the column and identified using mass spectrometry. A table of elution strategies is provided below.
Elution conditions may not be strong enough to elute unoptimized compounds.
Isocratic elution
The elution buffer is identical to the application buffer, ligands move readily through the column but at different speeds according to their underlying affinity for the target.
Analytes are eluted by adding a high concentration of a high-affinity binding partner to the mobile phase, bound analytes are competed off of the stationary phase; the additive can be either a protein that scavenges bound ligands or a small molecule that displaces them.
Competitive binding
.
Allows for concentration of analytes with immediate elution; high recovery.
Compounds not previously tested may have higher affinity than the elution additive.
Derivatization-free approaches
An example thermal proteome profiling workflow. Binding of a drug to a protein often leads to ligand-induced stabilization of the protein (1), which can be measured by comparing the amount of non-denatured protein remaining in a drug-treated sample to an untreated control. The change in protein stability can be visualized as a rightward shift in its stability curve (2). This image was adapted from BioRender.com.
While the approaches above have shown success, they are inherently limited by their need for
steric hindrance.[10] Immobilized ligands and targets are limited in their ability to move freely through space in a way that replicates the native protein-ligand interaction, and conformational change from induced fit is often limited when proteins or drugs are immobilized. Probe-based approaches also alter the three-dimensional nature of the ligand-protein interaction by introducing functional groups to the ligand, which can alter compound activity. Derivatization-free approaches aim to infer interactions by proxy, often through observations of changes to protein stability upon binding, and sometimes through chromatographic co-elution.[15]
The stability-based methods below are thought to work due to
An example drug affinity responsive target stability (DARTS) workflow. Binding of a drug to a protein often leads to ligand-induced stabilization of the protein. In DARTS, drug and control treated proteins are subjected to limited proteolysis 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. This image was made using BioRender.com.
Drug affinity responsive target stability (DARTS)
The Drug Affinity Responsive Target Stability
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.[18]
folded form of a protein. Extent of oxidation can be monitored by mass spectrometry and used to generate stability curves. This image was made using BioRender.com
.
Stability of proteins from rates of oxidation (SPROX)
Stability of Proteins from Rates of Oxidation also rests upon the assumption that
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.[16]
Affinity selection-mass spectrometry
While adoption of affinity selection-mass spectrometry (AS-MS) has led to an expansion of assay formats,
compounds per experiment have been reported in the literature, and one group has reported assaying chemical libraries against heterogeneousprotein pools.[20]
The basic steps of AS-MS are described in more detail below.
gel filtration column. Protein-bound compounds move around the beads and exit the column quickly. Unbound compounds are small enough to travel through beads and take a longer path before elution. This image was made using BioRender.com
.
Affinity selection
A generalized AS-MS workflow begins with the pre-incubation of
millimolar solutions, effectively capping the number of compounds screened in the thousands.[20] After appropriate test compounds and targets are selected and incubated, ligand-protein complexes can be separated by a variety of means.[19]
Separation of unbound small molecules and ligand-protein complexes
Affinity selection is followed by the removal of unbound
gel filtration chromatography, which allows for simultaneous removal of unbound ligands from up to 96 samples.[21] Samples are also passed through porous beads, but centrifugation is used to move the sample through the column.[21] SpeedScreen is not coupled to an LC-MS system and requires further processing prior to final analysis. In this case, ligands
must be freed from their targets and analyzed separately.
LC-MS/MS. Drug and protein elution profiles are constructed and correlated. Target identification is supported by a strong correlation in elution profile between a drug and a protein. This image was made using BioRender.com
.
Target identification by chromatographic co-elution (TICC)
Target identification by
ion-exchange chromatography system and fractionated. Lysate proteins are eluted along an ionic strength gradient and fractions are collected over short time intervals. Each fraction is analyzed by LC-MS/MS for both protein and drug content. Individual proteins elute with characteristic profiles, and pre-incubated drugs should mirror the elution profiles of the targets they complex with. Correlation of drug and protein elution profiles allows for targets to be narrowed down and inferred.[22]
Computational approaches
Molecular docking simulations
The development and application of bench-top chemoproteomics assays is often time consuming and cost-prohibitive.
Molecular docking strategies are categorized by the type of information that is already known about the ligand and protein of interest.[23]
Ligand-based methods
An example pharmacophore model. Each sphere represents a different scorable feature.
When a
least-squares regression for superimposition, but this requires user-selected anchor points and therefore introduces human bias into the process. Pharmacophore models require training data sets, giving rise to another challenge—selection of the appropriate library of compounds to adequately train models. Data set size and chemical diversity significantly affect performance of the downstream product.[25]
Structure-based methods
Ideally, the structure of a drug target is known, which allows for
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.[24]
Applications
Druggability
ubiquitination
of the target by the E3 ubiquitin ligase, leading to target degradation.
Chemoproteomic strategies have been used to expand the scope of
E3 ubiquitin ligase. The interaction brings the E3 ubiquitin ligase close enough to the target that the target is labeled for degradation. The existence of potential covalent binding sites across the proteome suggests that many drugs can be covalently targeted using such a modality.[26]
Drug repurposing
Chemoproteomics is at the forefront of
drug repurposing. This is particularly relevant in the era of COVID-19, which saw a dire need to rapidly identify FDAapproved drugs that have antiviral activity.[27] 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 antiviralRemdesivir, which was among the first repurposed drugs to be used in the pandemic.[27] Remdesivir was tested via thermal proteome profiling in a HepG2cellular thermal shift assay, along with the controversial drug hydroxychloroquine, and investigators discovered TRIP13 as a potential off-target of Remdesivir.[27]
High-throughput screening
Approved drugs are never identified as hits in
proteins.[20] 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.[20]
Real World Applications of Chemoproteomic Techniques
Knockaert et al confirmed CDKs and discovered CK1 as targets of purvanolol; CK1 is a Plasmodium protein, and purvanolol analogs have activity against Plasmodium.
Merck & Co. used AS-MS to successfully screen for ligands against the difficult to drug STING protein, which has a large binding site and strong competing endogenous ligand
