Emerging Methods in Chemoproteomics with Relevance to Drug Discovery

Targeting RNA with small molecules-A safety perspective

RNA is a major player in cellular function, and consequently can drive a number of disease pathologies. Over the past several years, small molecule-RNA targeting (smRNA targeting) has developed into a promising drug discovery approach. Numerous techniques, tools, and assays have been developed to support this field, and significant investments have been made by pharmaceutical and biotechnology companies. To date, the focus has been on identifying disease validated primary targets for smRNA drug development, yet RNA as a secondary (off) target for all small molecule drug programs largely has been unexplored. In this perspective, we discuss structure, target, and mechanism-driven safety aspects of smRNAs and highlight how these parameters can be evaluated in drug discovery programs to produce potentially safer drugs.

Recent Advances in PROTACs for Drug Targeted Protein Research

Proteolysis-targeting chimera (PROTAC) is a heterobifunctional molecule. Typically, PROTAC consists of two terminals which are the ligand of the protein of interest (POI) and the specific ligand of E3 ubiquitin ligase, respectively, via a suitable linker. PROTAC degradation of the target protein is performed through the ubiquitin–proteasome system (UPS). The general process is that PROTAC binds to the target protein and E3 ligase to form a ternary complex and label the target protein with ubiquitination. The ubiquitinated protein is recognized and degraded by the proteasome in the cell. At present, PROTAC, as a new type of drug, has been developed to degrade a variety of cancer target proteins and other disease target proteins, and has shown good curative effects on a variety of diseases. For example, PROTACs targeting AR, BR, BTK, Tau, IRAK4, and other proteins have shown unprecedented clinical efficacy in cancers, neurodegenerative diseases, inflammations, and other fields. Recently, PROTAC has entered a phase of rapid development, opening a new field for biomedical research and development. This paper reviews the various fields of targeted protein degradation by PROTAC in recent years and summarizes and prospects the hot targets and indications of PROTAC.

ABPP-HT*-Deep Meets Fast for Activity-Based Profiling of Deubiquitylating Enzymes Using Advanced DIA Mass Spectrometry Methods

Activity-based protein profiling (ABPP) uses a combination of activity-based chemical probes with mass spectrometry (MS) to selectively characterise a particular enzyme or enzyme class. ABPP has proven invaluable for profiling enzymatic inhibitors in drug discovery. When applied to cell extracts and cells, challenging the ABP-enzyme complex formation with a small molecule can simultaneously inform on potency, selectivity, reversibility/binding affinity, permeability, and stability. ABPP can also be applied to pharmacodynamic studies to inform on cellular target engagement within specific organs when applied to in vivo models. Recently, we established separate high depth and high throughput ABPP (ABPP-HT) protocols for the profiling of deubiquitylating enzymes (DUBs). However, the combination of the two, deep and fast, in one method has been elusive. To further increase the sensitivity of the current ABPP-HT workflow, we implemented state-of-the-art data-independent acquisition (DIA) and data-dependent acquisition (DDA) MS analysis tools. Hereby, we describe an improved methodology, ABPP-HT* (enhanced high-throughput-compatible activity-based protein profiling) that in combination with DIA MS methods, allowed for the consistent profiling of 35-40 DUBs and provided a reduced number of missing values, whilst maintaining a throughput of 100 samples per day.

PROTACs technology for targeting non-oncoproteins: Advances and perspectives

Proteolysis targeting chimeras (PROTACs) have been developed to be an effective technology for targeted protein degradation. Each PROTAC contains three key components: a protein-of-interest (POI) ligand, an E3 ligase ligand, and a linker. These bifunctional molecules can hijack the intracellular inherent ubiquitin-proteasome system to degrade different POIs. With several advantages over other therapeutic strategies, PROTACs have set off a new upsurge of drug discovery in recent years. PRTOACs have been extensively explored worldwide and have excelled not only in cancer diseases but also in cardiovascular diseases, fatty liver disease, immune diseases, neurodegenerative diseases, and viral infections. In this review, we aim to summarize the rapid progress from 2010 to 2021 in PROTACs targeting various non-oncoproteins and elucidate the advantages of PROTACs technology. Finally, the potential challenges of this dynamic field are also discussed.

Bim transfer between Bcl-2-like protein and Hsp70 underlines Bcl-2/Hsp70 crosstalk to regulate apoptosis

The chaperone heat shock protein 70 (Hsp70) is crucial for avoiding protein misfolding under stress, but it is also upregulated in many kinds of cancers, where its ability to buffer cellular stress prevents apoptosis. Previous research has suggested that Bim, a BH3-only member of the Bcl-2 family proteins, also serves as a cochaperone for Hsp70, which modulates the folding and stabilization of many Hsp70 oncogenic substrates in tumor cells. However, a definitive demonstration of crosstalk between Bcl-2 and Hsp70 family proteins and molecular mechanism remain unclear. Herein, we examined the effects of pan-Bcl-2 inhibitor S1, Hsp70 inhibitor S1g-6 on the K562, U937, H23, HL-60 cell lines and these inhibitors synergistically induce mitochondrial apoptosis in cancer cell lines. Moreover, we identified that Bim transfer between Bcl-2-like protein and Hsp70 underlines Bcl-2/Hsp70 crosstalk in mitochondrial apoptosis pathway. Thus, the synergy of S1 and S1g-6 to induce a panel of cancer cell lines apoptosis by inhibiting free Bim and facilitating oncogenic client AKT folding and activation. Together, our results demonstrated the combination of Bcl-2 inhibitor and Hsp70 inhibitor showed synergistic effect in cancer cells and the potential to decrease tumor regression.

ABPP-HT - High-Throughput Activity-Based Profiling of Deubiquitylating Enzyme Inhibitors in a Cellular Context

The potency and selectivity of a small molecule inhibitor are key parameters to assess during the early stages of drug discovery. In particular, it is very informative for characterizing compounds in a relevant cellular context in order to reveal potential off-target effects and drug efficacy. Activity-based probes are valuable tools for that purpose, however, obtaining cellular target engagement data in a high-throughput format has been particularly challenging. Here, we describe a new methodology named ABPP-HT (high-throughput-compatible activity-based protein profiling), implementing a semi-automated proteomic sample preparation workflow that increases the throughput capabilities of the classical ABPP workflow approximately ten times while preserving its enzyme profiling characteristics. Using a panel of deubiquitylating enzyme (DUB) inhibitors, we demonstrate the feasibility of ABPP-HT to provide compound selectivity profiles of endogenous DUBs in a cellular context at a fraction of time as compared to previous methodologies.

The antimalarial resistome - finding new drug targets and their modes of action

To this day, malaria remains a global burden, affecting millions of people, especially those in sub-Saharan Africa and Asia. The rise of drug resistance to current antimalarial treatments, including artemisinin-based combination therapies, has made discovering new small molecule compounds with novel modes of action an urgent matter. The concerted effort to construct enormous compound libraries and develop high-throughput phenotypic screening assays to find compounds effective at specifically clearing malaria-causing Plasmodium parasites at any stage of the life cycle has provided many antimalarial prospects, but does not indicate their target or mode of action. Here, we review recent advances in antimalarial drug discovery efforts, focusing on the following 'omics' approaches in mode of action studies: IVIEWGA, CETSA, metabolomic profiling.

Analysing the nanoparticle-protein corona for potential molecular target identification

When nanoparticles are introduced into biological systems, host proteins tend to associate on the particle surface to form a protein layer termed the "protein corona" (PC). Identifying the proteins that constitute the PC can yield useful information about nanoparticle processing, bio-distribution, toxicity and clearance. Similarly, characterizing and identifying proteins within the PC from patient samples provides opportunities to probe disease proteomes and identify molecules that influence the disease process. Thus, nanoparticles represent unique probing tools for discovery of molecular targets for diseases. Here, we report a first review on target identification using nanoparticles in biological samples based on analysing physico chemical interactions. We also summarize the evolution of the PC surrounding various nano-systems, comment on PC signature, address PC complexity in fluids, and outline challenges associated with analysing the PC. In addition, the influence on PC formation of various nanoparticle parameters is summarized; nanoparticle characteristics considered include size, charge, temperature, and surface modifications for both organic and inorganic nanomaterials. We also discuss the advantages of nanotechnology, over other more invasive and laborious methods, for identifying potential diagnostic and therapeutic targets.

PROTACs: great opportunities for academia and industry

Although many kinds of therapies are applied in the clinic, drug-resistance is a major and unavoidable problem. Another disturbing statistic is the limited number of drug targets, which are presently only 20-25% of all protein targets that are currently being studied. Moreover, the focus of current explorations of targets are their enzymatic functions, which ignores the functions from their scaffold moiety. As a promising and appealing technology, PROteolysis TArgeting Chimeras (PROTACs) have attracted great attention both from academia and industry for finding available approaches to solve the above problems. PROTACs regulate protein function by degrading target proteins instead of inhibiting them, providing more sensitivity to drug-resistant targets and a greater chance to affect the nonenzymatic functions. PROTACs have been proven to show better selectivity compared to classic inhibitors. PROTACs can be described as a chemical knockdown approach with rapidity and reversibility, which presents new and different biology compared to other gene editing tools by avoiding misinterpretations that arise from potential genetic compensation and/or spontaneous mutations. PRTOACs have been widely explored throughout the world and have outperformed not only in cancer diseases, but also in immune disorders, viral infections and neurodegenerative diseases. Although PROTACs present a very promising and powerful approach for crossing the hurdles of present drug discovery and tool development in biology, more efforts are needed to gain to get deeper insight into the efficacy and safety of PROTACs in the clinic. More target binders and more E3 ligases applicable for developing PROTACs are waiting for exploration.

An omics perspective on drug target discovery platforms

The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to disease, and to evaluate the efficacy, safety and commercial potential of the target. The high-throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased the volume of scientific data available for this arduous task. Therefore, computational platforms identifying and ranking disease-relevant targets from existing biomedical data sources, including omics databases, are needed. To date, more than 30 drug target discovery (DTD) platforms exist. They provide information-rich databases and graphical user interfaces to help scientists identify putative targets and pre-evaluate their therapeutic efficacy and potential side effects. Here we survey and compare a set of popular DTD platforms that utilize multiple data sources and omics-driven knowledge bases (either directly or indirectly) for identifying drug targets. We also provide a description of omics technologies and related data repositories which are important for DTD tasks.

Argentilactone Molecular Targets in Paracoccidioides brasiliensis Identified by Chemoproteomics

Paracoccidioidomycosis (PCM) is the cause of many deaths from systemic mycoses. The etiological agents of PCM belong to the Paracoccidioides genus, which is restricted to Latin America. The infection is acquired through the inhalation of conidia that primarily lodge in the lungs and may disseminate to other organs and tissues. The treatment for PCM is commonly performed via the administration of antifungals such as amphotericin B, co-trimoxazole, and itraconazole. The antifungal toxicity and side effects, in addition to their long treatment times, have stimulated research for new bioactive compounds. Argentilactone is a compound that was isolated from the Brazilian savanna plant Hyptis ovalifolia, and it has been suggested to be a potent antifungal, inhibiting the dimorphism of P. brasiliensis and the enzymatic activity of isocitrate lyase, a key enzyme of the glyoxylate cycle. This work was developed due to the importance of elucidating the putative mode of action of argentilactone. The chemoproteomics approach via affinity chromatography was the methodology used to explore the interactions between P. brasiliensis proteins and argentilactone. A total of 109 proteins were identified and classified functionally. The most representative functional categories were related to amino acid metabolism, energy, and detoxification. Argentilactone inhibited the enzymatic activity of malate dehydrogenase, citrate synthase, and pyruvate dehydrogenase. Furthermore, argentilactone induces the production of reactive oxygen species and inhibits the biosynthesis of cell wall polymers.

Impact of Mass Spectrometry-Based Technologies and Strategies on Chemoproteomics as a Tool for Drug Discovery

Chemoproteomics is an invaluable tool to discover protein targets from phenotypic assays and to understand on- and off-target engagement of potential therapeutic compounds. Highlighted in this technology perspective is our view on how improvements in mass spectrometry (MS)-based proteomics technology have dramatically impacted chemoproteomics. Improvements in sample preparation, MS instrumentation, data acquisition, and quantification strategies have enabled medicinal chemists, chemical biologists, and mass spectrometrists to develop new chemoproteomic experiments and improve existing methods. As a result of improvements in MS, we will detail how bead-based affinity capture and activity-based proteome profiling methods have been reduced from multiple LC-MS runs for samples and controls down to a single LC-MS run each for sample and control. With improvements in scan duty cycle and sensitivity, sufficient depth of proteome coverage can be obtained for capture-free methods, which do not utilize an enrichment step.

Protac-Induced Protein Degradation in Drug Discovery: Breaking the Rules or Just Making New Ones?

Targeted protein degradation, using bifunctional small molecules (Protacs) to remove specific proteins from within cells, has emerged as a novel drug discovery strategy with the potential to offer therapeutic interventions not achievable with existing approaches. In this Perspective, the brief history of the field is surveyed from a drug discovery perspective with a focus on the key advances in knowledge which have led to the definition and exemplification of protein degradation concepts and their resulting applications to medicine discovery. The approach has the potential to bring disruptive change to drug discovery; the many potential advantages and outstanding challenges which lie ahead of this technology are discussed.

Introduction: Cancer Gene Networks

Constructing, evaluating, and interpreting gene networks generally sits within the broader field of systems biology, which continues to emerge rapidly, particular with respect to its application to understanding the complexity of signaling in the context of cancer biology. For the purposes of this volume, we take a broad definition of systems biology. Considering an organism or disease within an organism as a system, systems biology is the study of the integrated and coordinated interactions of the network(s) of genes, their variants both natural and mutated (e.g., polymorphisms, rearrangements, alternate splicing, mutations), their proteins and isoforms, and the organic and inorganic molecules with which they interact, to execute the biochemical reactions (e.g., as enzymes, substrates, products) that reflect the function of that system. Central to systems biology, and perhaps the only approach that can effectively manage the complexity of such systems, is the building of quantitative multiscale predictive models. The predictions of the models can vary substantially depending on the nature of the model and its inputoutput relationships. For example, a model may predict the outcome of a specific molecular reaction(s), a cellular phenotype (e.g., alive, dead, growth arrest, proliferation, and motility), a change in the respective prevalence of cell or subpopulations, a patient or patient subgroup outcome(s). Such models necessarily require computers. Computational modeling can be thought of as using machine learning and related tools to integrate the very high dimensional data generated from modern, high throughput omics technologies including genomics (next generation sequencing), transcriptomics (gene expression microarrays; RNAseq), metabolomics and proteomics (ultra high performance liquid chromatography, mass spectrometry), and "subomic" technologies to study the kinome, methylome, and others. Mathematical modeling can be thought of as the use of ordinary differential equations and related tools to create dynamic, semi-mechanistic models of low dimensional data including gene/protein signaling as a function of time/dose. More recently, the integration of imaging technologies into predictive multiscale modeling has begun to extend further the scales across which data can be obtained and used to gain insight into system function.There are several goals for predictive multiscale modeling including the more academic pursuit of understanding how the system or local feature thereof is regulated or functions, to the more practical or translational goals of identifying predictive (selecting which patient should receive which drug/therapy) or prognostic (disease progress and outcome in an individual patient) biomarkers and/or identifying network vulnerabilities that represent potential targets for therapeutic benefit with existing drugs (including drug repurposing) or for the development of new drugs. These various goals are not necessarily mutually exclusive or inclusive. Within this volume, readers will find examples of many of the activities noted above. Each chapter contains practical and/or methodological insights to guide readers in the design and interpretation of their own and published work.