GDP-capture compound--a novel tool for the profiling of GTPases in pro- and eukaryotes by capture compound mass spectrometry (CCMS)

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.

Affinity-based target identification for bioactive small molecules

A variety of new approaches of affinity-based target identification for bioactive small molecules are being developed, facilitating drug development and understanding complicated biological processes.

Target identification of small molecules based on chemical biology approaches

Recently, a phenotypic approach-screens that assess the effects of compounds on cells, tissues, or whole organisms-has been reconsidered and reintroduced as a complementary strategy of a target-based approach for drug discovery. Although the finding of novel bioactive compounds from large chemical libraries has become routine, the identification of their molecular targets is still a time-consuming and difficult process, making this step rate-limiting in drug development. In the last decade, we and other researchers have amassed a large amount of phenotypic data through progress in omics research and advances in instrumentation. Accordingly, the profiling methodologies using these datasets expertly have emerged to identify and validate specific molecular targets of drug candidates, attaining some progress in current drug discovery (e.g., eribulin). In the case of a compound that shows an unprecedented phenotype likely by inhibiting a first-in-class target, however, such phenotypic profiling is invalid. Under the circumstances, a photo-crosslinking affinity approach should be beneficial. In this review, we describe and summarize recent progress in both affinity-based (direct) and phenotypic profiling (indirect) approaches for chemical biology target identification.

Functional interrogation of kinases and other nucleotide-binding proteins

The largest mammalian enzyme family is the kinases. Kinases and other nucleotide-binding proteins are key regulators of signal transduction pathways and the mutation or overexpression of these proteins is often the difference between health and disease. As a result, a massive research effort has focused on understanding how these proteins function and how to inhibit them for therapeutic benefit. Recent advances in chemical biological tools have enabled functional interrogation of these enzymes to provide a deeper understanding of their physiological roles. In addition, these innovative platforms have paved the way for a new generation of drugs whose properties have been guided by functional profiling.

Chemical proteomics in drug discovery

Real-world drug discovery and development remains a notoriously unproductive and increasingly uneconomical process even in the Omics era. The dominating paradigm in the industry continues to be target-based drug design, with an increased perception of the role of signaling pathways in homeostasis and in disease. Since proteins represent the major type of drug targets, proteomics-based approaches, which study proteins under relatively physiological conditions, have great potential if they can be reduced to practice such that they successfully complement the arsenal of drug discovery techniques. This chapter discusses examples of drug discovery processes where chemical proteomics-based assays using native endogenous proteins should have substantial impact.

Proteome-wide identification of staurosporine-binding kinases using capture compound mass spectrometry

The enormous diversity of kinases and their pivotal role in cell signaling have set kinases in the focus of biomedical research. Profiling the kinome of tissues of different origin is essential for biomarker discovery. In drug research, it is necessary to comprehend the specificity profile of a given kinase inhibitor. Capture Compound Mass Spectrometry (CCMS) (Koster et al., Assay Drug. Dev. Technol. 5:381-390, 2007) addresses the need for a tool to physically isolate and reliably profile the binders of kinase inhibitors directly in biological samples. Capture Compounds™ are trifunctional probes: a selectivity function consisting of the kinase inhibitor interacts reversibly with the native target proteins in equilibrium, a photoactivatable reactivity function forms an irreversible covalent bond to the target protein upon irradiation, and a sorting function allows the captured protein(s) to be isolated and identified by mass spectrometric analysis in an affinity-driven manner. Capture Compounds™ with any kinase inhibitor as selectivity function can be synthesized. We here used staurosporine as the selectivity function because it targets and, therefore, allows profiling a broad range of kinases (Romano and Giordano, Cell Cycle 7:3364-3668, 2008). Furthermore, we give an example of the application of the staurosporine Capture Compound to isolate kinases from human liver-derived HepG2 cells.

SAHA Capture Compound--a novel tool for the profiling of histone deacetylases and the identification of additional vorinostat binders

Suberoylanilide hydroxamic acid (SAHA) is a potent histone deacetylase (HDAC) inhibitor. Inhibitors of HDACs are used in cancer therapy based on the role HDACs play in transcription by regulating chromatin compaction and non-histone proteins such as transcription factors. Profiling of HDAC expression is of interest in the functional proteomics analysis of cancer. Also, non-HDAC proteins may interact with HDAC inhibitor drugs and contribute to the drug mode of action. We here present a tool for the unbiased chemical proteomic profiling of proteins that specifically interact with SAHA. We designed and synthesized a trifunctional Capture Compound containing SAHA as selectivity and identified HDACs1, 2, 3 and 6, known and predicted HDAC interactors from human-derived HepG2 cell lysate, as well as a set of new potential non-HDAC targets of SAHA. One of these non-HDAC targets, isochorismatase domain-containing protein 2 (ISOC2) is putative hydrolase associated with the negative regulation of the tumor-suppressor p16(INK4a). We demonstrated the direct and dose-dependent interaction of SAHA to the purified recombinant ISOC2 protein. Using SAHA Capture Compound mass spectrometry, we thus identified potential new SAHA target proteins in an entirely unbiased chemical proteomics approach.

Studying protein-protein affinity and immobilized ligand-protein affinity interactions using MS-based methods

This review discusses the most important current methods employing mass spectrometry (MS) analysis for the study of protein affinity interactions. The methods are discussed in depth with particular reference to MS-based approaches for analyzing protein-protein and protein-immobilized ligand interactions, analyzed either directly or indirectly. First, we introduce MS methods for the study of intact protein complexes in the gas phase. Next, pull-down methods for affinity-based analysis of protein-protein and protein-immobilized ligand interactions are discussed. Presently, this field of research is often called interactomics or interaction proteomics. A slightly different approach that will be discussed, chemical proteomics, allows one to analyze selectivity profiles of ligands for multiple drug targets and off-targets. Additionally, of particular interest is the use of surface plasmon resonance technologies coupled with MS for the study of protein interactions. The review addresses the principle of each of the methods with a focus on recent developments and the applicability to lead compound generation in drug discovery as well as the elucidation of protein interactions involved in cellular processes. The review focuses on the analysis of bioaffinity interactions of proteins with other proteins and with ligands, where the proteins are considered as the bioactives analyzed by MS.

Drug target deconvolution by chemical proteomics

Drug target deconvolution is a process where the action of a drug, a small molecule, is characterised by identifying the proteins binding the drug and initiating the biological effect. The biological relevant target has to be extracted, or deconvoluted, from a list of proteins identified in such an approach. Beside the medically desired action of the drug, the identification of other proteins binding the drug can help to identify side effects and toxicity at a very early stage of drug development. The current approach to identify the proteins binding to the drug is an affinity-enrichment based approach, where the drug molecule is immobilised to a matrix through a linker and the proteins binding to the drug are identified by proteomics.