Image-Based Annotation of Chemogenomic Libraries for Phenotypic Screening

Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still pose a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.

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.

Application of Advanced Technologies in Natural Product Research: A Review with Special Emphasis on ADMET Profiling

The successful conversion of natural products (NPs) into lead compounds and novel pharmacophores has emboldened the researchers to harness the drug discovery process with a lot more enthusiasm. However, forfeit of bioactive NPs resulting from an overabundance of metabolites and their wide dynamic range have created the bottleneck in NP researches. Similarly, the existence of multidimensional challenges, including the evaluation of pharmacokinetics, pharmacodynamics, and safety parameters, has been a concerning issue. Advancement of technology has brought the evolution of traditional natural product researches into the computer-based assessment exhibiting pretentious remarks about their efficiency in drug discovery. The early attention to the quality of the NPs may reduce the attrition rate of drug candidates by parallel assessment of ADMET profiling. This article reviews the status, challenges, opportunities, and integration of advanced technologies in natural product research. Indeed, emphasis will be laid on the current and futuristic direction towards the application of newer technologies in early-stage ADMET profiling of bioactive moieties from the natural sources. It can be expected that combinatorial approaches in ADMET profiling will fortify the natural product-based drug discovery in the near future.

Target engagement approaches for pharmacological evaluation in animal models

The field of chemical biology has introduced several approaches, typically using chemical probes, to measure the direct binding interaction of a small molecule with its biological target in cells. The use of these direct target engagement assays in pharmaceutical development can support mechanism of action hypothesis testing, rank ordering of compounds, and iterative improvements of chemical matter. This Feature Article highlights a newer application of these approaches: the quantification of target engagement in animal models to support late stage preclinical development and the nomination of a drug candidate to clinical trials. Broadly speaking, these efforts can be divided between compounds that covalently and reversibly interact with protein targets; recent examples for both categories are discussed for a range of targets, along with their limitations. New, promising technologies are also highlighted, in addition to the application of target engagement determination to new therapeutic modalities.

Controlling cellular distribution of drugs with permeability modifying moieties

Phenotypic screening provides compounds with very limited target cellular localization data. In order to select the most appropriate target identification methods, determining if a compound acts at the cell-surface or intracellularly can be very valuable. In addition, controlling cell-permeability of targeted therapeutics such as antibody-drug conjugates (ADCs) and targeted nanoparticle formulations can reduce toxicity from extracellular release of drug in undesired tissues or direct activity in bystander cells. By incorporating highly polar, anionic moieties via short polyethylene glycol linkers into compounds with known intracellular, and cell-surface targets, we have been able to correlate the cellular activity of compounds with their subcellular site of action. For compounds with nuclear (Brd, PARP) or cytosolic (dasatinib, NAMPT) targets, addition of the permeability modifying group (small sulfonic acid, polycarboxylic acid, or a polysulfonated fluorescent dye) results in near complete loss of biological activity in cell-based assays. For cell-surface targets (H3, 5HT1A, β2AR) significant activity was maintained for all conjugates, but the results were more nuanced in that the modifiers impacted binding/activity of the resulting conjugates. Taken together, these results demonstrate that small anionic compounds can be used to control cell-permeability independent of on-target activity and should find utility in guiding target deconvolution studies and controlling drug distribution of targeted therapeutics.

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.

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.

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.

Discovery and Characterization of Novel Nonsubstrate and Substrate NAMPT Inhibitors

Cancer cells are highly reliant on NAD⁺-dependent processes, including glucose metabolism, calcium signaling, DNA repair, and regulation of gene expression. Nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting enzyme for NAD⁺ salvage from nicotinamide, has been investigated as a target for anticancer therapy. Known NAMPT inhibitors with potent cell activity are composed of a nitrogen-containing aromatic group, which is phosphoribosylated by the enzyme. Here, we identified two novel types of NAM-competitive NAMPT inhibitors, only one of which contains a modifiable, aromatic nitrogen that could be a phosphoribosyl acceptor. Both types of compound effectively deplete cellular NAD⁺, and subsequently ATP, and produce cell death when NAMPT is inhibited in cultured cells for more than 48 hours. Careful characterization of the kinetics of NAMPT inhibition in vivo allowed us to optimize dosing to produce sufficient NAD⁺ depletion over time that resulted in efficacy in an HCT116 xenograft model. Our data demonstrate that direct phosphoribosylation of competitive inhibitors by the NAMPT enzyme is not required for potent in vitro cellular activity or in vivo antitumor efficacy. Mol Cancer Ther; 16(7); 1236-45. ©2017 AACR.

Applications of chemogenomic library screening in drug discovery

The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography.

FK506, an Immunosuppressive Drug, Induces Autophagy by Binding to the V-ATPase Catalytic Subunit A in Neuronal Cells

The drug FK506 (tacrolimus, fujimycin) exerts its immunosuppressive effects by regulating the nuclear factor of the activated T-cell (NFAT) family of transcription factors. However, FK506 also exhibits neuroprotective effects, but its direct target proteins that mediate these effects have not been determined. To identify the target proteins responsible for FK506's neuroprotective effects, the drug affinity responsive target stability (DARTS) method was performed using label-free FK506, and LC-MS/MS analysis of the FK506-treated proteome was also performed. Using DARTS and LC-MS/MS analyses in combination with reference studies, V-ATPase catalytic subunit A (ATP6V1A) was identified as a new target protein of FK506. The biological relevance of ATP6V1A in mediating the neuroprotective effects of FK506 was validated by analyzing FK506 activity with respect to autophagy via acridine orange staining and transcription factor EB (TFEB) translocation assay. These analyses demonstrated that the binding of FK506 with ATP6V1A induces autophagy by activating the translocation of TFEB from the cytosol into the nucleus. Because autophagy has been identified as a mechanism for treating neurodegenerative diseases and because we have demonstrated that FK506 induces autophagy, this study demonstrates that FK506 is a possible new therapy for treating neurodegenerative diseases.

Current status and future prospects for enabling chemistry technology in the drug discovery process

This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of "dangerous" reagents. Also featured are advances in the "computer-assisted drug design" area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.

Next-generation phenotypic screening

Phenotypic drug discovery (PDD) strategies are defined by screening and selection of hit or lead compounds based on quantifiable phenotypic endpoints without prior knowledge of the drug target. We outline the challenges associated with traditional phenotypic screening strategies and propose solutions and new opportunities to be gained by adopting modern PDD technologies. We highlight both historical and recent examples of approved drugs and new drug candidates discovered by modern phenotypic screening. Finally, we offer a prospective view of a new era of PDD underpinned by a wealth of technology advances in the areas of in vitro model development, high-content imaging and image informatics, mechanism-of-action profiling and target deconvolution.