Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips

AI approaches for the discovery and validation of drug targets

Artificial intelligence (AI) holds immense promise for accelerating and improving all aspects of drug discovery, not least target discovery and validation. By integrating a diverse range of biological data modalities, AI enables the accurate prediction of drug target properties, ultimately illuminating biological mechanisms of disease and guiding drug discovery strategies. Despite the indisputable potential of AI in drug target discovery, there are many challenges and obstacles yet to be overcome, including dealing with data biases, model interpretability and generalisability, and the validation of predicted drug targets, to name a few. By exploring recent advancements in AI, this review showcases current applications of AI for drug target discovery and offers perspectives on the future of AI for the discovery and validation of drug targets, paving the way for the generation of novel and safer pharmaceuticals.

Recent advances in liposome development for studying protein-lipid interactions

Protein-lipid interactions are crucial for various cellular biological processes like intracellular signaling, membrane transport, and cytoskeletal dynamics. Therefore, studying these interactions is essential to understand and unravel their specific functions. Nevertheless, the interacting proteins of many lipids are poorly understood and still require systematic study. Liposomes are the most well-known and familiar biomimetic systems used to study protein-lipid interactions. Although liposomes have been widely used for studying protein-lipid interactions in classical methods such as the co-flotation assay (CFA), co-sedimentation assay (CSA), and flow cytometric assay (FCA), an overview of their current applications and developments in high-throughput methods is not yet available. Here, we summarize the liposome development in low and high-throughput methods to study protein-lipid interactions. Besides, a constructive comment for each platform is presented to stimulate the advancement of these technologies in the future.

Identifying Protein-Drug Interactions in Cell Lysates Using Histidine Hydrogen Deuterium Exchange

Identifying the targets of a drug is critical to understand the mechanism of action and predicts possible side effects. The conventional approach is capturing interacting proteins by affinity purification. However, it requires drugs to be immobilized to a solid support or derivatized with chemical moieties used for pulling down interacting proteins. Such covalent modifications to drugs may mask a critical recognition site for or alter the binding affinity to their targets. To overcome the drawback, several methods that do not require covalent modifications to drugs have been developed. These methods identify targets by detecting proteins whose thermodynamic stability is enhanced in the presence of drugs. Although the utility of these methods has been demonstrated, the difficulty in identifying low abundant targets is the common problem of these methods. We have developed a new target identification method that increases the likelihood of identifying low abundant targets. The method uses histidine-hydrogen deuterium exchange (His-HDX) as a readout technique to probe the changes in protein stability induced by drugs. The workflow involves incubating cell lysates in various concentrations of a protein denaturant in the presence and absence of a drug in D₂O followed by digestion of the proteins, enrichment of His-containing peptides, and analysis of the enriched His-peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The developed method was successfully applied to identify the interaction between endogenously expressed MAPK14 and its inhibitor in HEK293 cell lysates. The implementation of selective enrichment of histidine-containing peptides in the workflow was a key that enabled identifying the MAPK14-inhibitor interaction.

Sec14 family of lipid transfer proteins in yeasts

The hydrophobicity of lipids prevents their free movement across the cytoplasm. To achieve highly heterogeneous and precisely regulated lipid distribution in different cellular membranes, lipids are transported by lipid transfer proteins (LTPs) in addition to their transport by vesicles. Sec14 family is one of the most extensively studied groups of LTPs. Here we provide an overview of Sec14 family of LTPs in the most studied yeast Saccharomyces cerevisiae as well as in other selected non-Saccharomyces yeasts-Schizosaccharomyces pombe, Kluyveromyces lactis, Candida albicans, Candida glabrata, Cryptococcus neoformans, and Yarrowia lipolytica. Discussed are specificities of Sec14-domain LTPs in various yeasts, their mode of action, subcellular localization, and physiological function. In addition, quite few Sec14 family LTPs are target of antifungal drugs, serve as modifiers of drug resistance or influence virulence of pathologic yeasts. Thus, they represent an important object of study from the perspective of human health.

[From high content screening to target deconvolution: New insights for phenotypic approaches]

The advent of the molecular biology and the completion of the human genome sequencing prompted the pharmaceutical industry to progressively implement target-centric drug discovery strategies. However, concerns regarding the research and development productivity during the last ten years, combined with technological developments in high-content screening, automation, image analysis and artificial intelligence triggered a renewed interest for the phenotypic drug discovery approaches. Target-centric and phenotypic approaches are more and more considered complementary, hence, positioning the target deconvolution on the critical path. This review analyzes the evolution of the target-centric and phenotypic approaches, focusing more specifically on the high-content screening and the target deconvolution technologies currently available.

Saccharomyces cerevisiae and Caffeine Implications on the Eukaryotic Cell

Caffeine-a methylxanthine analogue of the purine bases adenine and guanine-is by far the most consumed neuro-stimulant, being the active principle of widely consumed beverages such as coffee, tea, hot chocolate, and cola. While the best-known action of caffeine is to prevent sleepiness by blocking the adenosine receptors, caffeine exerts a pleiotropic effect on cells, which lead to the activation or inhibition of various cell integrity pathways. The aim of this review is to present the main studies set to investigate the effects of caffeine on cells using the model eukaryotic microorganism Saccharomyces cerevisiae, highlighting the caffeine synergy with external cell stressors, such as irradiation or exposure to various chemical hazards, including cigarette smoke or chemical carcinogens. The review also focuses on the importance of caffeine-related yeast phenotypes used to resolve molecular mechanisms involved in cell signaling through conserved pathways, such as target of rapamycin (TOR) signaling, Pkc1-Mpk1 mitogen activated protein kinase (MAPK) cascade, or Ras/cAMP protein kinase A (PKA) pathway.

Developments and Applications of Functional Protein Microarrays

Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

Technological Advances in Preclinical Drug Evaluation: The Role of -Omics Methods

Preclinical drug development is an essential step in the drug development process where the evaluation of new chemical entities occurs. In particular, preclinical drug development phases include deep analysis of drug candidates' interactions with biomolecules/targets, their safety, toxicity, pharmacokinetics, metabolism by use of assays in vitro and in vivo animal assays. Legal aspects of the required procedures are well-established. Herein, we present a comprehensive summary of current state-of-the art approaches and techniques used in preclinical studies. In particular, we will review the potential of new, -omics methods and platforms for mechanistic evaluation of drug candidates and speed-up of the preclinical evaluation steps.

Turning liabilities into opportunities: Off-target based drug repurposing in cancer

Targeted drugs and precision medicine have transformed the landscape of cancer therapy and significantly improved patient outcomes in many cases. However, as therapies are becoming more and more tailored to smaller patient populations and acquired resistance is limiting the duration of clinical responses, there is an ever increasing demand for new drugs, which is not easily met considering steadily rising drug attrition rates and development costs. Considering these challenges drug repurposing is an attractive complementary approach to traditional drug discovery that can satisfy some of these needs. This is facilitated by the fact that most targeted drugs, despite their implicit connotation, are not singularly specific, but rather display a wide spectrum of target selectivity. Importantly, some of the unintended drug "off-targets" are known anticancer targets in their own right. Others are becoming recognized as such in the process of elucidating off-target mechanisms that in fact are responsible for a drug's anticancer activity, thereby revealing potentially new cancer vulnerabilities. Harnessing such beneficial off-target effects can therefore lead to novel and promising precision medicine approaches. Here, we will discuss experimental and computational methods that are employed to specifically develop single target and network-based off-target repurposing strategies, for instance with drug combinations or polypharmacology drugs. By illustrating concrete examples that have led to clinical translation we will furthermore examine the various scientific and non-scientific factors that cumulatively determine the success of these efforts and thus can inform the future development of new and potentially lifesaving off-target based drug repurposing strategies for cancers that constitute important unmet medical needs.

A rapid absorbance-based growth assay to screen the toxicity of oligomer Aβ42 and protect against cell death in yeast

Multiple lines of evidence show that soluble oligomer forms of amyloid β protein (Aβ₄₂) are the most neurotoxic species in the brain and correlates with the degree of neuronal loss and cognitive deficit in Alzheimer’s disease. Although many studies have used mammalian cells to investigate oligomer Aβ₄₂ toxicity, the use of more simple eukaryotic cellular systems offers advantages for large-scale screening studies. We have previously established and validated budding yeast, Saccharomyces cerevisiae to be a simple and a robust model to study the toxicity of Aβ. Using colony counting based methods, oligomeric Aβ₄₂ was shown to induce dose-dependent cell death in yeast. We have adapted this method for high throughput screening by developing an absorbance-based growth assay. We further validated the assay with treatments previously shown to protect oligomer Aβ₄₂ induced cell death in mammalian and yeast cells. This assay offers a platform for studying underlying mechanisms of oligomer Aβ₄₂ induced cell death using gene deletion/overexpression libraries and developing novel agents that alleviate Aβ₄₂ induced cell death.

Suppression of respiratory growth defect of mitochondrial phosphatidylserine decarboxylase deficient mutant by overproduction of Sfh1, a Sec14 homolog, in yeast

Interorganelle phospholipid transfer is critical for eukaryotic membrane biogenesis. In the yeast Saccharomyces cerevisiae, phosphatidylserine (PS) synthesized by PS synthase, Pss1, in the endoplasmic reticulum (ER) is decarboxylated to phosphatidylethanolamine (PE) by PS decarboxylase, Psd1, in the ER and mitochondria or by Psd2 in the endosome, Golgi, and/or vacuole, but the mechanism of interorganelle PS transport remains to be elucidated. Here we report that Sfh1, a member of Sec14 family proteins of S. cerevisiae, possesses the ability to enhance PE production by Psd2. Overexpression of SFH1 in the strain defective in Psd1 restored its growth on non-fermentable carbon sources and increased the intracellular and mitochondrial PE levels. Sfh1 was found to bind various phospholipids, including PS, in vivo. Bacterially expressed and purified Sfh1 was suggested to have the ability to transport fluorescently labeled PS between liposomes by fluorescence dequenching assay in vitro. Biochemical subcellular fractionation suggested that a fraction of Sfh1 localizes to the endosome, Golgi, and/or vacuole. We propose a model that Sfh1 promotes PE production by Psd2 by transferring phospholipids between the ER and endosome.

Chemical Biology Strategies to Study Autophagy

Growing amount of evidence in the last two decades highlight that macroautophagy (generally referred to as autophagy) is not only indispensable for survival in yeast but also equally important to maintain cellular quality control in higher eukaryotes as well. Importantly, dysfunctional autophagy has been explicitly shown to be involved in various physiological and pathological conditions such as cell death, cancer, neurodegenerative, and other diseases. Therefore, modulation and regulation of the autophagy pathway has emerged as an alternative strategy for the treatment of various disease conditions in the recent years. Several studies have shown genetic or pharmacological modulation of autophagy to be effective in treating cancer, clearing intracellular aggregates and pathogens. Understanding and controlling the autophagic flux, either through a genetic or pharmacological approach is therefore a highly promising approach and of great scientific interest as spatiotemporal and cell-tissue-organ level autophagy regulation is not clearly understood. Indeed, chemical biology approaches that identify small molecule effectors of autophagy have thus a dual benefit: the modulators act as tools to study and understand the process of autophagy, and may also have therapeutic potential. In this review, we discuss different strategies that have appeared to screen and identify potent small molecule modulators of autophagy.

Selective Usage of Isozymes for Stress Response

Isozymes are enzymes with similar sequences that catalyze the same reaction in a given species. In Saccharomyces cerevisiae, most isozymes have major isoforms with high expression levels and minor isoforms with little expression under normal growth conditions. In a proteomic study aimed at identifying yeast protein regulated by rapamycin, we found an interesting phenomenon, that, for several metabolic enzymes, the major isozymes are downregulated while the minor isozymes are upregulated. Through enzymological and biochemical studies, we demonstrate that a rapamycin-upregulated enolase isozyme (ENO1) favors gluconeogenesis and a rapamycin-upregulated alcohol dehydrogenase isozyme (ALD4) promotes the reduction of NAD⁺ to NADH (instead of NADP⁺ to NADPH). Gene deletion study in yeast showed that the ENO1 and ALD4 are important for yeast survival under less-favorable growth conditions. Therefore, our study highlights the different metabolic needs of cells under different conditions and how nature chooses different isozymes to fit the metabolic needs.

Changes of Cell Biochemical States Are Revealed in Protein Homomeric Complex Dynamics

We report here a simple and global strategy to map out gene functions and target pathways of drugs, toxins, or other small molecules based on "homomer dynamics" protein-fragment complementation assays (hdPCA). hdPCA measures changes in self-association (homomerization) of over 3,500 yeast proteins in yeast grown under different conditions. hdPCA complements genetic interaction measurements while eliminating the confounding effects of gene ablation. We demonstrate that hdPCA accurately predicts the effects of two longevity and health span-affecting drugs, the immunosuppressant rapamycin and the type 2 diabetes drug metformin, on cellular pathways. We also discovered an unsuspected global cellular response to metformin that resembles iron deficiency and includes a change in protein-bound iron levels. This discovery opens a new avenue to investigate molecular mechanisms for the prevention or treatment of diabetes, cancers, and other chronic diseases of aging.

Phenotype and target-based chemical biology investigations in cancers

Chemical biology has been attracting a lot of attention because of the key roles of chemical methods and techniques in helping to decipher and manipulate biological systems. Although chemical biology encompasses a broad field, this review will focus on chemical biology aimed at using exogenous chemical probes to interrogate, modify and manipulate biological processes, at the cellular and organismal levels, in a highly controlled and dynamic manner. In this area, many advances have been achieved for cancer biology and therapeutics, from target identification and validation based on active anticancer compounds (forward approaches) to discoveries of anticancer molecules based on some important targets including protein-protein interaction (reverse approaches). Herein we attempt to summarize some recent progresses mainly from China through applying chemical biology approaches to explore molecular mechanisms of carcinogenesis. Additionally, we also outline several new strategies for chemistry to probe cellular activities such as proximity-dependent labeling methods for identifying protein-protein interactions, genetically encoded sensors, and light activating or repressing gene expression system.

Tombusvirus RNA replication depends on the TOR pathway in yeast and plants

Similar to other (+)RNA viruses, tomato bushy stunt virus (TBSV) utilizes metabolites, lipids, membranes, and co-opted host factors during replication. The coordination of cell metabolism and growth with environmental cues is performed by the target of rapamycin (TOR) kinase in eukaryotic cells. In this paper, we find that TBSV replication partially inhibits TOR activity, likely due to recruitment of glycolytic enzymes to the viral replication compartment, which results in reduced ATP levels in the cytosol. Complete inhibition of TOR activity with rapamycin in yeast or AZD8055 inhibitor in plants reduces tombusvirus replication. We find that high glucose concentration, which stimulates TOR activity, enhanced tombusvirus replication in yeast. Depletion of yeast Sch9 or plant S6K1 kinase, a downstream effector of TOR, also inhibited tombusvirus replication in yeast and plant or the assembly of the viral replicase in vitro. Altogether, the TOR pathway is crucial for TBSV to replicate efficiently in hosts.

Decoding the anticancer activity of VO-clioquinol compound: the mechanism of action and cell death pathways in human osteosarcoma cells

Vanadium compounds were studied in recent years by considering them as a representative of a new class of non-platinum metal anticancer drugs. However, a few challenges still remain in the discovery of new molecular targets of these new metallodrugs. Studies on cell signaling pathways related to vanadium compounds have scarcely been reported and so far this information is highly critical for identifying novel targets that play a key role in the antitumor actions of vanadium complexes. This research deals with the alterations in the intracellular signaling pathways promoted by an oxovanadium(iv) complex with the clioquinol (5-chloro-7-iodo-8-quinolinol), VO(CQ)₂, on a human osteosarcoma cell line (MG-63). Herein are reported, for the first time, the antitumor properties of VO(CQ)₂ and the relative abundance of 224 proteins (which are involved in most of the common intracellular pathways) to identify novel targets of the studied complex. Besides, full-length human recombinant AKT1 kinase was produced by using an IVTT system to evaluate the variation of relative tyrosin-phosphorylation levels caused by this compound. The results of the differential protein expression levels reveal several up-regulated proteins such as CASP3, CASP6, CASP7, CASP10, CASP11, Bcl-x, DAPK and down-regulated ones, such as PKB/AKT, DIABLO, among others. Moreover, cell signaling pathways involved in several altered pathways related to the PKC and AP2 family have been identified in both treatments (2.5 and 10 μM) suggesting the crucial antitumoral role of VO(CQ)₂. Finally, it has been demonstrated that this compound (10 μM, 6 h) triggers a decrease of 2-fold in in situ AKT1 expression.

Deciphering the effect of an oxovanadium(iv) complex with the flavonoid chrysin (VOChrys) on intracellular cell signalling pathways in an osteosarcoma cell line

Vanadium complexes were studied during recent years and considered as a representative of a new class of non-platinum metal antitumor agents in combination with their low toxicity. However, a few challenges still remain in the discovery of new molecular targets for these novel metal-based drugs. The study of cell signaling pathways related to vanadium drugs, which is highly critical for identifying specific targets that play an important role in the antitumor activity of vanadium compounds, is scarce. This research deals with the alterations in intracellular signaling pathways promoted by an oxovanadium(iv) complex with the flavonoid chrysin [VO(chrysin)2EtOH]2 (VOChrys) in a human osteosarcoma cell line (MG-63). Herein we report for the first time the effect of [VO(chrysin)2EtOH]2 on the relative abundance of 224 proteins, which are involved in the most common intracellular pathways. Besides, full-length human recombinant (FAK and AKT1) kinases are produced using an in situ IVTT system and then we have evaluated the variation of relative tyrosine-phosphorylation levels caused by the [VO(chrysin)2EtOH]2 compound. The results of the differential protein expression levels reveal that several proteins such as PKB/AKT, PAK, DAPK, Cdk 4, 6 and 7, FADD, AP2, NAK, and JNK, among others, were altered. Moreover, cell signaling pathways related to the PTK2B, FAK, PKC families suggests an important role associated with the antitumor activity of [VO(chrysin)2EtOH]2 was demonstrated. Finally, the effect of this compound on in situ expressed FAK and AKT1 is validated by determining the phosphorylation level, which decreased in the former and increased in the latter.

Systematic Identification of Mycobacterium tuberculosis Effectors Reveals that BfrB Suppresses Innate Immunity

Mycobacterium tuberculosis (Mtb) has evolved multiple strategies to counter the human immune system. The effectors of Mtb play important roles in the interactions with the host. However, because of the lack of highly efficient strategies, there are only a handful of known Mtb effectors, thus hampering our understanding of Mtb pathogenesis. In this study, we probed Mtb proteome microarray with biotinylated whole-cell lysates of human macrophages, identifying 26 Mtb membrane proteins and secreted proteins that bind to macrophage proteins. Combining GST pull-down with mass spectroscopy then enabled the specific identification of all binders. We refer to this proteome microarray-based strategy as SOPHIE (Systematic unlOcking of Pathogen and Host Interacting Effectors). Detailed investigation of a novel effector identified here, the iron storage protein BfrB (Rv3841), revealed that BfrB inhibits NF-κB-dependent transcription through binding and reducing the nuclear abundance of the ribosomal protein S3 (RPS3), which is a functional subunit of NF- κB. The importance of this interaction was evidenced by the promotion of survival in macrophages of the mycobacteria, Mycobacterium smegmatis, by overexpression of BfrB. Thus, beyond demonstrating the power of SOPHIE in the discovery of novel effectors of human pathogens, we expect that the set of Mtb effectors identified in this work will greatly facilitate the understanding of the pathogenesis of Mtb, possibly leading to additional potential molecular targets in the battle against tuberculosis.

Edge-based sensitivity analysis of signaling networks by using Boolean dynamics

MOTIVATION

Biological networks are composed of molecular components and their interactions represented by nodes and edges, respectively, in a graph model. Based on this model, there were many studies with respect to effects of node-based mutations on the network dynamics, whereas little attention was paid to edgetic mutations so far.

RESULTS

In this paper, we defined an edgetic sensitivity measure that quantifies how likely a converging attractor is changed by edge-removal mutations in a Boolean network model. Through extensive simulations based on that measure, we found interesting properties of highly sensitive edges in both random and real signaling networks. First, the sensitive edges in random networks tend to link two end nodes both of which are susceptible to node-knockout mutations. Interestingly, it was analogous to an observation that the sensitive edges in human signaling networks are likely to connect drug-target genes. We further observed that the edgetic sensitivity predicted drug-targets better than the node-based sensitivity. In addition, the sensitive edges showed distinguished structural characteristics such as a lower connectivity, more involving feedback loops and a higher betweenness. Moreover, their gene-ontology enrichments were clearly different from the other edges. We also observed that genes incident to the highly sensitive interactions are more central by forming a considerably large connected component in human signaling networks. Finally, we validated our approach by showing that most sensitive interactions are promising edgetic drug-targets in p53 cancer and T-cell apoptosis networks. Taken together, the edgetic sensitivity is valuable to understand the complex dynamics of signaling networks.

CONTACT

kwonyk@ulsan.ac.kr

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A novel dual luciferase based high throughput assay to monitor autophagy in real time in yeast S. cerevisiae

BACKGROUND

Macroautophagy is a cellular response to starvation wherein superfluous and damaged cytoplasmic constituents are degraded to provide energy for survival and to maintain cellular homeostasis. Dysfunctional autophagy is attributed to disease progression in several pathological conditions and therefore, autophagy has appeared as a potential pharmacological target for such conditions.

OBJECTIVE

In search of potential drugs that modulate autophagy, identifying small molecule effectors of autophagy is the primary step. The conventional autophagy assays have a limitation that they cannot be scaled down to a high throughput format, therefore, novel sensitive assays are needed to discover new candidate molecules. Keeping this rationale in mind, a dual luciferase based assay was developed in the yeast S. cerevisiae that could measure both selective and general autophagy in real time.

METHODS

Firefly and Renilla luciferase reporter genes were cloned under POT-1 promoter. Using fatty acid medium the promoter was induced and the luciferase cargo was allowed to build up. The cells were then transferred to starvation conditions to stimulate autophagy and the degradation of luciferase markers was followed with time.

RESULTS AND CONCLUSION

The assay was more sensitive than conventional assays and could be scaled down to a 384 well format using an automated system. A good Z-factor score indicated that the assay is highly suitable for High Throughput Screening (HTS) of small molecule libraries. Screening of a small molecule library with our assay identified several known and novel modulators of autophagy.

Relations between Effects and Structure of Small Bicyclic Molecules on the Complex Model System Saccharomyces cerevisiae

The development of compounds able to modify biological functions largely took advantage of parallel synthesis to generate a broad chemical variance of compounds to be tested for the desired effect(s). The budding yeast Saccharomyces cerevisiae is a model for pharmacological studies since a long time as it represents a relatively simple system to explore the relations among chemical variance and bioactivity. To identify relations between the chemical features of the molecules and their activity, we delved into the effects of a library of small compounds on the viability of a set of S. cerevisiae strains. Thanks to the high degree of chemical diversity of the tested compounds and to the measured effect on the yeast growth rate, we were able to scale-down the chemical library and to gain information on the most effective structures at the substituent level. Our results represent a valuable source for the selection, rational design, and optimization of bioactive compounds.

Protein Array-based Approaches for Biomarker Discovery in Cancer

Biomarkers are deemed to be potential tools in early diagnosis, therapeutic monitoring, and prognosis evaluation for cancer, with simplicity as well as economic advantages compared with computed tomography and biopsy. However, most of the current cancer biomarkers present insufficient sensitivity as well as specificity. Therefore, there is urgent requirement for the discovery of biomarkers for cancer. As one of the most exciting emerging technologies, protein array provides a versatile and robust platform in cancer proteomics research because it shows tremendous advantages of miniaturized features, high throughput, and sensitive detections in last decades. Here, we will present a relatively complete picture on the characteristics and advance of different types of protein arrays in application for biomarker discovery in cancer, and give the future perspectives in this area of research.

Integrated Strategies to Gain a Systems-Level View of Dynamic Signaling Networks

In order to survive and function properly in the face of an ever changing environment, cells must be able to sense changes in their surroundings and respond accordingly. Cells process information about their environment through complex signaling networks composed of many discrete signaling molecules. Individual pathways within these networks are often tightly integrated and highly dynamic, allowing cells to respond to a given stimulus (or, as is typically the case under physiological conditions, a combination of stimuli) in a specific and appropriate manner. However, due to the size and complexity of many cellular signaling networks, it is often difficult to predict how cellular signaling networks will respond under a particular set of conditions. Indeed, crosstalk between individual signaling pathways may lead to responses that are nonintuitive (or even counterintuitive) based on examination of the individual pathways in isolation. Therefore, to gain a more comprehensive view of cell signaling processes, it is important to understand how signaling networks behave at the systems level. This requires integrated strategies that combine quantitative experimental data with computational models. In this chapter, we first examine some of the progress that has recently been made toward understanding the systems-level regulation of cellular signaling networks, with a particular emphasis on phosphorylation-dependent signaling networks. We then discuss how genetically targetable fluorescent biosensors are being used together with computational models to gain unique insights into the spatiotemporal regulation of signaling networks within single, living cells.

Protein-Protein Interaction Inhibitors of BRCA1 Discovered Using Small Molecule Microarrays

Microarray screening technology has transformed the life sciences arena over the last decade. The platform is widely used in the area of mapping interaction networks, to molecular fingerprinting and small molecular inhibitor discovery. The technique has significantly impacted both basic and applied research. The microarray platform can likewise enable high-throughput screening and discovery of protein-protein interaction (PPI) inhibitors. Herein we demonstrate the application of microarray-guided PPI inhibitor discovery, using human BRCA1 as an example. Mutations in BRCA1 have been implicated in ~50 % of hereditary breast cancers. By targeting the (BRCT)₂ domain, we showed compound 15a and its prodrug 15b inhibited BRCA1 activities in tumor cells. Unlike previously reported peptide-based PPI inhibitors of BRCA1, the compounds identified could be directly administered to tumor cells, thus making them useful in targeting BRCA1/PARP-related pathways involved in DNA damage and repair response, for cancer therapy.

Candida species Rewired Hyphae Developmental Programs for Chlamydospore Formation

Chlamydospore formation is a characteristic of many fungal species, among them the closely related human-pathogenic dimorphic yeasts Candida albicans and C. dubliniensis. Whereas function and regulation of filamentation are well-studied in these species, the basis of chlamydospore formation is mostly unknown. Here, we investigate the contribution of environmental and genetic factors and identified central proteins involved in species-specific regulation of chlamydosporulation. We show that specific nutrient levels strongly impact chlamydospore initiation, with starvation favoring sporulation and elevated levels of saccharides or peptone inhibiting it. Thresholds for these nutritional effects differ between C. albicans and C. dubliniensis, which explain species-specific chlamydospore formation on certain diagnostic media. A C. albicans nrg1Δ mutant phenocopied C. dubliniensis, putting Nrg1 regulation at the basis of species-specific chlamydospore formation under various conditions. By screening a series of potential chlamydospore regulators, we identified the TOR and cAMP pathways as crucial for sporulation. As rapamycin treatment blocked chlamydosporulation, a low basal Tor1 activity seems to be essential. In addition, TOR effector pathways play an important role, and loss of the NCR (nitrogen catabolite repression) gene regulators Gat1 and Gln3 reduced chlamydospore formation. A severe reduction was seen for a C. albicans gcn4Δ deletion strain, implicating a link between regulation of amino acid biosynthesis and chlamydospore development. On the other hand, deletion of the GTPase gene RAS1 and the adenylyl cyclase gene CYR1 caused a defect in chlamydospore formation that was mostly rescued by cAMP supplementation. Thus, cAMP-signaling is a second major pathway to control chlamydospore production. Finally, we confirmed light exposure to have a repressive effect on chlamydosporulation. However, permanent illumination only reduced, but not abolished chlamydospore production of C. albicans whereas C. dubliniensis sporulation was unaffected. In summary, we describe novel environmental factors which determine chlamydosporulation and propose a first model for the regulatory network of chlamydospore formation by different Candida species.

Selectivity Determination of a Small Molecule Chemical Probe Using Protein Microarray and Affinity Capture Techniques

Small molecule selectivity is an essential component of candidate drug selection and target validation. New technologies are required to better understand off-target effects, with particular emphasis needed on broad protein profiling. Here, we describe the use of a tritiated chemical probe and a 9000 human protein microarray to discern the binding selectivity of an inhibitor of the mRNA decapping scavenger enzyme DcpS. An immobilized m⁷GTP resin was also used to assess the selectivity of a DcpS inhibitor against mRNA cap-associated proteins in whole cell extracts. These studies confirm the exquisite selectivity of diaminoquinazoline DcpS inhibitors, and highlight the utility of relatively simple protein microarray and affinity enrichment technologies in drug discovery and chemical biology.

Protein microarray applications: Autoantibody detection and posttranslational modification

The discovery of DNA microarrays was a major milestone in genomics; however, it could not adequately predict the structure or dynamics of underlying protein entities, which are the ultimate effector molecules in a cell. Protein microarrays allow simultaneous study of thousands of proteins/peptides, and various advancements in array technologies have made this platform suitable for several diagnostic and functional studies. Antibody arrays enable researchers to quantify the abundance of target proteins in biological fluids and assess PTMs by using the antibodies. Protein microarrays have been used to assess protein-protein interactions, protein-ligand interactions, and autoantibody profiling in various disease conditions. Here, we summarize different microarray platforms with focus on its biological and clinical applications in autoantibody profiling and PTM studies. We also enumerate the potential of tissue microarrays to validate findings from protein arrays as well as other approaches, highlighting their significance in proteomics.

The Potentials and Pitfalls of Microarrays in Neglected Tropical Diseases: A Focus on Human Filarial Infections

Data obtained from expression microarrays enables deeper understanding of the molecular signatures of infectious diseases. It provides rapid and accurate information on how infections affect the clustering of gene expression profiles, pathways and networks that are transcriptionally active during various infection states compared to conventional diagnostic methods, which primarily focus on single genes or proteins. Thus, microarray technologies offer advantages in understanding host-parasite interactions associated with filarial infections. More importantly, the use of these technologies can aid diagnostics and helps translate current genomic research into effective treatment and interventions for filarial infections. Studying immune responses via microarray following infection can yield insight into genetic pathways and networks that can have a profound influence on the development of anti-parasitic vaccines.

The evolution of drug discovery: from phenotypes to targets, and back

Cumulative scientific and technological advances over the past two centuries have transformed drug discovery from a largely serendipitous process into the high tech pipelines of today.

Target Identification of Compounds from a Cell Viability Phenotypic Screen Using a Bead/Lysate-Based Affinity Capture Platform

The pharmaceutical industry has been continually challenged by dwindling target diversity. To obviate this trend, phenotypic screens have been adopted, complementing target-centric screening approaches. Phenotypic screens identify drug leads using clinically relevant and translatable mechanisms, remaining agnostic to targets. While target anonymity is advantageous early in the drug discovery process, it poses challenges to hit progression, including the development of backup series, retaining desired pharmacology during optimization, discovery of markers, and understanding mechanism-driven toxicity. Consequently, significant effort has been expended to elaborate the targets and mechanisms at work for promising screening hits. Affinity capture is commonly leveraged, where the compounds are linked to beads and targets are abstracted from cell homogenates. This technique has proven effective for identifying targets of kinase, PARP, and HDAC inhibitors, and examples of new targets have been reported. Herein, a three-pronged approach to target deconvolution by affinity capture is described, including the implementation of a uniqueness index that helps discriminate between bona fide targets and background. The effectiveness of this approach is demonstrated using characterized compounds that act on known and noncanonical target classes. The platform is subsequently applied to phenotypic screening hits, identifying candidate targets. The success rate of bead-based affinity capture is discussed.

Studying Cellular Signal Transduction with OMIC Technologies

In the gulf between genotype and phenotype exists proteins and, in particular, protein signal transduction systems. These systems use a relatively limited parts list to respond to a much longer list of extracellular, environmental, and/or mechanical cues with rapidity and specificity. Most signaling networks function in a highly non-linear and often contextual manner. Furthermore, these processes occur dynamically across space and time. Because of these complexities, systems and "OMIC" approaches are essential for the study of signal transduction. One challenge in using OMIC-scale approaches to study signaling is that the "signal" can take different forms in different situations. Signals are encoded in diverse ways such as protein-protein interactions, enzyme activities, localizations, or post-translational modifications to proteins. Furthermore, in some cases, signals may be encoded only in the dynamics, duration, or rates of change of these features. Accordingly, systems-level analyses of signaling may need to integrate multiple experimental and/or computational approaches. As the field has progressed, the non-triviality of integrating experimental and computational analyses has become apparent. Successful use of OMIC methods to study signaling will require the "right" experiments and the "right" modeling approaches, and it is critical to consider both in the design phase of the project. In this review, we discuss common OMIC and modeling approaches for studying signaling, emphasizing the philosophical and practical considerations for effectively merging these two types of approaches to maximize the probability of obtaining reliable and novel insights into signaling biology.

"Omics" in pharmaceutical research: overview, applications, challenges, and future perspectives

In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.

Identifying compound efficacy targets in phenotypic drug discovery

The identification of the efficacy target(s) for hits from phenotypic compound screens remains a key step to progress compounds into drug development. In addition to efficacy targets, the characterization of epistatic proteins influencing compound activity often facilitates the elucidation of the underlying mechanism of action; and, further, early determination of off-targets that cause potentially unwanted secondary phenotypes helps in assessing potential liabilities. This short review discusses the most important technologies currently available for characterizing the direct and indirect target space of bioactive compounds following phenotypic screening. We present a comprehensive strategy employing complementary approaches to balance individual technology strengths and weaknesses.

Application of chemical biology in target identification and drug discovery

Drug discovery and development is vital to the well-being of mankind and sustainability of the pharmaceutical industry. Using chemical biology approaches to discover drug leads has become a widely accepted path partially because of the completion of the Human Genome Project. Chemical biology mainly solves biological problems through searching previously unknown targets for pharmacologically active small molecules or finding ligands for well-defined drug targets. It is a powerful tool to study how these small molecules interact with their respective targets, as well as their roles in signal transduction, molecular recognition and cell functions. There have been an increasing number of new therapeutic targets being identified and subsequently validated as a result of advances in functional genomics, which in turn led to the discovery of numerous active small molecules via a variety of high-throughput screening initiatives. In this review, we highlight some applications of chemical biology in the context of drug discovery.

Utilizing Yeast Surface Human Proteome Display Libraries to Identify Small Molecule-Protein Interactions

The identification of proteins that interact with small bioactive molecules is a critical but often difficult and time-consuming step in understanding cellular signaling pathways or molecular mechanisms of drug action. Numerous methods for identifying small molecule-interacting proteins have been developed and utilized, including affinity-based purification followed by mass spectrometry analysis, protein microarrays, phage display, and three-hybrid approaches. Although all these methods have been used successfully, there remains a need for additional techniques for analyzing small molecule-protein interactions. A promising method for identifying small molecule-protein interactions is affinity-based selection of yeast surface-displayed human proteome libraries. Large and diverse libraries displaying human protein fragments on the surface of yeast cells have been constructed and subjected to FACS-based enrichment followed by comprehensive exon microarray-based output analysis to identify protein fragments with affinity for small molecule ligands. In a recent example, a proteome-wide search has been successfully carried out to identify cellular proteins binding to the signaling lipids PtdIns(4,5)P2 and PtdIns(3,4,5)P3. Known phosphatidylinositide-binding proteins such as pleckstrin homology domains were identified, as well as many novel interactions. Intriguingly, many novel nuclear phosphatidylinositide-binding proteins were discovered. Although the existence of an independent pool of nuclear phosphatidylinositides has been known about for some time, their functions and mechanism of action remain obscure. Thus, the identification and subsequent study of nuclear phosphatidylinositide-binding proteins is expected to bring new insights to this important biological question. Based on the success with phosphatidylinositides, it is expected that the screening of yeast surface-displayed human proteome libraries will be of general use for the discovery of novel small molecule-protein interactions, thus facilitating the study of cellular signaling pathways and mechanisms of drug action or toxicity.

Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity

Poor understanding of the basic biology of Mycobacterium tuberculosis (MTB), the etiological agent of tuberculosis, hampers development of much-needed drugs, vaccines, and diagnostic tests. Better experimental tools are needed to expedite investigations of this pathogen at the systems level. Here, we present a functional MTB proteome microarray covering most of the proteome and an ORFome library. We demonstrate the broad applicability of the microarray by investigating global protein-protein interactions, small-molecule-protein binding, and serum biomarker discovery, identifying 59 PknG-interacting proteins, 30 bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP) binding proteins, and 14 MTB proteins that together differentiate between tuberculosis (TB) patients with active disease and recovered individuals. Results suggest that the MTB rhamnose pathway is likely regulated by both the serine/threonine kinase PknG and c-di-GMP. This resource has the potential to generate a greater understanding of key biological processes in the pathogenesis of tuberculosis, possibly leading to more effective therapies for the treatment of this ancient disease.

Array-based proteomic approaches to study signal transduction pathways: prospects, merits and challenges

Very often dysfunctional aspects of various signalling networks are found to be associated with human diseases and disorders. The major characteristics of signal transduction pathways are specificity, amplification of the signal, desensitisation and integration, which is accomplished not solely, but majorly by proteins. Array-based profiling of protein-protein and other biomolecular interactions is a versatile approach, which holds immense potential for multiplex interactome mapping and provides an inclusive representation of the signal transduction pathways and networks. Protein microarrays such as analytical protein microarrays (antigen-antibody interactions, autoantibody screening), RP microarrays (interaction of a particular ligand with all the possible targets in cell), functional protein microarrays (protein-protein or protein-ligand interactions) are implemented for various applications, including analysis of protein interactions and their significance in signalling cascades. Additionally, successful amalgamation of the array-based approaches with different label-free detection techniques allows real-time analysis of interaction kinetics of multiple interaction events simultaneously. This review discusses the prospects, merits and limitations of different variants of array-based techniques and their promising applications for studying the modifications and interactions of biomolecules, and highlights the studies associated with signal transduction pathways and their impact on disease pathobiology.

The use of affinity sorbents in targeted proteomics

The complexity of most proteomes is too high to obtain a truly comprehensive view of all expressed proteins by any of the current technologies. Prefractionation techniques are thus necessary to dig deeper into the low-abundance region of the proteome. Progress in the application of affinity sorbents to focus on particular protein classes of low abundance, while at the same time adding understanding about their function through the way they interact with the affinity ligands, will be described.:

Phenotypic screens for compounds that target the cellular pathologies underlying Parkinson's disease

Parkinson's disease (PD) is a devastating neurodegenerative disease that affects over one million patients in the US. Yet, no disease modifying drugs exist, only those that temporarily alleviate symptoms. Because of its poorly defined and highly complex disease etiology, it is essential to embrace unbiased and innovative approaches for identifying new chemical entities that target the underlying toxicities associated with PD. Traditional target-based drug discovery paradigm can suffer from a bias toward a small number of potential targets. Phenotypic screening of both genetic and pharmacological PD models offers an alternative approach to discover compounds that target the initiating causes and effectors of cellular toxicity. The relative paucity of reported phenotypic screens illustrates the intrinsic difficulty in establishing model systems that are both biologically meaningful and adaptable to high-throughput screening. Parallel advances in PD models and in vivo screening technologies will help create opportunities for identifying new therapeutic leads with unanticipated, breakthrough mechanisms of action.

Ribosome display and photo-cross-linking techniques for in vitro identification of target proteins of bioactive small molecules

The identification of target proteins of bioactive small molecules as bioprobe candidates or drug seeds is indispensable for elucidating their actions and predicting their side effects. To meet the current need, we developed a scheme for detection and identification of target proteins by using ribosome display and photo-cross-linking techniques, and demonstrated the feasibility. The mRNAs encoding full-length human proteins (FHPs) were constructed and translated in vitro to prepare pools of FHP-ribosome-mRNA complexes used for ribosome display selection. Expression levels of the FHPs were confirmed by Western blot analysis, and photo-cross-linked small-molecule beads were assessed through cell-free synthesized FHP binding assay. After ribosome display selection against photo-cross-linked small-molecule beads, RT-PCR using mRNAs recovered from the selected ternary complexes and electrophoresis of the PCR products allowed specific detection of the target proteins binding to the beads. In addition, a repeat of ribosome display selection enabled us to identify the target proteins even if the molar quantity was one ten-thousandth of that of the other proteins in a cell-free synthesized FHP pool. Therefore, these results showed that ribosome display using photo-cross-linked small-molecule beads and further extended FHP pool could be one of the powerful techniques for identification of unknown target proteins of bioactive small molecules.

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.

A Whi7-anchored loop controls the G1 Cdk-cyclin complex at start

Cells commit to a new cell cycle at Start by activation of the G1 Cdk-cyclin complex which, in turn, triggers a genome-wide transcriptional wave that executes the G1/S transition. In budding yeast, the Cdc28-Cln3 complex is regulated by an ER-retention mechanism that is important for proper cell size control. We have isolated small-cell-size CDC28 mutants showing impaired retention at the ER and premature accumulation of the Cln3 cyclin in the nucleus. The differential interactome of a quintuple Cdc28(wee) mutant pinpointed Whi7, a Whi5 paralog targeted by Cdc28 that associates to the ER in a phosphorylation-dependent manner. Our results demonstrate that the Cln3 cyclin and Whi7 act in a positive feedback loop to release the G1 Cdk-cyclin complex and trigger Start once a critical size has been reached, thus uncovering a key nonlinear mechanism at the earliest known events of cell-cycle entry.

The Arabidopsis oligopeptidases TOP1 and TOP2 are salicylic acid targets that modulate SA-mediated signaling and the immune response

Salicylic acid (SA) is a small phenolic molecule with hormonal properties, and is an essential component of the immune response. SA exerts its functions by interacting with protein targets; however, the specific cellular components modulated by SA and critical for immune signal transduction are largely unknown. To uncover cellular activities targeted by SA, we probed Arabidopsis protein microarrays with a functional analog of SA. We demonstrate that thimet oligopeptidases (TOPs) constitute a class of SA-binding enzymes. Biochemical evidence demonstrated that SA interacts with TOPs and inhibits their peptidase activities to various degrees both in vitro and in plant extracts. Functional characterization of mutants with altered TOP expression indicated that TOP1 and TOP2 mediate SA-dependent signaling and are necessary for the immune response to avirulent pathogens. Our results support a model whereby TOP1 and TOP2 act in separate pathways to modulate SA-mediated cellular processes.