Chemical genetics: ligand-based discovery of gene function

Modular and divergent synthesis of 2,N3-disubstituted 4-quinazolinones facilitated by regioselective N-alkylation

The synthesis of a biologically relevant 2-amino-N3-alkylamido 4-quinazolinone has been accomplished in four steps from commercially available materials using design principles from both modular and divergent synthesis. N3-Alkylation of 2-chloro-4(3H)-quinazolinone using methyl bromoacetate, followed by C2-amination produced a suitable scaffold for introducing molecular diversity. Optimization of alkylation conditions afforded full regioselectivity, enabling exclusive access to the N-alkylated isomer. Subsequent C2-amination using piperidine, pyrrolidine, or diethylamine, followed by amide bond formation using variously substituted phenethylamines, generated fifteen unique 4-quinazolinones bearing C2-amino and N3-alkylamido substituents. These efforts highlight the reciprocal influence of C2 and N3 substitution on functionalization at either position, establish an effective synthetic pathway toward 2,N3-disubstituted 4-quinazolinones, and enable preliminary bioactivity studies while providing an experiential learning opportunity for undergraduate student researchers.

Target prediction and potential application of dihydroartemisinin on hepatocarcinoma treatment

With high incidence of hepatocarcinoma and limited effective treatments, most patients suffer in pain. Antitumor drugs are single-targeted, toxicity, causing adverse side effects and resistance. Dihydroartemisinin (DHA) inhibits tumor through multiple mechanisms effectively. This study explores and evaluates safety and potential mechanism of DHA towards human hepatocarcinoma based on network pharmacology in a comprehensive way. Adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of DHA were evaluated with pkCSM, SwissADME, and ADMETlab. Potential targets of DHA were obtained from SwissTargetPrediction, Drugbank, TargetNET, and PharmMapper. Target gene of hepatocarcinoma was obtained from OMIM, GeneCards, and DisGeNET. Overlapping targets and hub genes were identified and analyzed for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathway. Molecular docking was utilized to investigate the interactions sites and hydrogen bonds. Cell counting kit-8 (CCK8), wound healing, invasion, and migration assays on HepG2 and SNU387 cell proved DHA inhibits malignant biological features of hepatocarcinoma cell. DHA is safe and desirable for clinical application. A total of 131 overlapping targets were identified. Biofunction analysis showed targets were involved in kinase activity, protein phosphorylation, intracellular reception, signal transduction, transcriptome dysregulation, PPAR pathway, and JAK-STAT signaling axis. Top 9 hub genes were obtained using MCC (Maximal Clique Centrality) algorithm, namely CDK1, CCNA2, CCNB1, CCNB2, KIF11, CHEK1, TYMS, AURKA, and TOP2A. Molecular docking suggests that all hub genes form a stable interaction with DHA for optimal binding energy were all less than - 5 kcal/mol. Dihydroartemisinin might be a potent and safe anticarcinogen based on its biological safety and effective therapeutic effect.

Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy

Chemical genetic screens are a powerful tool for exploring how cancer cells' response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or nuclear factor κB (NF-κB) inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.

Chemical genetic approaches for the discovery of bacterial cell wall inhibitors

Antimicrobial resistance (AMR) in bacterial pathogens is a worldwide health issue. The innovation gap in discovering new antibiotics has remained a significant hurdle in combating the AMR problem. Currently, antibiotics target various vital components of the bacterial cell envelope, nucleic acid and protein biosynthesis machinery and metabolic pathways essential for bacterial survival. The critical role of the bacterial cell envelope in cell morphogenesis and integrity makes it an attractive drug target. While a significant number of in-clinic antibiotics target peptidoglycan biosynthesis, several components of the bacterial cell envelope have been overlooked. This review focuses on various antibacterial targets in the bacterial cell wall and the strategies employed to find their novel inhibitors. This review will further elaborate on combining forward and reverse chemical genetic approaches to discover antibacterials that target the bacterial cell envelope.

Integrated chemical and genetic screens unveil FSP1 mechanisms of ferroptosis regulation

Ferroptosis, marked by iron-dependent lipid peroxidation, may present an Achilles heel for the treatment of cancers. Ferroptosis suppressor protein-1 (FSP1), as the second ferroptosis mainstay, efficiently prevents lipid peroxidation via NAD(P)H-dependent reduction of quinones. Because its molecular mechanisms have remained obscure, we studied numerous FSP1 mutations present in cancer or identified by untargeted random mutagenesis. This mutational analysis elucidates the FAD/NAD(P)H-binding site and proton-transfer function of FSP1, which emerged to be evolutionarily conserved among different NADH quinone reductases. Using random mutagenesis screens, we uncover the mechanism of action of next-generation FSP1 inhibitors. Our studies identify the binding pocket of the first FSP1 inhibitor, iFSP1, and introduce the first species-independent FSP1 inhibitor, targeting the NAD(P)H-binding pocket. Conclusively, our study provides new insights into the molecular functions of FSP1 and enables the rational design of FSP1 inhibitors targeting cancer cells.

Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy

Chemical genetic screens are a powerful tool for exploring how cancer cells' response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or NF-kB inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.

Development and photo-properties and intracellular behavior of visible-light-responsive molecule localizing to organelles of living cell

Visible-light-responsive azobenzene derivative in which a functional group having cell membrane permeability and a fluorophore were bonded was synthesized. This compound localized to the hydrophobic part in the lipid membrane of the liposome, and when the light corresponding to the transition absorption of azobenzene was irradiated, morphological change of the liposome was observed. When this compound was loaded into living cells, this molecule localized to the lysosome and when irradiated with light of the same wavelength caused cell death. These observed changes are thought to be due to photoisomerization of azobenzene derivatives.

Graphical abstract

Zebrafish as a Mainstream Model for In Vivo Systems Pharmacology and Toxicology

Pharmacology and toxicology are part of a much broader effort to understand the relationship between chemistry and biology. While biomedicine has necessarily focused on specific cases, typically of direct human relevance, there are real advantages in pursuing more systematic approaches to characterizing how health and disease are influenced by small molecules and other interventions. In this context, the zebrafish is now established as the representative screenable vertebrate and, through ongoing advances in the available scale of genome editing and automated phenotyping, is beginning to address systems-level solutions to some biomedical problems. The addition of broader efforts to integrate information content across preclinical model organisms and the incorporation of rigorous analytics, including closed-loop deep learning, will facilitate efforts to create systems pharmacology and toxicology with the ability to continuously optimize chemical biological interactions around societal needs. In this review, we outline progress toward this goal.

IFITM proteins assist cellular uptake of diverse linked chemotypes

The search for cell-permeable drugs has conventionally focused on low-molecular weight (MW), nonpolar, rigid chemical structures. However, emerging therapeutic strategies break traditional drug design rules by employing flexibly linked chemical entities composed of more than one ligand. Using complementary genome-scale chemical-genetic approaches we identified an endogenous chemical uptake pathway involving interferon-induced transmembrane proteins (IFITMs) that modulates the cell permeability of a prototypical biopic inhibitor of MTOR (RapaLink-1, MW: 1784 g/mol). We devised additional linked inhibitors targeting BCR-ABL1 (DasatiLink-1, MW: 1518 g/mol) and EIF4A1 (BisRoc-1, MW: 1466 g/mol), uptake of which was facilitated by IFITMs. We also found that IFITMs moderately assisted some proteolysis-targeting chimeras and examined the physicochemical requirements for involvement of this uptake pathway.

Navigating Transcriptomic Connectivity Mapping Workflows to Link Chemicals with Bioactivities

Screening new compounds for potential bioactivities against cellular targets is vital for drug discovery and chemical safety. Transcriptomics offers an efficient approach for assessing global gene expression changes, but interpreting chemical mechanisms from these data is often challenging. Connectivity mapping is a potential data-driven avenue for linking chemicals to mechanisms based on the observation that many biological processes are associated with unique gene expression signatures (gene signatures). However, mining the effects of a chemical on gene signatures for biological mechanisms is challenging because transcriptomic data contain thousands of noisy genes. New connectivity mapping approaches seeking to distinguish signal from noise continue to be developed, spurred by the promise of discovering chemical mechanisms, new drugs, and disease targets from burgeoning transcriptomic data. Here, we analyze these approaches in terms of diverse transcriptomic technologies, public databases, gene signatures, pattern-matching algorithms, and statistical evaluation criteria. To navigate the complexity of connectivity mapping, we propose a harmonized scheme to coherently organize and compare published workflows. We first standardize concepts underlying transcriptomic profiles and gene signatures based on various transcriptomic technologies such as microarrays, RNA-Seq, and L1000 and discuss the widely used data sources such as Gene Expression Omnibus, ArrayExpress, and MSigDB. Next, we generalize connectivity mapping as a pattern-matching task for finding similarity between a query (e.g., transcriptomic profile for new chemical) and a reference (e.g., gene signature of known target). Published pattern-matching approaches fall into two main categories: vector-based use metrics like correlation, Jaccard index, etc., and aggregation-based use parametric and nonparametric statistics (e.g., gene set enrichment analysis). The statistical methods for evaluating the performance of different approaches are described, along with comparisons reported in the literature on benchmark transcriptomic data sets. Lastly, we review connectivity mapping applications in toxicology and offer guidance on evaluating chemical-induced toxicity with concentration-response transcriptomic data. In addition to serving as a high-level guide and tutorial for understanding and implementing connectivity mapping workflows, we hope this review will stimulate new algorithms for evaluating chemical safety and drug discovery using transcriptomic data.

Reactivity-based chemical-genetic study of protein kinases

The human protein kinase superfamily comprises over 500 members that operate in nearly every signal transduction pathway and regulate essential cellular processes. Deciphering the functional roles of protein kinases with small-molecule inhibitors is essential to enhance our understanding of cell signaling and to facilitate the development of new therapies. However, it is rather challenging to identify selective kinase inhibitors because of the conserved nature of the ATP binding site. A number of chemical-genetic approaches have been developed during the past two decades to enable selective chemical perturbation of the activity of individual kinases. Herein, we review the development and application of chemical-genetic strategies that feature the use of covalent inhibitors targeting cysteine residues to dissect the cellular functions of protein kinases.

Computational drug design of novel COVID-19 inhibitor

BACKGROUND

In 2003, the first case of severe acute respiratory syndrome coronavirus (SARS-CoV) was recorded. Coronaviruses (CoVs) have caused a major outbreak of human fatal pneumonia. Currently, there is no specific drug or treatment for diseases caused by SARS CoV 2. Computational approach that adopts dynamic models is widely accepted as indispensable tool in drug design but yet to be exploited in covid-19 in Zaria, Nigeria. In this study, steps were taken to advance on the successful achievements in the field of covid-19 drug, with the aid of in silico drug design technique, to create novel inhibitor drug candidates with better activity. In this study, one thousand human immunodeficiency virus (HIV1) antiviral chemical compounds from www.bindingBD.org were docked on the SARS CoV 2 main protease protein data bank identification number 6XBH (PDB ID: 6XBH) and the molecular docking score were ranked in order to identify the compounds with the highest inhibitory effects, and easy selection for future studies.

RESULTS

The docking studies showed some interesting results. Inhibitors with Index numbers 331, 741, and 819 had the highest binding affinity. Similarly, inhibitors with Index number 441, 847, and 46 had the lowest hydrogen bond energy. Inhibitor with index number 331 was reported with the lowest value (- 48.38kCal/mol). Five new compounds were designed from the selected six (6) compounds with the best binding score giving a total of thirty (30) novel compounds. The low binding energy of inhibitor with index no. 847b is unique, as most of the interaction energies are of H-bond type with amino acids (Thr26, Gly143, Ser144, Cys145, Glu166, Gln189, Hie164, Met49, Thr26, Thr25, Thr190, Asn142, Met165) resulting in an overall negative value (-16.31 kCal/mol) making it the best of all the newly designed inhibitors.

CONCLUSIONS

The novel inhibitor is 2-(2-(5-amino-2-((((3-aminobenzyl)oxy)carbonyl)amino)-5-oxopentanamido)-4-(2-(tert-butyl)-4-oxo-4-(pentan-3-ylamino) butanamido)-3-hydroxybutyl) benzoic acid. The improvement it has over the parent inhibitor is from the primary amine group attached to meta position of first benzene ring and the carboxyl group attached to the ortho position of the second benzene ring. The molecular dynamics studies also show that the novel inhibitor remains stable after the study. This result makes it a better drug candidate against SARS CoV 2 main protease when compared with the co-crystallized inhibitor or any of the 1000 docked inhibitors.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s42269-022-00892-z.

The Selenoprotein Glutathione Peroxidase 4: From Molecular Mechanisms to Novel Therapeutic Opportunities

The selenoprotein glutathione peroxidase 4 (GPX4) is one of the main antioxidant mediators in the human body. Its central function involves the reduction of complex hydroperoxides into their respective alcohols often using reduced Glutathione (GSH) as a reducing agent. GPX4 has become a hotspot therapeutic target in biomedical research following its characterization as a chief regulator of ferroptosis, and its subsequent recognition as a specific pharmacological target for the treatment of an extensive variety of human diseases including cancers and neurodegenerative disorders. Several recent studies have provided insights into how GPX4 is distinguished from the rest of the glutathione peroxidase family, the unique biochemical properties of GPX4, how GPX4 is related to lipid peroxidation and ferroptosis, and how the enzyme may be modulated as a potential therapeutic target. This current report aims to review the literature underlying all these insights and present an up-to-date perspective on the current understanding of GPX4 as a potential therapeutic target.

Plant growth promotion by the interaction of a novel synthetic small molecule with GA-DELLA function

Synthesized small molecules are useful as tools to investigate hormonal signaling involved in plant growth and development. They are also important as agrochemicals to promote beneficial properties of crops in the field. We describe here the synthesis and mode of action of a novel growth-promoting chemical, A1. A1 stimulates enhanced growth in both shoot and root tissues of plants, acting by increasing both dry and fresh weight. This suggests that A1 not only promotes uptake of water but also increases production of cellular material. A1 treatment of Arabidopsisleads to the degradation of DELLA growth-inhibitory proteins suggesting that A1-mediated growth promotion is dependent upon this mechanism. We performed genetic analysis to confirm this and further dissect the mechanism of A1 action upon growth in Arabidopsis. A quintuple dellamutant was insensitive to A1, confirming that the mode of action was indeed via a DELLA-dependent mechanism. The ga1-5gibberellin synthesis mutant was similarly insensitive, suggesting that to promote growth in ArabidopsisA1 requires the presence of endogenous gibberellins. This was further suggested by the observation that double mutants of GID1 gibberellin receptor genes were insensitive to A1. Taken together, our data suggest that A1 acts to enhance sensitivity to endogenous gibberellins thus leading to observed enhanced growth via DELLA degradation. A1 and related compounds will be useful to identify novel signaling components involved in plant growth and development, and as agrochemicals suitable for a wide range of crop species.

Identification of stomatal-regulating molecules from de novo arylamine collection through aromatic C-H amination

Stomata—small pores generally found on the leaves of plants—control gas exchange between plant and the atmosphere. Elucidating the mechanism that underlies such control through the regulation of stomatal opening/closing is important to understand how plants regulate photosynthesis and tolerate against drought. However, up-to-date, molecular components and their function involved in stomatal regulation are not fully understood. We challenged such problem through a chemical genetic approach by isolating and characterizing synthetic molecules that influence stomatal movement. Here, we describe that a small chemical collection, prepared during the development of C–H amination reactions, lead to the discovery of a Stomata Influencing Molecule (SIM); namely, a sulfonimidated oxazole that inhibits stomatal opening. The starting molecule SIM1 was initially isolated from screening of compounds that inhibit light induced opening of dayflower stomata. A range of SIM molecules were rapidly accessed using our state-of-the-art C–H amination technologies. This enabled an efficient structure–activity relationship (SAR) study, culminating in the discovery of a sulfonamidated oxazole derivative (SIM*) having higher activity and enhanced specificity against stomatal regulation. Biological assay results have shed some light on the mode of action of SIM molecules within the cell, which may ultimately lead to drought tolerance-conferring agrochemicals through the control of stomatal movement.

Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions

New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. Here, we review the computational approaches to predicting protein-ligand interactions in the context of drug discovery, focusing on methods using artificial intelligence (AI). We begin with a brief introduction to proteins (targets), ligands (e.g. drugs) and their interactions for nonexperts. Next, we review databases that are commonly used in the domain of protein-ligand interactions. Finally, we survey and analyze the machine learning (ML) approaches implemented to predict protein-ligand binding sites, ligand-binding affinity and binding pose (conformation) including both classical ML algorithms and recent deep learning methods. After exploring the correlation between these three aspects of protein-ligand interaction, it has been proposed that they should be studied in unison. We anticipate that our review will aid exploration and development of more accurate ML-based prediction strategies for studying protein-ligand interactions.

Late-Stage Diversification: A Motivating Force in Organic Synthesis

Interest in therapeutic discovery typically drives the preparation of natural product analogs, but these undertakings contribute significant advances for synthetic chemistry as well. The need for a highly efficient and scalable synthetic route to a complex molecular scaffold for diversification frequently inspires new methodological development or unique application of existing methods on structurally intricate systems. Additionally, synthetic planning with an aim toward late-stage diversification can provide access to otherwise unavailable compounds or facilitate preparation of complex molecules with diverse patterns of substitution around a shared carbon framework. For these reasons among others, programs dedicated to the diversification of natural product frameworks and other complex molecular scaffolds have been increasing in popularity, a trend likely to continue given their fruitfulness and breadth of impact. In this Perspective, we discuss our experience using late-stage diversification as a guiding principle for the synthesis of natural product analogs and reflect on the impact such efforts have on the future of complex molecule synthesis.

The Chemistry and Biology of Ferroptosis

Ferroptosis is a recently described form of cell death driven by iron-dependent lipid peroxidation. This type of cell death was first observed in response to treatment of tumor cells with a small-molecule chemical probe named erastin. Most subsequent advances in understanding the mechanisms governing ferroptosis involved the use of genetic screens and small-molecule probes. We describe herein the utility and limitations of chemical probes that have been used to analyze and perturb ferroptosis, as well as mechanistic studies of ferroptosis that benefitted from the use of these probes and genetic screens. We also suggest probes for ferroptosis and highlight mechanistic questions surrounding this form of cell death that will be a high priority for exploration in the future.

A novel peptide antagonist of the human growth hormone receptor

Excess circulating human growth hormone (hGH) in vivo is linked to metabolic and growth disorders such as cancer, diabetes, and acromegaly. Consequently, there is considerable interest in developing antagonists of hGH action. Here, we present the design, synthesis, and characterization of a 16-residue peptide (site 1-binding helix [S1H]) that inhibits hGH-mediated STAT5 phosphorylation in cultured cells. S1H was designed as a direct sequence mimetic of the site 1 mini-helix (residues 36-51) of wild-type hGH and acts by inhibiting the interaction of hGH with the human growth hormone receptor (hGHR). In vitro studies indicated that S1H is stable in human serum and can adopt an α-helix in solution. Our results also show that S1H mitigates phosphorylation of STAT5 in cells co-treated with hGH, reducing intracellular STAT5 phosphorylation levels to those observed in untreated controls. Furthermore, S1H was found to attenuate the activity of the hGHR and the human prolactin receptor, suggesting that this peptide acts as an antagonist of both lactogenic and somatotrophic hGH actions. Finally, we used alanine scanning to determine how discrete amino acids within the S1H sequence contribute to its structural organization and biological activity. We observed a strong correlation between helical propensity and inhibitory effect, indicating that S1H-mediated antagonism of the hGHR is largely dependent on the ability for S1H to adopt an α-helix. Taken together, these results show that S1H not only acts as a novel peptide-based antagonist of the hGHR but can also be applied as a chemical tool to study the molecular nature of hGH-hGHR interactions.

Whole-Seedling-Based Chemical Genetic Screens in Arabidopsis

Forward genetics has been extremely powerful for dissecting biological pathways in various model organisms. However, it is limited by the fact that redundant gene families and essential genes cannot be readily uncovered through such methods. Chemical genetics, on the other hand, provides a valuable complementary approach to probe biological processes and is suitable for not only genetic model organisms but also genetically less tractable species. We describe here a high-throughput chemical genetic screening method simply based on plant growth and developmental phenotypes in Arabidopsis. It was successfully utilized to study plant immunity and can be easily adapted for dissecting other plant signal transduction pathways.

PROMIS: Global Analysis of PROtein-Metabolite Interactions

Small molecules are not only intermediates of metabolism, but also play important roles in signaling and in controlling cellular metabolism, growth, and development. Although a few systematic studies have been conducted, the true extent of protein-small molecule interactions in biological systems remains unknown. PROtein-metabolite interactions using size separation (PROMIS) is a method for studying protein-small molecule interactions in a non-targeted, proteome- and metabolome-wide manner. This approach uses size-exclusion chromatography followed by proteomics and metabolomics liquid chromatography-mass spectrometry analysis of the collected fractions. Assuming that small molecules bound to proteins would co-fractionate together, we found numerous small molecules co-eluting with proteins, strongly suggesting the formation of stable complexes. Using PROMIS, we identified known small molecule-protein complexes, such as between enzymes and cofactors, and also found novel interactions. © 2019 The Authors. Basic Protocol 1: Preparation of native cell lysate from plant material Support Protocol: Bradford assay to determine protein concentration Basic Protocol 2: Separation of molecular complexes using size-exclusion chromatography Basic Protocol 3: Simultaneous extraction of proteins and metabolites using single-step extraction protocol Basic Protocol 4: Metabolomics analysis Basic Protocol 5: Proteomics analysis.

The impact of chemoinformatics on drug discovery in the pharmaceutical industry

Introduction: Even though there have been substantial advances in our understanding of biological systems, research in drug discovery is only just now beginning to utilize this type of information. The single-target paradigm, which exemplifies the reductionist approach, remains a mainstay of drug research today. A deeper view of the complexity involved in drug discovery is necessary to advance on this field.Areas covered: This perspective provides a summary of research areas where cheminformatics has played a key role in drug discovery, including of the available resources as well as a personal perspective of the challenges still faced in the field.Expert opinion: Although great strides have been made in the handling and analysis of biological and pharmacological data, more must be done to link the data to biological pathways. This is crucial if one is to understand how drugs modify disease phenotypes, although this will involve a shift from the single drug/single target paradigm that remains a mainstay of drug research. Moreover, such a shift would require an increased awareness of the role of physiology in the mechanism of drug action, which will require the introduction of new mathematical, computer, and biological methods for chemoinformaticians to be trained in.

Optogenetic tools for dissecting complex intracellular signaling pathways

Intracellular signaling forms complicated networks that involve dynamic alterations of the protein-protein interactions occurring inside a cell. To dissect these complex networks, light-inducible optogenetic technologies have offered a novel approach for modulating the function of intracellular machineries in space and time. Optogenetic approaches combine genetic and optical methods to initiate and control protein functions within live cells. In this review, we provide an overview of the optical strategies that can be used to manipulate intracellular signaling proteins and secondary messengers at the molecular level. We briefly address how an optogenetic actuator can be engineered to enhance homo- or hetero-interactions, survey various optical tools and targeting strategies for controlling cell-signaling pathways, examine their extension to in vivo systems and discuss the future prospects for the field.

Multifunctional transcriptional coactivator PC4 is a global co-regulator of p53-dependent stress response and gene regulation

Human positive coactivator 4 (PC4), a multifunctional chromatin-associated protein, is known to directly interact with p53 and modulate expressions of a few p53-dependent genes. However, the role of PC4 in p53's myriad of other regulatory functions is not known. The p53-PC4 interaction was selectively perturbed by a small peptide which led to abrogation of genotoxic stress-induced up-regulation of many p53-dependent genes and reduction of apoptosis in A549 cells. Over-expression of a PC4 point mutant, incapable of binding p53, recapitulated many of the effects of the peptide. Global gene expression profiling in A549 cells, upon peptide treatment, revealed PC4's involvement in the regulation of many p53-dependent pathways, including the Hippo pathway. Introduction of the peptide in neuronal cells significantly reduced its amyloid-β-induced death. Thus, PC4 emerges as a global co-regulator of p53 and a therapeutic target against pathogeneses where the p53-dependent cell death process plays a crucial role.

Emerging strategies for the identification of protein-metabolite interactions

Interactions between biological molecules enable life. The significance of a cell-wide understanding of molecular complexes is thus obvious. In comparison to protein-protein interactions, protein-metabolite interactions remain under-studied. However, this has been gradually changing due to technological progress. Here, we focus on the interactions between ligands and receptors, the triggers of signalling events. While the number of small molecules with proven or proposed signalling roles is rapidly growing, most of their protein receptors remain unknown. Conversely, there are numerous signalling proteins with predicted ligand-binding domains for which the identities of the metabolite counterparts remain elusive. Here, we discuss the current biochemical strategies for identifying protein-metabolite interactions and how they can be used to characterize known metabolite regulators and identify novel ones.

Integrating yeast chemical genomics and mammalian cell pathway analysis

Chemical genomics has been applied extensively to evaluate small molecules that modulate biological processes in Saccharomyces cerevisiae. Here, we use yeast as a surrogate system for studying compounds that are active against metazoan targets. Large-scale chemical-genetic profiling of thousands of synthetic and natural compounds from the Chinese National Compound Library identified those with high-confidence bioprocess target predictions. To discover compounds that have the potential to function like therapeutic agents with known targets, we also analyzed a reference library of approved drugs. Previously uncharacterized compounds with chemical-genetic profiles resembling existing drugs that modulate autophagy and Wnt/β-catenin signal transduction were further examined in mammalian cells, and new modulators with specific modes of action were validated. This analysis exploits yeast as a general platform for predicting compound bioactivity in mammalian cells.

14-3-3εa directs the pulsatile transport of basal factors toward the apical domain for lumen growth in tubulogenesis

Ascidians have become a powerful model system in which to uncover basic mechanisms that govern body plan specification and elaboration. In particular, the ascidian notochord is a highly tractable model for tubulogenesis. Here, we use chemical genetics to identify roles for 14-3-3εa, and its binding partner ezrin/radixin/moesin (ERM), in tubulogenesis. Combining genetic and chemical perturbations with live cell imaging, we present evidence that 14-3-3εa–ERM interactions are required for tubulogenesis and that they act by promoting a directed cytoplasmic flow, previously uncharacterized, which carries lumen-associated components from the basal domain to the apical domain to feed lumen growth. Because many core components of this system are highly conserved, these results have broad implications for tubulogenesis in many other contexts.

The Ciona notochord has emerged as a simple and tractable in vivo model for tubulogenesis. Here, using a chemical genetics approach, we identified UTKO1 as a selective small molecule inhibitor of notochord tubulogenesis. We identified 14-3-3εa protein as a direct binding partner of UTKO1 and showed that 14-3-3εa knockdown leads to failure of notochord tubulogenesis. We found that UTKO1 prevents 14-3-3εa from interacting with ezrin/radixin/moesin (ERM), which is required for notochord tubulogenesis, suggesting that interactions between 14-3-3εa and ERM play a key role in regulating the early steps of tubulogenesis. Using live imaging, we found that, as lumens begin to open between neighboring cells, 14-3-3εa and ERM are highly colocalized at the basal cortex where they undergo cycles of accumulation and disappearance. Interestingly, the disappearance of 14-3-3εa and ERM during each cycle is tightly correlated with a transient flow of 14-3-3εa, ERM, myosin II, and other cytoplasmic elements from the basal surface toward the lumen-facing apical domain, which is often accompanied by visible changes in lumen architecture. Both pulsatile flow and lumen formation are abolished in larvae treated with UTKO1, in larvae depleted of either 14-3-3εa or ERM, or in larvae expressing a truncated form of 14-3-3εa that lacks the ability to interact with ERM. These results suggest that 14-3-3εa and ERM interact at the basal cortex to direct pulsatile basal accumulation and basal–apical transport of factors that are essential for lumen formation. We propose that similar mechanisms may underlie or may contribute to lumen formation in tubulogenesis in other systems.

Targeting RNA in mammalian systems with small molecules

The recognition of RNA functions beyond canonical protein synthesis has challenged the central dogma of molecular biology. Indeed, RNA is now known to directly regulate many important cellular processes, including transcription, splicing, translation, and epigenetic modifications. The misregulation of these processes in disease has led to an appreciation of RNA as a therapeutic target. This potential was first recognized in bacteria and viruses, but discoveries of new RNA classes following the sequencing of the human genome have invigorated exploration of its disease-related functions in mammals. As stable structure formation is evolving as a hallmark of mammalian RNAs, the prospect of utilizing small molecules to specifically probe the function of RNA structural domains and their interactions is gaining increased recognition. To date, researchers have discovered bioactive small molecules that modulate phenotypes by binding to expanded repeats, microRNAs, G-quadruplex structures, and RNA splice sites in neurological disorders, cancers, and other diseases. The lessons learned from achieving these successes both call for additional studies and encourage exploration of the plethora of mammalian RNAs whose precise mechanisms of action remain to be elucidated. Efforts toward understanding fundamental principles of small molecule-RNA recognition combined with advances in methodology development should pave the way toward targeting emerging RNA classes such as long noncoding RNAs. Together, these endeavors can unlock the full potential of small molecule-based probing of RNA-regulated processes and enable us to discover new biology and underexplored avenues for therapeutic intervention in human disease. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions RNA in Disease and Development > RNA in Disease.

What Can We Learn from Wide-Angle Solution Scattering?

Extending collection of x-ray solution scattering data into the wide-angle regime (WAXS) can provide information not readily extracted from small angle (SAXS) data. It is possible to accurately predict WAXS scattering on the basis of atomic coordinate sets and thus use it as a means of testing molecular models constructed on the basis of crystallography, molecular dynamics (MD), cryo-electron microscopy or ab initio modeling. WAXS data may provide insights into the secondary, tertiary and quaternary structural organization of macromolecules. It can provide information on protein folding and unfolding beyond that attainable from SAXS data. It is particularly sensitive to structural fluctuations in macromolecules and can be used to generate information about the conformational make up of ensembles of structures co-existing in solution. Novel approaches to modeling of structural fluctuations can provide information on the spatial extent of large-scale structural fluctuations that are difficult to obtain by other means. Direct comparison with the results of MD simulations are becoming possible. Because it is particularly sensitive to small changes in structure and flexibility it provides unique capabilities for the screening of ligand libraries for detection of functional interactions. WAXS thereby provides an important extension of SAXS that can generate structural and dynamic information complementary to that obtainable by other biophysical techniques.

Linear and Kernel Model Construction Methods for Predicting Drug-Target Interactions in a Chemogenomic Framework

Identification of drug-target interactions is a crucial process in drug discovery. In this chapter, we present protocols for recent advancements in machine learning methods for predicting drug-target interactions from heterogeneous biological data in a chemogenomic framework, in which prediction is based on the chemical structure data of drug candidate compounds and translated genomic sequence data of target candidate proteins. Most existing methods are based on either linear modeling or kernel modeling. To illustrate linear modeling, we introduce sparsity-induced binary classifiers and sparse canonical correlation analysis. To illustrate kernel modeling, we introduce pairwise kernel-based support vector machines and kernel-based distance learning. Workflows for using these techniques are presented. We also discuss the characteristics of each method and suggest some directions for future research.

Sparse Modeling to Analyze Drug-Target Interaction Networks

Most drugs produce their phenotypic effects by interacting with target proteins, and understanding the molecular features that underpin drug-target interactions is crucial when designing a novel drug. In this chapter, we introduce the protocols that have driven recent advances in sparse modeling methods for analyzing drug-target interaction networks within a chemogenomic framework. In this approach, the chemical structures of candidate drug compounds are correlated with the genomic sequences of the candidate target proteins. We demonstrate the use of sparse canonical correspondence analysis and sparsity-induced binary classifiers to extract the underlying molecular features that are most strongly involved in drug-target interactions. We focus on drug chemical substructures and protein domains. Workflows for applying these methods are presented, and an application is described in detail. We consider the characteristics of each method and suggest possible directions for future research.

(−)-Cytisine: Access to a stereochemically defined and functionally flexible piperidine scaffold

Cytisine undergoes ready fragmentation to provide a highly flexible (and “privileged”) piperidine scaffold capable of exploring a diversity of chemical space.

A countermeasure development pipeline

We have developed an integrated pipeline for countermeasure discovery that, under the auspices of the National Institutes of Health Countermeasures Against Chemical Threats network, is one of the few efforts within academia that by design spans the spectrum from discovery to phase I. The successful implementation of this approach for cyanide would enable efficient proof-of-concept studies that would lay the foundation for a generalizable strategy for parallel mechanistic studies and accelerated countermeasure development in the face of new and emerging chemical threats.

Identification and characterization of inhibitors of UDP-glucose and UDP-sugar pyrophosphorylases for in vivo studies

UDP-sugars serve as ultimate precursors in hundreds of glycosylation reactions (e.g. for protein and lipid glycosylation, synthesis of sucrose, cell wall polysaccharides, etc.), underlying an important role of UDP-sugar-producing enzymes in cellular metabolism. However, genetic studies on mechanisms of UDP-sugar formation were frequently hampered by reproductive impairment of the resulting mutants, making it difficult to assess an in vivo role of a given enzyme. Here, a chemical library containing 17 500 compounds was separately screened against purified UDP-glucose pyrophosphorylase (UGPase) and UDP-sugar pyrophosphorylase (USPase), both enzymes representing the primary mechanisms of UDP-sugar formation. Several compounds have been identified which, at 50 μm, exerted at least 50% inhibition of the pyrophosphorylase activity. In all cases, both UGPase and USPase activities were inhibited, probably reflecting common structural features of active sites of these enzymes. One of these compounds (cmp #6), a salicylamide derivative, was found as effective inhibitor of Arabidopsis pollen germination and Arabidopsis cell culture growth. Hit optimization on cmp #6 yielded two analogs (cmp #6D and cmp #6D2), which acted as uncompetitive inhibitors against both UGPase and USPase, and were strong inhibitors in the pollen test, with apparent inhibition constants of less than 1 μm. Their effects on pollen germination were relieved by addition of UDP-glucose and UDP-galactose, suggesting that the inhibitors targeted UDP-sugar formation. The results suggest that cmp #6 and its analogs may represent useful tools to study in vivo roles of the pyrophosphorylases, helping to overcome the limitations of genetic approaches.

Optogenetic toolkit for precise control of calcium signaling

Calcium acts as a second messenger to regulate a myriad of cell functions, ranging from short-term muscle contraction and cell motility to long-term changes in gene expression and metabolism. To study the impact of Ca2+-modulated 'ON' and 'OFF' reactions in mammalian cells, pharmacological tools and 'caged' compounds are commonly used under various experimental conditions. The use of these reagents for precise control of Ca2+ signals, nonetheless, is impeded by lack of reversibility and specificity. The recently developed optogenetic tools, particularly those built upon engineered Ca2+ release-activated Ca2+ (CRAC) channels, provide exciting opportunities to remotely and non-invasively modulate Ca2+ signaling due to their superior spatiotemporal resolution and rapid reversibility. In this review, we briefly summarize the latest advances in the development of optogenetic tools (collectively termed as 'genetically encoded Ca2+ actuators', or GECAs) that are tailored for the interrogation of Ca2+ signaling, as well as their applications in remote neuromodulation and optogenetic immunomodulation. Our goal is to provide a general guide to choosing appropriate GECAs for optical control of Ca2+ signaling in cellulo, and in parallel, to stimulate further thoughts on evolving non-opsin-based optogenetics into a fully fledged technology for the study of Ca2+-dependent activities in vivo.

Found in Translation: Applying Lessons from Model Systems to Strigolactone Signaling in Parasitic Plants

Strigolactones (SLs) are small molecules that act as endogenous hormones to regulate plant development as well as exogenous cues that help parasitic plants to infect their hosts. Given that parasitic plants are experimentally challenging systems, researchers are using two approaches to understand how they respond to host-derived SLs. The first involves extrapolating information on SLs from model genetic systems to dissect their roles in parasitic plants. The second uses chemicals to probe SL signaling directly in the parasite Striga hermonthica. These approaches indicate that parasitic plants have co-opted a family of α/β hydrolases to perceive SLs. The importance of this genetic and chemical information cannot be overstated since parasitic plant infestations are major obstacles to food security in the developing world.

Inhibition of cell polarity establishment in stomatal asymmetric cell division using the chemical compound bubblin

Stem-cell polarization is a crucial step in asymmetric cell division, which is a universal system for generating cellular diversity in multicellular organisms. Several conventional genetics studies have attempted to elucidate the mechanisms underlying cell polarization in plants, but it remains largely unknown. In plants, stomata, which are valves for gas exchange, are generated through several rounds of asymmetric divisions. In this study, we identified and characterized a chemical compound that affects stomatal stem-cell polarity. High-throughput screening for bioactive molecules identified a pyridine-thiazole derivative, named bubblin, which induced stomatal clustering in Arabidopsis epidermis. Bubblin perturbed stomatal asymmetric division, resulting in the generation of two identical daughter cells. Both cells continued to express the stomatal-fate determinant SPEECHLESS, and then differentiated into mispatterned stomata. Bubblin-treated cells had a defect in the polarized localization of BREAKING OF ASYMMETRY IN THE STOMATAL LINEAGE (BASL), which is required for asymmetric cell fate determination. Our results suggest that bubblin induces stomatal lineage cells to divide without BASL-dependent pre-mitotic establishment of polarity. Bubblin is a potentially valuable tool for investigating cell polarity establishment in stomatal asymmetric division.

Identification of Methylosome Components as Negative Regulators of Plant Immunity Using Chemical Genetics

Nucleotide-binding leucine-rich repeat (NLR) proteins serve as immune receptors in both plants and animals. To identify components required for NLR-mediated immunity, we designed and carried out a chemical genetics screen to search for small molecules that can alter immune responses in Arabidopsis thaliana. From 13 600 compounds, we identified Ro 8-4304 that was able to specifically suppress the severe autoimmune phenotypes of chs3-2D (chilling sensitive 3, 2D), including the arrested growth morphology and heightened PR (Pathogenesis Related) gene expression. Further, six Ro 8-4304 insensitive mutants were uncovered from the Ro 8-4304-insensitive mutant (rim) screen using a mutagenized chs3-2D population. Positional cloning revealed that rim1 encodes an allele of AtICln (I, currents; Cl, chloride; n, nucleotide). Genetic and biochemical analysis demonstrated that AtICln is in the same protein complex with the methylosome components small nuclear ribonucleoprotein D3b (SmD3b) and protein arginine methyltransferase 5 (PRMT5), which are required for the biogenesis of small nuclear ribonucleoproteins (snRNPs) involved in mRNA splicing. Double mutant analysis revealed that SmD3b is also involved in the sensitivity to Ro 8-4304, and the prmt5-1 chs3-2D double mutant is lethal. Loss of AtICln, SmD3b, or PRMT5 function results in enhanced disease resistance against the virulent oomycete pathogen Hyaloperonospora arabidopsidis Noco2, suggesting that mRNA splicing plays a previously unknown negative role in plant immunity. The successful implementation of a high-throughput chemical genetic screen and the identification of a small-molecule compound affecting plant immunity indicate that chemical genetics is a powerful tool to study whole-organism plant defense pathways.

Identification of Novel Human Breast Carcinoma (MDA-MB-231) Cell Growth Modulators from a Carbohydrate-Based Diversity Oriented Synthesis Library

The application of a cell-based growth inhibition on a library of skeletally different glycomimetics allowed for the selection of a hexahydro-2H-furo[3,2-b][1,4]oxazine compound as candidate inhibitors of MDA-MB-231 cell growth. Subsequent synthesis of analogue compounds and preliminary biological studies validated the selection of a valuable hit compound with a novel polyhydroxylated structure for the modulation of the breast carcinoma cell cycle mechanism.

Large-scale image-based screening and profiling of cellular phenotypes

Cellular phenotypes are observable characteristics of cells resulting from the interactions of intrinsic and extrinsic chemical or biochemical factors. Image-based phenotypic screens under large numbers of basal or perturbed conditions can be used to study the influences of these factors on cellular phenotypes. Hundreds to thousands of phenotypic descriptors can also be quantified from the images of cells under each of these experimental conditions. Therefore, huge amounts of data can be generated, and the analysis of these data has become a major bottleneck in large-scale phenotypic screens. Here, we review current experimental and computational methods for large-scale image-based phenotypic screens. Our focus is on phenotypic profiling, a computational procedure for constructing quantitative and compact representations of cellular phenotypes based on the images collected in these screens. © 2016 International Society for Advancement of Cytometry.

A TiS2 nanosheet enhanced fluorescence polarization biosensor for ultra-sensitive detection of biomolecules

Development of new strategies for the sensitive and selective detection of ultra-low concentrations of specific cancer markers is of great importance for assessing cancer therapeutics due to its crucial role in early clinical diagnoses and biomedical applications. In this work, we have developed two types of fluorescence polarization (FP) amplification assay strategies for the detection of biomolecules by using TiS2 as a FP enhancer and Zn(2+)-dependent self-hydrolyzing deoxyribozymes as catalysts to realize enzyme-catalyzed target-recycling signal amplification. One approach is based on the terminal protection of small-molecule-linked DNA, in which biomolecular binding to small molecules in DNA-small-molecule chimeras can protect the conjugated DNA from degradation by exonuclease I (Exo I); the other approach is based on the terminal protection of biomolecular bound aptamer DNA, in which biomolecules directly bound to the single strand aptamer DNA can protect the ssDNA from degradation by Exo I. We select folate receptor (FR) and thrombin (Tb) as model analytes to verify the current concept. It is shown that under optimized conditions, our strategies exhibit high sensitivity and selectivity for the quantification of FR and Tb with low detection limits (0.003 ng mL(-1) and 0.01 pM, respectively). Additionally, this strategy is a simple "mix and detect" approach, and does not require any separation steps. This biosensor is also utilized in the analysis of real biological samples, the results agree well with those obtained by the enzyme-linked immunosorbent assay (ELISA).

Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting

Ubiquitin is essential for eukaryotic life and varies in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies indicate that ubiquitin is highly tolerant to single mutations. We hypothesized that this tolerance would be reduced by chemically induced physiologic perturbations. To test this hypothesis, a class of first year UCSF graduate students employed deep mutational scanning to determine the fitness landscape of all possible single residue mutations in the presence of five different small molecule perturbations. These perturbations uncover 'shared sensitized positions' localized to areas around the hydrophobic patch and the C-terminus. In addition, we identified perturbation specific effects such as a sensitization of His68 in HU and a tolerance to mutation at Lys63 in DTT. Our data show how chemical stresses can reduce buffering effects in the ubiquitin proteasome system. Finally, this study demonstrates the potential of lab-based interdisciplinary graduate curriculum.

DOI:http://dx.doi.org/10.7554/eLife.15802.001

The ability of an organism to grow and reproduce, that is, it’s “fitness”, is determined by how its genes interact with the environment. Yeast is a model organism in which researchers can control the exact mutations present in the yeast’s genes (its genotype) and the conditions in which the yeast cells live (their environment). This allows researchers to measure how a yeast cell’s genotype and environment affect its fitness.

Ubiquitin is a protein that many organisms depend on to manage cell stress by acting as a tag that targets other proteins for degradation. Essential proteins such as ubiquitin often remain unchanged by mutation over long periods of time. As a result, these proteins evolve very slowly. Like all proteins, ubiquitin is built from a chain of amino acid molecules linked together, and the ubiquitin proteins of yeast and humans are made of almost identical sequences of amino acids.

Although ubiquitin has barely changed its sequence over evolution, previous studies have shown that – under normal growth conditions in the laboratory – most amino acids in ubiquitin can be mutated without any loss of cell fitness. This led Mavor et al. to hypothesize that treating the yeast cells with chemicals that cause cell stress might lead to amino acids in ubiquitin becoming more sensitive to mutation.

To test this idea, a class of graduate students at the University of California, San Francisco grew yeast cells with different ubiquitin mutations together, and with different chemicals that induce cell stress, and measured their growth rates. Sequencing the ubiquitin gene in the thousands of tested yeast cells revealed that three of the chemicals cause a shared set of amino acids in ubiquitin to become more sensitive to mutation.

This result suggests that these amino acids are important for the stress response, possibly by altering the ability of yeast cells to target certain proteins for degradation. Conversely, another chemical causes yeast to become more tolerant to changes in the ubiquitin sequence. The experiments also link changes in particular amino acids in ubiquitin to specific stress responses.

Mavor et al. show that many of ubquitin’s amino acids are sensitive to mutation under different stress conditions, while others can be mutated to form different amino acids without effecting fitness. By testing the effects of other chemicals, future experiments could further characterize how the yeast’s genotype and environment interact.

DOI:http://dx.doi.org/10.7554/eLife.15802.002

A Multiplexed High-Content Screening Approach Using the Chromobody Technology to Identify Cell Cycle Modulators in Living Cells

Many screening hits show relatively poor quality regarding later efficacy and safety. Therefore, small-molecule screening efforts shift toward high-content analysis providing more detailed information. Here, we describe a novel screening approach to identify cell cycle modulators with low toxicity by combining the Cell Cycle Chromobody (CCC) technology with the CytoTox-Glo (CTG) cytotoxicity assay. The CCC technology employs intracellularly functional single-domain antibodies coupled to a fluorescent protein (chromobodies) to visualize the cell cycle-dependent redistribution of the proliferating cell nuclear antigen (PCNA) in living cells. This image-based cell cycle analysis was combined with determination of dead-cell protease activity in cell culture supernatants by the CTG assay. We adopted this multiplex approach to high-throughput format and screened 960 Food and Drug Administration (FDA)-approved drugs. By this, we identified nontoxic compounds, which modulate different cell cycle stages, and validated selected hits in diverse cell lines stably expressing CCC. Additionally, we independently validated these hits by flow cytometry as the current state-of-the-art format for cell cycle analysis. This study demonstrates that CCC imaging is a versatile high-content screening approach to identify cell cycle modulators, which can be multiplexed with cytotoxicity assays for early elimination of toxic compounds during screening.

Prediction of drug–target interaction by label propagation with mutual interaction information derived from heterogeneous network

By implementing label propagation on drug/target similarity network with mutual interaction information derived from drug–target heterogeneous network, LPMIHN algorithm identifies potential drug–target interactions.

All-in-One azides: empowered click reaction for in vivo labeling and imaging of biomolecules

We designed and synthesized All-in-One (AIO) reactive azide reagents for bioorthogonal reactions with highly efficient Cu(i) ligand moieties, an azido group, and functional tags for imaging or purification.