Target deconvolution of bioactive small molecules: the heart of chemical biology and drug discovery

2,5-Dihydroxyterephthalic Acid: A Matrix for Improved Detection and Imaging of Amino Acids

Amino acids (AAs), which are low-molecular-weight (low-MW) metabolites, serve as essential building blocks not only for protein synthesis but also for maintaining the nitrogen balance in living systems. In situ detection and imaging of AAs are crucial for understanding more complex biological processes. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a label-free mass spectrometric imaging technique that enables the simultaneous detection and imaging of the spatial distribution and relative abundance of different endogenous/exogenous compounds in biological samples. The excellent efficiency of MALDI-MSI is attributed to the choice of the MALDI matrix. However, to the best of our knowledge, no matrix has been specifically developed for AAs. Herein, we report a MALDI matrix, 2,5-dihydroxyterephthalic acid (DHT), which can improve the detection and imaging of AAs in biological samples by MALDI-MS. Our results indicated that DHT exhibited strong ultraviolet-visible (UV-vis) absorption, uniform matrix deposition, and high vacuum stability. Moreover, the matrix-related ion signals produced from DHT were reduced by 50 and 71.8% at m/z < 500 compared to the commonly used matrices of 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA), respectively, in their respective organic solvents. In terms of quantitative performance, arginine, glutamic acid, glutamine, and proline can be detected with limits of detection of 6, 4, 6, and 4 ng/mL, respectively, using the DHT as the matrix. Using DHT as the matrix, all 20 protein AAs were successfully detected in human serum by MALDI-MS, whereas only 7 and 10 AAs were detected when DHB and CHCA matrices were used, respectively. Furthermore, 20 protein AAs and taurine were successfully detected and imaged in a section of edible Crassostrea gigas (oyster) tissue for the first time. Our study demonstrates that using DHT as a matrix can improve the detection and imaging of AAs in biological samples by MALDI-MS.

Identification of inhibitors for the transmembrane Trypanosoma cruzi eIF2α kinase relevant for parasite proliferation

The TcK2 protein kinase of Trypanosoma cruzi, the causative agent of Chagas disease, is structurally similar to the human kinase PERK, which phosphorylates the initiation factor eIF2α and, in turn, inhibits translation initiation. We have previously shown that absence of TcK2 kinase impairs parasite proliferation within mammalian cells, positioning it as a potential target for treatment of Chagas disease. To better understand its role in the parasite, here we initially confirmed the importance of TcK2 in parasite proliferation by generating CRISPR/Cas9 TcK2-null cells, albeit they more efficiently differentiate into infective forms. Proteomics indicates that the TcK2 knockout of proliferative forms expresses proteins including trans-sialidases, normally restricted to infective and nonproliferative trypomastigotes explaining decreased proliferation and better differentiation. TcK2 knockout cells lost phosphorylation of eukaryotic initiation factor 3 and cyclic AMP responsive-like element, recognized to promote growth, likely explaining both decreased proliferation and augmented differentiation. To identify specific inhibitors, a library of 379 kinase inhibitors was screened by differential scanning fluorimetry using a recombinant TcK2 encompassing the kinase domain and selected molecules were tested for kinase inhibition. Only Dasatinib and PF-477736, inhibitors of Src/Abl and ChK1 kinases, showed inhibitory activity with IC50 of 0.2 ± 0.02 mM and 0.8 ± 0.1, respectively. In infected cells Dasatinib inhibited growth of parental amastigotes (IC50 = 0.6 ± 0.2 mM) but not TcK2 of depleted parasites (IC50 > 34 mM) identifying Dasatinib as a potential lead for development of therapeutics for Chagas disease targeting TcK2.

Vutiglabridin Modulates Paraoxonase 1 and Ameliorates Diet-Induced Obesity in Hyperlipidemic Mice

Vutiglabridin is a clinical-stage synthetic small molecule that is being developed for the treatment of obesity and its target proteins have not been fully identified. Paraoxonase-1 (PON1) is an HDL-associated plasma enzyme that hydrolyzes diverse substrates including oxidized low-density lipoprotein (LDL). Furthermore, PON1 harbors anti-inflammatory and antioxidant capacities and has been implicated as a potential therapeutic target for treating various metabolic diseases. In this study, we performed a non-biased target deconvolution of vutiglabridin using Nematic Protein Organisation Technique (NPOT) and identified PON1 as an interacting protein. We examined this interaction in detail and demonstrate that vutiglabridin binds to PON1 with high affinity and protects PON1 against oxidative damage. Vutiglabridin treatment significantly increased plasma PON1 levels and enzyme activity but not PON1 mRNA in wild-type C57BL/6J mice, suggesting that vutiglabridin modulates PON1 post-transcriptionally. We further investigated the effects of vutiglabridin in obese and hyperlipidemic LDLR-/- mice and found that it significantly increases plasma PON1 levels, while decreasing body weight, total fat mass, and plasma cholesterol levels. Overall, our results demonstrate that PON1 is a direct, interacting target of vutiglabridin, and that the modulation of PON1 by vutiglabridin may provide benefits for the treatment of hyperlipidemia and obesity.

The Role of Natural Products as Sources of Therapeutic Agents for Innovative Drug Discovery

Emerging threats to human health require a concerted effort in search of both preventive and treatment strategies, placing natural products at the center of efforts to obtain new therapies and reduce disease spread and associated mortality. The therapeutic value of compounds found in plants has been known for ages, resulting in their utilization in homes and in clinics for the treatment of many ailments ranging from common headache to serious conditions such as wounds. Despite the advancement observed in the world, plant based medicines are still being used to treat many pathological conditions or are used as alternatives to modern medicines. In most cases, these natural products or plant-based medicines are used in an un-purified state as extracts. A lot of research is underway to identify and purify the active compounds responsible for the healing process. Some of the current drugs used in clinics have their origins as natural products or came from plant extracts. In addition, several synthetic analogues are natural product-based or plant-based. With the emergence of novel infectious agents such as the SARS-CoV-2 in addition to already burdensome diseases such as diabetes, cancer, tuberculosis and HIV/AIDS, there is need to come up with new drugs that can cure these conditions. Natural products offer an opportunity to discover new compounds that can be converted into drugs given their chemical structure diversity. Advances in analytical processes make drug discovery a multi-dimensional process involving computational designing and testing and eventual laboratory screening of potential drug candidates. Lead compounds will then be evaluated for safety, pharmacokinetics and efficacy. New technologies including Artificial Intelligence, better organ and tissue models such as organoids allow virtual screening, automation and high-throughput screening to be part of drug discovery. The use of bioinformatics and computation means that drug discovery can be a fast and efficient process and enable the use of natural products structures to obtain novel drugs. The removal of potential bottlenecks resulting in minimal false positive leads in drug development has enabled an efficient system of drug discovery. This review describes the biosynthesis and screening of natural products during drug discovery as well as methods used in studying natural products.

Sensing technologies and experimental platforms for the characterization of advanced oral drug delivery systems

Complex and miniaturized oral drug delivery systems are being developed rapidly for targeted, controlled drug release and improved bioavailability. Standard analytical techniques are widely used to characterize i) drug carrier and active pharmaceutical ingredients before loading into a delivery device (to ensure the solid form), and ii) the entire drug delivery system during the development process. However, in light of the complexity and the size of some of these systems, standard techniques as well as novel sensing technologies and experimental platforms need to be used in tandem. These technologies and platforms are discussed in this review, with a special focus on passive delivery systems in size range from a few 100 µm to a few mm. Challenges associated with characterizing these systems and evaluating their effect on oral drug delivery in the preclinical phase are also discussed.

ProBiS-Dock Database: A Web Server and Interactive Web Repository of Small Ligand-Protein Binding Sites for Drug Design

We have developed a new system, ProBiS-Dock, which can be used to determine the different types of protein binding sites for small ligands. The binding sites identified this way are then used to construct a new binding site database, the ProBiS-Dock Database, that allows for the ranking of binding sites according to their utility for drug development. The newly constructed database currently has more than 1.4 million binding sites and offers the possibility to investigate potential drug targets originating from different biological species. The interactive ProBiS-Dock Database, a web server and repository that consists of all small-molecule ligand binding sites in all of the protein structures in the Protein Data Bank, is freely available at http://probis-dock-database.insilab.org. The ProBiS-Dock Database will be regularly updated to keep pace with the growth of the Protein Data Bank, and our anticipation is that it will be useful in drug discovery.

Synthesis, Biological and Computational Evaluation of Novel 2,3-dihydro-2-aryl-4-(4- isobutylphenyl)-1,5-benzothiazepine Derivatives as Anticancer and Anti-EGFR Tyrosine Kinase Agents

BACKGROUND

Despite the availability of a variety of chemotherapeutic agents, cancer is still one of the leading causes of death worldwide because of the problems with existing chemotherapeutic agents like objectionable side effects, lack of selectivity, and resistance. Hence, there is an urgent need for the development of novel anticancer agents with high usefulness, fewer side effects, devoid of resistance and superior selectivity.

OBJECTIVE

The objective of this study is to synthesize a series of novel 1,5-benzothiazepine derivatives and evaluate their anticancer activity employing biological and computational methods.

METHODS

Twenty new benzothiazepines (BT1-BT20) were prepared by condensing different 1-(4- isobutylphenyl)ethanone chalcones with 2-amiothiophenol and evaluated for their anticancer activity by MTT assay against three cell lines including HT-29 (colon cancer), MCF-7 (breast cancer) and DU-145 (prostate cancer). These compounds were also tested for their inhibitory action against EGFR (Epidermal Growth Factor Receptor) tyrosine kinase enzyme by taking into account of their excellent action against colon and breast cancer cell lines. Further, the structural features responsible for the activity were identified by Pharmacophorebased modelling using Schrodinger's PHASETM software.

RESULTS

Among the 20 benzothiazepine derivatives, three compounds viz., BT18, BT19 and BT20 exhibited promising activity against the cell lines tested and the activity of BT20 was more than the standard methotrexate. Again the above three compounds showed excellent inhibitory activity with the percentage inhibition of 64.5, 57.3 and 55.8 respectively against EGFR (Epidermal Growth Factor Receptor) tyrosine kinase. PHASE identified a five-point AHHRR model for the proposed activity and the computational studies provided insights into the structural requirements for the anticancer activity and the results were consistent with the observed in vitro activity data.

CONCLUSION

These novel benzothiazepines will be useful as lead molecules for the further development of new cancer therapies against colon and breast cancers.

Streamlined Target Deconvolution Approach Utilizing a Single Photoreactive Chloroalkane Capture Tag

Identification of physiologically relevant targets for lead compounds emerging from drug discovery screens is often the rate-limiting step toward understanding their mechanism of action and potential for undesired off-target effects. To this end, we developed a streamlined chemical proteomic approach utilizing a single, photoreactive cleavable chloroalkane capture tag, which upon attachment to bioactive compounds facilitates selective isolation of their respective cellular targets for subsequent identification by mass spectrometry. When properly positioned, the tag does not significantly affect compound potency and membrane permeability, allowing for binding interactions with the tethered compound (probe) to be established within intact cells under physiological conditions. Subsequent UV-induced covalent photo-cross-linking "freezes" the interactions between the probe and its cellular targets and prevents their dissociation upon cell lysis. Targets cross-linked to the capture tag are then efficiently enriched through covalent capture onto HaloTag coated beads and subsequent selective chemical release from the solid support. The tag's built-in capability for selective enrichment eliminates the need for ligation of a capture tag, thereby simplifying the workflow and reducing variability introduced through additional operational steps. At the same time, the capacity for adequate cross-linking without structural optimization permits modular assembly of photoreactive chloroalkane probes, which reduces the burden of customized chemistry. Using three model compounds, we demonstrate the capability of this approach to identify known and novel cellular targets, including those with low affinity and/or low abundance as well as membrane targets with several transmembrane domains.

A New Metric Quantifying Chemical and Biological Property of Small Molecule Metabolites and Drugs

One prominent class of drugs is chemical small molecules (CSMs), but the majority of CSMs are of very low druggable potential. Therefore, it is quite important to predict drug-related properties (druggable properties) for candidate CSMs. Currently, a number of druggable properties (e.g., logP and pKa) can be calculated by in silico methods; still the identification of druggable CSMs is a high-risk task, and new quantitative metrics for the druggable potential of CSMs are increasingly needed. Here, we present normalized bond energy (NBE), a new metric for the above purpose. By applying NBE to the DrugBank CSMs whose properties are largely known, we revealed that NBE is able to describe a number of critical druggable properties including logP, pKa, membrane permeability, blood-brain barrier penetration, and human intestinal absorption. Moreover, given that the human endogenous metabolites can serve as important resources for drug discovery, we applied NBE to the metabolites in the Human Metabolome Database. As a result, NBE showed a significant difference in metabolites from various body fluids and was correlated with some important properties, including melting point and water solubility.

Discovery and preclinical efficacy of HSG4112, a synthetic structural analog of glabridin, for the treatment of obesity

Background

HSG4112 is a clinical-stage drug candidate for the treatment of obesity. Here, we report its discovery and preclinical efficacy.

Methods

In high-fat diet (HFD)-induced obese male C57BL/6J mice, we tested the weight loss effect of synthetic compounds derived from a structure–activity relationship (SAR) study of glabridin, a natural compound known to reduce body weight and influence energy homeostasis. After selecting HSG4112 as our optimized compound from this discovery method, we characterized its pharmacological effects on parameters related to obesity through in vivo metabolic and biochemical measurements, histology and gene expression analysis, and indirect calorimetry.

Results

Through the SAR study, we identified four novel components of glabridin pertinent for its anti-obesity activity, and found that HSG4112, an optimized structural analog of glabridin, markedly supersedes glabridin in weight reduction efficacy and chemical stability. Six-week administration of HSG4112 to HFD-induced obese mice led to dose-dependent normalization of obesity-related parameters, including body weight, muscle and adipose tissue weight, adipocyte size, and serum leptin/insulin/glucose levels. The weight reduction induced by HSG4112 was partially mediated by decreased food intake and mainly mediated by increased energy expenditure, with no change in physical activity. Accordingly, the pattern of transcriptional changes was aligned with increased energy expenditure in the liver and muscles. Following significant body weight reduction, robust amelioration of histopathology and blood markers of fatty liver were also observed.

Conclusions

Our study demonstrates the key chemical components of glabridin pertinent to its weight loss effects and suggests HSG4112 as a promising novel drug candidate for the pharmacological treatment of obesity.

Identification of the Molecular Mechanisms of Peimine in the Treatment of Cough Using Computational Target Fishing

Peimine (also known as verticine) is the major bioactive and characterized compound of Fritillariae Thunbergii Bulbus, a traditional Chinese medicine that is most frequently used to relieve a cough. Nevertheless, its molecular targets and mechanisms of action for cough are still not clear. In the present study, potential targets of peimine for cough were identified using computational target fishing combined with manual database mining. In addition, protein-protein interaction (PPI), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using, GeneMANIA and Database for Annotation, Visualization and Integrated Discovery (DAVID) databases respectively. Finally, an interaction network of drug-targets-pathways was constructed using Cytoscape. The results identified 23 potential targets of peimine associated with cough, and suggested that MAPK1, AKT1 and PPKCB may be important targets of pemine for the treatment of cough. The functional annotations of protein targets were related to the regulation of immunological and neurological function through specific biological processes and related pathways. A visual representation of the multiple targets and pathways that form a network underlying the systematic actions of peimine was generated. In summary, peimine is predicted to exert its systemic pharmacological effects on cough by targeting a network composed of multiple proteins and pathways.

MolTarPred: A web tool for comprehensive target prediction with reliability estimation

Molecular target prediction can provide a starting point to understand the efficacy and side effects of phenotypic screening hits. Unfortunately, the vast majority of in silico target prediction methods are not available as web tools. Furthermore, these are limited in the number of targets that can be predicted, do not estimate which target predictions are more reliable and/or lack comprehensive retrospective validations. We present MolTarPred ( http://moltarpred.marseille.inserm.fr/), a user-friendly web tool for predicting protein targets of small organic compounds. It is powered by a large knowledge base comprising 607,659 compounds and 4,553 macromolecular targets collected from the ChEMBL database. In about 1 min, the predicted targets for the supplied molecule will be listed in a table. The chemical structures of the query molecule and the most similar compounds annotated with the predicted target will also be shown to permit visual inspection and comparison. Practical examples of the use of MolTarPred are showcased. MolTarPred is a new resource for scientists that require a more complete knowledge of the polypharmacology of a molecule. The introduction of a reliability score constitutes an attractive functionality of MolTarPred, as it permits focusing experimental confirmatory tests on the most reliable predictions, which leads to higher prospective hit rates.

Drugs that target aging: how do we discover them?

INTRODUCTION

Biology of aging is focused on elucidating the biochemical and genetic pathways that contribute to cellular damage accumulation over time. Thirty years of research are beginning to bear fruit as the first pharmacological interventions based on biology of aging go through clinical trials. Evolutionary theories of aging suggest that naturally selected traits believed to impart fitness in young organisms may be damaging in later life. Three major areas of focus in biology of aging are lifespan, healthspan, and rejuvenation. Areas covered: Aging research has produced several validated pharmacological interventions currently in clinical trials. Herein, the authors consider two representative case studies: 1) rapamycin analogs and their effect on the mTORC1 pathway, and 2) small molecules that target and kill senescent cells. The authors also provide their expert current and future perspectives on aging targeting drug discovery. Expert opinion: Aging-related therapeutic interventions will continue to emerge at an accelerating pace, both from research in biology of aging, as well as from coordinated biomedical research in aging-related chronic conditions.

Unbiased Screens for Modifiers of Alpha-Synuclein Toxicity

PURPOSE OF REVIEW

We provide an overview about unbiased screens to identify modifiers of alpha-synuclein (αSyn)-induced toxicity, present the models and the libraries that have been used for screening, and describe how hits from primary screens were selected and validated.

RECENT FINDINGS

Screens can be classified as either genetic or chemical compound modifier screens, but a few screens do not fit this classification. Most screens addressing αSyn-induced toxicity, including genome-wide overexpressing and deletion, were performed in yeast. More recently, newer methods such as CRISPR-Cas9 became available and were used for screening purposes. Paradoxically, given that αSyn-induced toxicity plays a role in neurological diseases, there is a shortage of human cell-based models for screening. Moreover, most screens used mutant or fluorescently tagged forms of αSyn and only very few screens investigated wild-type αSyn. Particularly, no genome-wide αSyn toxicity screen in human dopaminergic neurons has been published so far. Most unbiased screens for modifiers of αSyn toxicity were performed in yeast, and there is a lack of screens performed in human and particularly dopaminergic cells.

Identification of Protein Targets of Bioactive Small Molecules Using Randomly Photomodified Probes

Identifying protein targets of bioactive small molecules often requires complex, lengthy development of affinity probes. We present a method for stochastic modification of small molecules of interest with a photoactivatable phenyldiazirine linker. The resulting isomeric mixture is conjugated to a hydrophilic copolymer decorated with biotin and a fluorophore. We validated this approach using known inhibitors of several medicinally relevant enzymes. At least a portion of the stochastic derivatives retained their binding to the target, enabling target visualization, isolation, and identification. Moreover, the mix of stochastic probes could be separated into fractions and tested for binding affinity. The structure of the active probe could be determined and the probe resynthesized to improve binding efficiency. Our approach can thus enable rapid target isolation, identification, and visualization, while providing information required for subsequent synthesis of an optimized probe.

Dynamic Proteomics Reveals High Plasticity of Cellular Proteome: Growth-Related and Drug-Induced Changes in Cancer Cells are Comparable

In chemical proteomics, the changes occurring in cellular proteomes upon drug treatment are used to identify the drug targets and the mechanism of action. However, proteomes of cultured cells undergo also natural alteration associated with changes in the media, attaining a degree of confluence as well as due to cell division and cell metabolism. These changes are implicitly assumed to be smaller in magnitude than the drug-induced changes that ultimately lead to cell demise. In this study, it is shown that growth-related proteome changes in the untreated control group are comparable in magnitude to drug-induced changes over the course of 48 h treatment. In two well-characterized cancer cell lines, growth-related effects assessed with deep proteomics analysis (10 481 proteins quantified with at least two peptides) show common trends, the steady downregulation of cell division processes, and the upregulation of metabolism-related pathways. The magnitude of these variations, which are present even before reaching 100% confluence reveals unexpectedly high plasticity of the cellular proteome. This finding reinforces the need, generally accepted in theory but not always followed in practice, to use a time-matched control when measuring drug-induced proteome changes.

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of protein-protein interactions (PPI) is no novelty, experimental approaches aiming to characterize endogenous protein-metabolite interactions (PMI) constitute a rather recent development. Herein, we present a protocol that allows simultaneous characterization of the PPI and PMI of a protein of choice, referred to as bait. Our protocol was optimized for Arabidopsis cell cultures and combines affinity purification (AP) with mass spectrometry (MS)-based protein and metabolite detection. In short, transgenic Arabidopsis lines, expressing bait protein fused to an affinity tag, are first lysed to obtain a native cellular extract. Anti-tag antibodies are used to pull down protein and metabolite partners of the bait protein. The affinity-purified complexes are extracted using a one-step methyl tert-butyl ether (MTBE)/methanol/water method. Whilst metabolites separate into either the polar or the hydrophobic phase, proteins can be found in the pellet. Both metabolites and proteins are then analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS or UPLC-MS/MS). Empty-vector (EV) control lines are used to exclude false positives. The major advantage of our protocol is that it enables identification of protein and metabolite partners of a target protein in parallel in near-physiological conditions (cellular lysate). The presented method is straightforward, fast, and can be easily adapted to biological systems other than plant cell cultures.

Hybrid in silico/in vitro target fishing to assign function to "orphan" compounds of food origin - The case of the fungal metabolite atromentin

Many small molecules of food origin may effect human health but lack an adequate description of their biological activity. To fill this knowledge gap, a first-line workflow is needed to assign putative functions, rank the endpoints for testing and guide wet-lab experiments. In this framework, the identification of potential biological targets can be used to probe the activity of orphan compounds using a so-called "target fishing" approach. Here, we present a proof of concept study using an in silico/in vitro target fishing approach on the fungal secondary metabolite atromentin. The procedure relies on a computational screening for activity identification coupled with experimental trials for dose-response characterization. Computational results identified estrogen receptors and 17-β-hydroxysteroid dehydrogenase as potential targets. Experiments confirmed a weak estrogenic activity, supporting the reliability of the procedure. Despite limited estrogenicity of atromentin, the proposed inhibition of 17-β-hydroxysteroid dehydrogenase should be considered as a source for endocrine disruptive effects.

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery

The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

Toxicodynamics of Mycotoxins in the Framework of Food Risk Assessment-An In Silico Perspective

Mycotoxins severely threaten the health of humans and animals. For this reason, many countries have enforced regulations and recommendations to reduce the dietary exposure. However, even though regulatory actions must be based on solid scientific knowledge, many aspects of their toxicological activity are still poorly understood. In particular, deepening knowledge on the primal molecular events triggering the toxic stimulus may be relevant to better understand the mechanisms of action of mycotoxins. The present work presents the use of in silico approaches in studying the mycotoxins toxicodynamics, and discusses how they may contribute in widening the background of knowledge. A particular emphasis has been posed on the methods accounting the molecular initiating events of toxic action. In more details, the key concepts and challenges of mycotoxins toxicology have been introduced. Then, topical case studies have been presented and some possible practical implementations of studying mycotoxins toxicodynamics have been discussed.

Structure-Based Kinase Profiling To Understand the Polypharmacological Behavior of Therapeutic Molecules

Several drugs elicit their therapeutic efficacy by modulating multiple cellular targets and possess varied polypharmacological actions. The identification of the molecular targets of a potent bioactive molecule is essential in determining its overall polypharmacological profile. Experimental procedures are expensive and time-consuming. Therefore, computational approaches are actively implemented in rational drug discovery. Here, we demonstrate a computational pipeline, based on reverse virtual screening technique using several consensus scoring strategies, and perform structure-based kinase profiling of 12 FDA-approved drugs. This target prediction showed an overall good performance, with an average AU-ROC greater than 0.85 for most drugs, and identified the true targets even at the top 2% cutoff. In contrast, 10 non-kinase binder drugs exhibited lower binding efficiency and appeared in the bottom of ranking list. Subsequently, we validated this pipeline on a potent therapeutic molecule, mahanine, whose polypharmacological profile related to targeting kinases is unknown. Our target-prediction method identified different kinases. Furthermore, we have experimentally validated that mahanine is able to modulate multiple kinases that are involved in cross-talk with different signaling molecules, which thereby exhibits its polypharmacological action. More importantly, in vitro kinase assay exhibited the inhibitory effect of mahanine on two such predicted kinases' (mTOR and VEGFR2) activity, with IC₅₀ values being ∼12 and ∼22 μM, respectively. Next, we generated a comprehensive drug-protein interaction fingerprint that explained the basis of their target selectivity. We observed that it is controlled by variations in kinase conformations followed by significant differences in crucial hydrogen-bond and van der Waals interactions. Such structure-based kinase profiling could provide useful information in revealing the unknown targets of therapeutic molecules from their polypharmacological behavior and would assist in drug discovery.

Chemical Proteomic Approaches Targeting Cancer Stem Cells: A Review of Current Literature

Cancer stem cells (CSCs) have been proposed as central drivers of tumor initiation, progression, recurrence, and therapeutic resistance. Therefore, identifying stem-like cells within cancers and understanding their properties is crucial for the development of effective anticancer therapies. Recently, chemical proteomics has become a powerful tool to efficiently determine protein networks responsible for CSC pathophysiology and comprehensively elucidate molecular mechanisms of drug action against CSCs. This review provides an overview of major methodologies utilized in chemical proteomic approaches. In addition, recent successful chemical proteomic applications targeting CSCs are highlighted. Future direction of potential CSC research by integrating chemical genomic and proteomic data obtained from a single biological sample of CSCs are also suggested in this review.

Chemical genetics-based development of small molecules targeting hepatitis C virus

Hepatitis C virus (HCV) infection is a major worldwide problem that has emerged as one of the most significant diseases affecting humans. There are currently no vaccines or efficient therapies without side effects, despite today's advanced medical technology. Currently, the common therapy for most patients (i.e. genotype 1) is combination of HCV-specific direct-acting antivirals (DAAs). Up to 2011, the standard of care (SOC) was a combination of peg-IFNα with ribavirin (RBV). After approval of NS3/4A protease inhibitor, SOC was peg-IFNα and RBV with either the first-generation DAAs boceprevir or telaprevir. In the past several years, various novel small molecules have been discovered and some of them (i.e., HCV polymerase, protease, helicase and entry inhibitors) have undergone clinical trials. Between 2013 and 2016, the second-generation DAA drugs simeprevir, asunaprevir, daclatasvir, dasabuvir, sofosbuvir, and elbasvir were approved, as well as the combinational drugs Harvoni^®, Zepatier^®, Technivie^®, and Epclusa^®. A number of reviews have been recently published describing the structure-activity relationship (SAR) in the development of HCV inhibitors and outlining current therapeutic approaches to hepatitis C infection. Target identification involves studying a drug's mechanism of action (MOA), and a variety of target identification methods have been developed in the past few years. Chemical biology has emerged as a powerful tool for studying biological processes using small molecules. The use of chemical genetic methods is a valuable strategy for studying the molecular mechanisms of the viral lifecycle and screening for anti-viral agents. Two general screening approaches have been employed: forward and reverse chemical genetics. This review reveals information on the small molecules in HCV drug discovery by using chemical genetics for targeting the HCV protein and describes successful examples of targets identified with these methods.

High-content drug screening for rare diseases

Per definition, rare diseases affect only a small number of subjects within a given population. Taken together however, they represent a considerable medical burden, which remains poorly addressed in terms of treatment. Compared to other diseases, obstacles to the development of therapies for rare diseases include less extensive physiopathology knowledge, limited number of patients to test treatments, and poor commercial interest from the industry. Recently, advances in high-throughput and high-content screening (HTS and HCS) have been fostered by the development of specific routines that use robot- and computer-assisted technologies to automatize tasks, allowing screening of a large number of compounds in a short period of time, using experimental model of diseases. These approaches are particularly relevant for drug repositioning in rare disease, which restricts the search to compounds that have already been tested in humans, thereby reducing the need for extensive preclinical tests. In the future, these same tools, combined with computational modeling and artificial neural network analyses, may also be used to predict individual clinical responses to drugs in a personalized medicine approach.

Affinity purification with metabolomic and proteomic analysis unravels diverse roles of nucleoside diphosphate kinases

Interactions between metabolites and proteins play an integral role in all cellular functions. Here we describe an affinity purification (AP) approach in combination with LC/MS-based metabolomics and proteomics that allows, to our knowledge for the first time, analysis of protein-metabolite and protein-protein interactions simultaneously in plant systems. More specifically, we examined protein and small-molecule partners of the three (of five) nucleoside diphosphate kinases present in the Arabidopsis genome (NDPK1-NDPK3). The bona fide role of NDPKs is the exchange of terminal phosphate groups between nucleoside diphosphates (NDPs) and triphosphates (NTPs). However, other functions have been reported, which probably depend on both the proteins and small molecules specifically interacting with the NDPK. Using our approach we identified 23, 17, and 8 novel protein partners of NDPK1, NDPK2, and NDPK3, respectively, with nucleotide-dependent proteins such as actin and adenosine kinase 2 being enriched. Particularly interesting, however, was the co-elution of glutathione S-transferases (GSTs) and reduced glutathione (GSH) with the affinity-purified NDPK1 complexes. Following up on this finding, we could demonstrate that NDPK1 undergoes glutathionylation, opening a new paradigm of NDPK regulation in plants. The described results extend our knowledge of NDPKs, the key enzymes regulating NDP/NTP homeostasis.

Selective purification and chemical labeling of a target protein on ruthenium photocatalyst-functionalized affinity beads

Selective purification and chemical labeling of a target protein in a protein mixture were simultaneously achieved on the surface of affinity beads functionalized with ligands, such as benzenesulfonamide and methotrexate (MTX), and a ruthenium complex containing 2,2'-bipyridine-4,4'-dicarboxylic acid (dcbpy). Chemical labeling of the target protein with a tyrosine radical trapper (TRT) proceeded on the surface of the beads when the target protein was in close proximity to the ruthenium photocatalyst. Both the protein purification and chemical labeling abilities of the affinity beads functionalized with ruthenium photocatalyst were not compromised after recycling several times. Dihydrofolate reductase (DHFR) endogenously expressed in HeLa cells was detected by chemical labeling with biotin-TRT on the affinity beads with high sensitivity compared to the conventional silver staining method.

Identification of Small Molecule-binding Proteins in a Native Cellular Environment by Live-cell Photoaffinity Labeling

Identifying the molecular target(s) of small molecules is a challenging but necessary step towards understanding their mechanism of action. While several target identification methods have been developed and used to successfully elucidate the binding proteins of a variety of small molecules, these techniques have drawbacks that make them unsuitable for detecting certain types of small molecule-target interactions. In particular, non-covalent interactions that depend on native cellular conditions, such as those of membrane proteins whose structures may be perturbed upon cell lysis, are often not amenable to affinity-based target identification methods. Here, we demonstrate a method wherein a probe containing a photolabile group is used to covalently crosslink to the small molecule binding protein within the environment of the live cell, allowing the detection and isolation of the target protein without the need for maintenance of the interaction after cell lysis. This technique is a valuable tool for studying biologically interesting small molecules with unknown mechanisms, both in the context of basic biology as well as drug discovery.

Identifying the cellular targets of natural products using T7 phage display

A description of the T7 phage biopanning procedure is provided with tips and advice suitable for setup in a chemistry laboratory.

Advances in identification and validation of protein targets of natural products without chemical modification

This review focuses on and reports case studies of the latest advances in target protein identification methods for label-free natural products. The integration of newly developed technologies will provide new insights and highlight the value of natural products for use as biological probes and new drug candidates.