Chemoproteomics for Plasmodium Parasite Drug Target Discovery

Emerging Plasmodium parasite drug resistance is threatening progress towards malaria control and elimination. While recent efforts in cell-based, high-throughput drug screening have produced first-in-class drugs with promising activities against different Plasmodium life cycle stages, most of these antimalarial agents have elusive mechanisms of action. Though challenging to address, target identification can provide valuable information to facilitate lead optimization and preclinical drug prioritization. Recently, proteome-wide methods for direct assessment of drug-protein interactions have emerged as powerful tools in a number of systems, including Plasmodium. In this review, we will discuss current chemoproteomic strategies that have been adapted to antimalarial drug target discovery, including affinity- and activity-based protein profiling and the energetics-based techniques thermal proteome profiling and stability of proteins from rates of oxidation. The successful application of chemoproteomics to the Plasmodium blood stage highlights the potential of these methods to link inhibitors to their molecular targets in more elusive Plasmodium life stages and intracellular pathogens in the future.     

SP3-FAIMS Chemoproteomics for High-Coverage Profiling of the Human Cysteinome**

Chemoproteomics has enabled the rapid and proteome-wide discovery of functional, redox-sensitive, and ligandable cysteine residues. Despite widespread adoption and considerable advances in both sample-preparation workflows and MS instrumentation, chemoproteomics experiments still typically only identify a small fraction of all cysteines encoded by the human genome. Here, we develop an optimized sample-preparation workflow that combines enhanced peptide labeling with single-pot, solid-phase-enhanced sample-preparation (SP3) to improve the recovery of biotinylated peptides, even from small sample sizes. By combining this improved workflow with on-line high-field asymmetric waveform ion mobility spectrometry (FAIMS) separation of labeled peptides, we achieve unprecedented coverage of >14000 unique cysteines in a single-shot 70 min experiment. Showcasing the wide utility of the SP3-FAIMS chemoproteomic method, we find that it is also compatible with competitive small-molecule screening by isotopic tandem orthogonal proteolysis–activity-based protein profiling (isoTOP-ABPP). In aggregate, our analysis of 18 samples from seven cell lines identified 34225 unique cysteines using only ∼28 h of instrument time. The comprehensive spectral library and improved coverage provided by the SP3-FAIMS chemoproteomics method will provide the technical foundation for future studies aimed at deciphering the functions and druggability of the human cysteineome.     

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022).     

用于新药开发的新的蛋白质功能预测方法

简述了在蛋白质功能预测领域中的研究方法和最新研发工具所面临的挑战,并讨论蛋白质功能预测是如何改变药物开发进展的,具体包括:基于序列同源性分析的注释转移、序列基元和模式增加了注释转移的说服力、3D结构信息可以精炼注释转移、亚细胞定位、翻译后修饰、结合位点和功能残基、蛋白质之间的相互作用.     

Drug Target Identification with Machine Learning: How to Choose Negative Examples

Identification of the protein targets of hit molecules is essential in the drug discovery process. Target prediction with machine learning algorithms can help accelerate this search, limiting the number of required experiments. However, Drug-Target Interactions databases used for training present high statistical bias, leading to a high number of false positives, thus increasing time and cost of experimental validation campaigns. To minimize the number of false positives among predicted targets, we propose a new scheme for choosing negative examples, so that each protein and each drug appears an equal number of times in positive and negative examples. We artificially reproduce the process of target identification for three specific drugs, and more globally for 200 approved drugs. For the detailed three drug examples, and for the larger set of 200 drugs, training with the proposed scheme for the choice of negative examples improved target prediction results: the average number of false positives among the top ranked predicted targets decreased, and overall, the rank of the true targets was improved.Our method corrects databases’ statistical bias and reduces the number of false positive predictions, and therefore the number of useless experiments potentially undertaken.     

Fragment-Based Drug Discovery against Mycobacteria: The Success and Challenges

The emergence of drug-resistant mycobacteria, including Mycobacterium tuberculosis (Mtb) and non-tuberculous mycobacteria (NTM), poses an increasing global threat that urgently demands the development of new potent anti-mycobacterial drugs. One of the approaches toward the identification of new drugs is fragment-based drug discovery (FBDD), which is the most ingenious among other drug discovery models, such as structure-based drug design (SBDD) and high-throughput screening. Specialized techniques, such as X-ray crystallography, nuclear magnetic resonance spectroscopy, and many others, are part of the drug discovery approach to combat the Mtb and NTM global menaces. Moreover, the primary drawbacks of traditional methods, such as the limited measurement of biomolecular toxicity and uncertain bioavailability evaluation, are successfully overcome by the FBDD approach. The current review focuses on the recognition of fragment-based drug discovery as a popular approach using virtual, computational, and biophysical methods to identify potent fragment molecules. FBDD focuses on designing optimal inhibitors against potential therapeutic targets of NTM and Mtb (PurC, ArgB, MmpL3, and TrmD). Additionally, we have elaborated on the challenges associated with the FBDD approach in the identification and development of novel compounds. Insights into the applications and overcoming the challenges of FBDD approaches will aid in the identification of potential therapeutic compounds to treat drug-sensitive and drug-resistant NTMs and Mtb infections.     

生物高分子磁性微球的制备及靶向给药应用

生物高分子磁性微球因具有磁效应、生物相容性和多种反应活性功能基团等特性,使其能广泛应用于生物医学、细胞学和生物工程等领域。综述了近年来生物高分子磁性微球的制备方法以及作为靶向给药载体的应用。     

Differential Chemoproteomics Reveals MARK2/3 as Cell Migration-Relevant Targets of the ALK Inhibitor Brigatinib

Metastasis poses a major challenge in cancer management, including EML4-ALK-rearranged non-small cell lung cancer (NSCLC). As cell migration is a critical step during metastasis, we assessed the anti-migratory activities of several clinical ALK inhibitors in NSCLC cells and observed differential anti-migratory capabilities despite similar ALK inhibition, with brigatinib displaying superior anti-migratory effects over other ALK inhibitors. Applying an unbiased in situ mass spectrometry-based chemoproteomics approach, we determined the proteome-wide target profile of brigatinib in EML4-ALK+ NSCLC cells. Dose-dependent and cross-competitive chemoproteomics suggested MARK2 and MARK3 as relevant brigatinib kinase targets. Functional validation showed that combined pharmacological inhibition or genetic modulation of MARK2/3 inhibited cell migration. Consistently, brigatinib treatment induced inhibitory YAP1 phosphorylation downstream of MARK2/3. Collectively, our data suggest that brigatinib exhibits unusual cross-phenotype polypharmacology as, despite similar efficacy for inhibiting EML4-ALK-dependent cell proliferation as other ALK inhibitors, it more effectively prevented migration of NSCLC cells due to co-targeting of MARK2/3.     

De Novo Prediction of Drug Targets and Candidates by Chemical Similarity-Guided Network-Based Inference

Identifying drug–target interactions is a crucial step in discovering novel drugs and for drug repositioning. Network-based methods have shown great potential thanks to the straightforward integration of information from different sources and the possibility of extracting novel information from the graph topology. However, despite recent advances, there is still an urgent need for efficient and robust prediction methods. Here, we present SimSpread, a novel method that combines network-based inference with chemical similarity. This method employs a tripartite drug–drug–target network constructed from protein–ligand interaction annotations and drug–drug chemical similarity on which a resource-spreading algorithm predicts potential biological targets for both known or failed drugs and novel compounds. We describe small molecules as vectors of similarity indices to other compounds, thereby providing a flexible means to explore diverse molecular representations. We show that our proposed method achieves high prediction performance through multiple cross-validation and time-split validation procedures over a series of datasets. In addition, we demonstrate that our method performed a balanced exploration of both chemical ligand space (scaffold hopping) and biological target space (target hopping). Our results suggest robust and balanced performance, and our method may be useful for predicting drug targets, virtual screening, and drug repositioning.     

Photoaffinity Labeling-Based Chemoproteomic Strategy Reveals RBBP4 as a Cellular Target of Protopanaxadiol against Colorectal Cancer Cells

Protopanaxadiol (PPD), a main ginseng metabolite, exerts powerful anticancer effects against multiple types of cancer; however, its cellular targets remain elusive. Here, we synthesized a cell-permeable PPD probe via introducing a bifunctional alkyne-containing diazirine photo-crosslinker and performed a photoaffinity labeling-based chemoproteomic study. We identified retinoblastoma binding protein 4 (RBBP4), a chromatin remodeling factor, as an essential cellular target of PPD in HCT116 colorectal cancer cells. PPD significantly decreased RBBP4-dependent trimethylation at lysine 27 of histone H3 (H3K27me3), a crucial epigenetic marker that correlates with histologic signs of colorectal cancer aggressiveness, and PPD inhibition of proliferation and migration of HCT116 cells was antagonized by RBBP4 RNA silencing. Collectively, our study highlights a previously undisclosed anti-colorectal cancer cellular target of the ginseng metabolite and advances the fundamental understanding of RBBP4 functions via a chemical biology strategy.     

昆虫抗性靶标部位及其在杀虫剂创制中的作用

本文从昆虫抗药性机理出发,重点评述了三种具有潜在开发价值的杀虫剂靶标部位(GABA受体,电压敏感性钠通道和乙酰胆碱酯酶),介绍了几种具有新颖作用机制的、无交互抗性的新农药品种,最后讨论了新杀虫剂创制的新途径及其意义。     

Discovery and Validation of Lmj_04_BRCT Domain,a Novel Therapeutic Target: Identification of Candidate Drugs for Leishmaniasis

Since many of the currently available antileishmanial treatments exhibit toxicity, low effectiveness, and resistance, search and validation of new therapeutic targets allowing the development of innovative drugs have become a worldwide priority. This work presents a structure-based drug discovery strategy to validate the Lmj_04_BRCT domain as a novel therapeutic target in Leishmania spp. The structure of this domain was explored using homology modeling, virtual screening, and molecular dynamics studies. Candidate compounds were validated in vitro using promastigotes of Leishmania major, L. amazonensis, and L. infantum, as well as primary mouse macrophages infected with L. major. The novel inhibitor CPE2 emerged as the most active of a group of compounds against Leishmania, being able to significantly reduce the viability of promastigotes. CPE2 was also active against the intracellular forms of the parasites and significantly reduced parasite burden in murine macrophages without exhibiting toxicity in host cells. Furthermore, L. major promastigotes treated with CPE2 showed significant lower expression levels of several genes (α-tubulin, Cyclin CYCA, and Yip1) related to proliferation and treatment resistance. Our in silico and in vitro studies suggest that the Lmj_04_BRCT domain and its here disclosed inhibitors are new potential therapeutic options against leishmaniasis.     

Indole-3-Glycerol Phosphate Synthase From Mycobacterium tuberculosis: A Potential New Drug Target

Tuberculosis (TB), caused by the pathogen Mycobacterium tuberculosis, affects millions of people worldwide. Several TB drugs have lost efficacy due to emerging drug resistance and new anti-TB targets are needed. Recent research suggests that indole-3-glycerol phosphate synthase (IGPS) in M. tuberculosis (MtIGPS) could be such a target. IGPS is a (β/α)₈-barrel enzyme that catalyzes the conversion of 1-(o-carboxyphenylamino)-1-deoxyribulose 5’-phosphate (CdRP) into indole-glycerol-phosphate (IGP) in the bacterial tryptophan biosynthetic pathway. M. tuberculosis over expresses the tryptophan pathway genes during an immune response and inhibition of MtIGPS allows CD4 T-cells to more effectively fight against M. tuberculosis. Here we review the published data on MtIGPS expression, kinetics, mechanism, and inhibition. We also discuss MtIGPS crystal structures and compare them to other IGPS structures to reveal potential structure-function relationships of interest for the purposes of drug design and biocatalyst engineering.     

Benzimidazoles in Drug Discovery: A Patent Review

Benzimidazole is a heterocyclic ring system that has been widely studied in the pharmaceutical field. For the past decade, numerous benzimidazole derivatives have been synthesized and evaluated for their wide range of pharmacological activities, which are beneficial for drug development. This article presents the biological effects of benzimidazole derivatives in each invention from 2015 to 2020. Two patent databases, Google Patents and Lens, were used to locate relevant granted patent applications. Specifically, this review delineates the role of patented benzimidazoles from a disease-centric perspective and examines the mechanisms of action of these compounds in related diseases. Most of the benzimidazoles have shown good activities against various target proteins. Whilst several of them have progressed into clinical trials, most patents presented novel therapeutic approaches for respective target diseases. Hence, their potential in being developed into clinical drugs are also discussed.     

Differently Tagged Probes for Protein Profiling of Mitochondria

The mitochondrion is one of the most important organelles in the eukaryotic cell. Characterization of the mitochondrial proteome is a prerequisite for understanding its cellular functions at the molecular level. Here we report a proteomics method based on mitochondrion-targeting groups and click chemistry. In our strategy, three different mitochondrion-targeting moieties were each augmented with a clickable handle and a cysteine-reactive group. Fluorescence-based bioimaging and fractionation experiments clearly showed that most signals arising from the labels were localized in the mitochondria of cells, as a result of covalent attachment between probe and target proteins. The three probes had distinct profiling characteristics. Furthermore, we successfully identified more than two hundred mitochondrial proteins. The results showed that different mitochondrion-targeting groups targeted distinct proteins with partial overlap. Most of the labeled proteins were localized in the mitochondrial matrix and inner mitochondrial membrane. Our results provide a tool for chemoproteomic analysis of mitochondrion-related proteins.     

A Nucleophilic Activity-Based Probe Enables Profiling of PLP-Dependent Enzymes

PLP-dependent enzymes represent an important class of highly “druggable” enzymes that perform a wide array of critical reactions to support all organisms. Inhibition of individual members of this family of enzymes has been validated as a therapeutic target for pathologies ranging from infection with Mycobacterium tuberculosis to epilepsy. Given the broad nature of the activities within this family of enzymes, we envisioned a universally acting probe to characterize existing and putative members of the family that also includes the necessary chemical moieties to enable activity-based protein profiling experiments. Hence, we developed a probe that contains an N-hydroxyalanine warhead that acts as a covalent inhibitor of PLP-dependent enzymes, a linear diazirine for UV crosslinking, and an alkyne moiety to enable enrichment of crosslinked proteins. Our molecule was used to study PLP-dependent enzymes in vitro as well as look at whole-cell lysates of M. tuberculosis and assess inhibitory activity. The probe was able to enrich and identify LysA, a PLP-dependent enzyme crucial for lysine biosynthesis, through mass spectrometry. Overall, our study shows the utility of this trifunctional first-generation probe. We anticipate further optimization of probes for PLP-dependent enzymes will enable the characterization of rationally designed covalent inhibitors of PLP-dependent enzymes, which will expedite the preclinical characterization of these important therapeutic targets.     

Activity-Based Protein Profiling (ABPP) of Oxidoreductases

Over the last two decades, activity-based protein profiling (ABPP) has been established as a tremendously useful proteomic tool for measuring the activity of proteins in their cellular context, annotating the function of uncharacterized proteins, and investigating the target profile of small-molecule inhibitors. Unlike hydrolases and other enzyme classes, which exhibit a characteristic nucleophilic residue, oxidoreductases have received much less attention in ABPP. In this minireview, the state of the art of ABPP of oxidoreductases is described and the scope and limitations of the existing approaches are discussed. It is noted that several ABPP probes have been described for various oxidases, but none so far for a reductase, which gives rise to opportunities for future research.     

Fragment-Based Drug Discovery for RNA Targets

Rapid development within the fields of both fragment-based drug discovery (FBDD) and medicinal targeting of RNA provides possibilities for combining technologies and methods in novel ways. This review provides an overview of fragment-based screening (FBS) against RNA targets, including a discussion of the most recently used screening and hit validation methods such as NMR spectroscopy, X-ray crystallography, and virtual screening methods. A discussion of fragment library design based on research from small-molecule RNA binders provides an overview on both the currently limited guidelines within RNA-targeting fragment library design, and future possibilities. Finally, future perspectives are provided on screening and hit validation methods not yet used in combination with both fragment screening and RNA targets.     

RCM反应以及其在药物研究开发中的应用

RCM反应是一类十分重要的环合反应。RCM反应机理独特、方便易行,因而在具有生物活性环状化合物的合成以及结构优化研究方面得到了大量的应用。本文介绍了RCM反应的基本概况和研究新进展,重点介绍了本反应在药物研究开发中的实际应用。