High content screening for drug discovery from traditional Chinese medicine

A dual-target SPR screening system for simultaneous ligand discovery of SARS-CoV-2 spike protein and its receptor ACE2 from Chinese herbs

Traditional Chinese Medicine (TCM) is a supremely valuable resource for the development of drug discovery. Few methods are capable of hunting for potential molecule ligands from TCM towards more than one single protein target. In this study, a novel dual-target surface plasmon resonance (SPR) biosensor was developed to perform targeted compound screening of two key proteins involved in the cellular invasion process of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): the spike (S) protein receptor binding domain (RBD) and the angiotensin-converting enzyme 2 (ACE2). The screening and identification of active compounds from six Chinese herbs were conducted taking into consideration the multi-component and multi-target nature of Traditional Chinese Medicine (TCM). Puerarin from Radix Puerariae Lobatae was discovered to exhibit specific binding affinity to both S protein RBD and ACE2. The results highlight the efficiency of the dual-target SPR system in drug screening and provide a novel approach for exploring the targeted mechanisms of active components from Chinese herbs for disease treatment.

Computational Approaches for the Structure-Based Identification of Novel Inhibitors Targeting Nucleoid-Associated Proteins in Mycobacterium Tuberculosis

Implementation of computational tools in the identification of novel drug targets for Tuberculosis (TB) has been a promising area of research. TB has been a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb) localized primarily on the lungs and it has been one of the most successful pathogen in the history of mankind. Extensively arising drug resistivity in TB has made it a global challenge and need for new drugs has become utmost important.The involvement of Nucleoid-Associated Proteins (NAPs) in maintaining the structure of the genomic material and regulating various cellular processes like transcription, DNA replication, repair and recombination makes significant, has opened a new arena to find the drugs targeting Mtb. The current study aims to identify potential inhibitors of NAPs through a computational approach. In the present work we worked on the eight NAPs of Mtb, namely, Lsr2, EspR, HupB, HNS, NapA, mIHF and NapM. The structural modelling and analysis of these NAPs were carried out. Moreover, molecular interaction were checked and binding energy was identified for 2500 FDA-approved drugs that were selected for antagonist analysis to choose novel inhibitors targeting NAPs of Mtb. Drugs including Amikacin, streptomycin, kanamycin, and isoniazid along with eight FDA-approved molecules that were found to be potential novel targets for these mycobacterial NAPs and have an impact on their functions. The potentiality of several anti-tubercular drugs as therapeutic agents identified through computational modelling and simulation unlocks a new gateway for accomplishing the goal to treat TB.

Brain organoids are new tool for drug screening of neurological diseases

At the level of in vitro drug screening, the development of a phenotypic analysis system with high-content screening at the core provides a strong platform to support high-throughput drug screening. There are few systematic reports on brain organoids, as a new three-dimensional in vitro model, in terms of model stability, key phenotypic fingerprint, and drug screening schemes, and particularly regarding the development of screening strategies for massive numbers of traditional Chinese medicine monomers. This paper reviews the development of brain organoids and the advantages of brain organoids over induced neurons or cells in simulated diseases. The paper also highlights the prospects from model stability, induction criteria of brain organoids, and the screening schemes of brain organoids based on the characteristics of brain organoids and the application and development of a high-content screening system.

Prevalence of bovine coronavirus in cattle in China: A systematic review and meta-analysis

Bovine coronavirus (BCoV) is one of the important pathogens that cause calf diarrhea (CD), winter dysentery (WD), and the bovine respiratory disease complex (BRDC), and spreads worldwide. An infection of BCoV in cattle can lead to death of young animals, stunted growth, reduced milk production, and milk quality, thus bringing serious economic losses to the bovine industry. Therefore, it is necessary to prevent and control the spread of BCoV. Here, a systematic review and meta-analysis was conducted to assess the prevalence of BCoV in cattle in China before 2022. A total of 57 articles regarding the prevalence of BCoV in cattle in China were collected from five databases (PubMed, ScienceDirect, CNKI, VIP, and Wan Fang). Based on the inclusion criteria, a total of 15,838 samples were included, and 6,136 were positive cases. The overall prevalence of BCoV was 30.8%, with the highest prevalence rate (60.5%) identified in South China and the lowest prevalence (15.6%) identified in Central China. We also analyzed other subgroup information, included sampling years, sample sources, detection methods, breeding methods, age, type of cattle, presence of diarrhea, and geographic and climatic factors. The results indicated that BCoV was widely prevalent in China. Among all subgroups, the sample sources, detection methods, breeding methods, and presence or absence of diarrheal might be potential risk factors responsible for BCoV prevalence. It is recommended to strengthen the detection of BCoV in cattle, in order to effectively control the spread of BCoV.

Multi-Omics-Guided Discovery of Omicsynins Produced by Streptomyces sp. 1647: Pseudo-Tetrapeptides Active Against Influenza A Viruses and Coronavirus HCoV-229E

Many microorganisms have mechanisms that protect cells against attack from viruses. The fermentation components of Streptomyces sp. 1647 exhibit potent anti-influenza A virus (IAV) activity. This strain was isolated from soil in southern China in the 1970s, but the chemical nature of its antiviral substance(s) has remained unknown until now. We used an integrated multi-omics strategy to identify the antiviral agents from this streptomycete. The antibiotics and Secondary Metabolite Analysis Shell (antiSMASH) analysis of its genome sequence revealed 38 biosynthetic gene clusters (BGCs) for secondary metabolites, and the target BGCs possibly responsible for the production of antiviral components were narrowed down to three BGCs by bioactivity-guided comparative transcriptomics analysis. Through bioinformatics analysis and genetic manipulation of the regulators and a biosynthetic gene, cluster 36 was identified as the BGC responsible for the biosynthesis of the antiviral compounds. Bioactivity-based molecular networking analysis of mass spectrometric data from different recombinant strains illustrated that the antiviral compounds were a class of structural analogues. Finally, 18 pseudo-tetrapeptides with an internal ureido linkage, omicsynins A1-A6, B1-B6, and C1-C6, were identified and/or isolated from fermentation broth. Among them, 11 compounds (omicsynins A1, A2, A6, B1-B3, B5, B6, C1, C2, and C6) are new compounds. Omicsynins B1-B4 exhibited potent antiviral activity against IAV with the 50% inhibitory concentration (IC₅₀) of approximately 1 µmol∙L^-1 and a selectivity index (SI) ranging from 100 to 300. Omicsynins B1-B4 also showed significant antiviral activity against human coronavirus HCoV-229E. By integrating multi-omics data, we discovered a number of novel antiviral pseudo-tetrapeptides produced by Streptomyces sp. 1647, indicating that the secondary metabolites of microorganisms are a valuable source of novel antivirals.

A Discovery Strategy for Active Compounds of Chinese Medicine Based on the Prediction Model of Compound-Disease Relationship

An accurate characterization of diseases and compounds is the key to predicting the compound-disease relationship (CDR). However, due to the difficulty of a comprehensive description of CDR, the accuracy of traditional drug development models for large-scale CDR prediction is usually unsatisfactory. In order to solve this problem, we propose a new method that integrates the molecular descriptors of compounds and the symptom descriptors of diseases to build a CDR two-dimensional matrix to predict candidate active compounds. The Matlab software draws grayscale images of CDRs, which are used as a benchmark dataset for training convolutional neural network (CNN) models. The trained model is used to predict candidate antitumor active compounds. Among the AlexNet and GoogLeNet models, we selected the GoogLeNet model for the prediction of active compounds in Chinese medicine, and its Acc, Sen, Pre, F-measure, MCC, and AUC are 0.960, 0.956, 0.965, 0.960, 0.920, and 0.964, respectively. In the prediction results of compounds, 1624 candidate CDRs were found in 124 Chinese medicines. Among them, we obtained 31 features of candidate antitumor active compounds. This method provides new insights for the discovery of candidate active compounds in Chinese medicine.

A Novel Chinese Herbal and Corresponding Chemical Formula for Cancer Treatment by Targeting Tumor Maintenance, Progression, and Metastasis

We characterized a so-called "heirloom recipe" Chinese herbal formula (temporarily named Formula X) that contains five Chinese medical botanical drugs, Huang-Lian (Coptis chinensis Franch. [Ranunculaceae]), Huang-Qin (Scutellaria baicalensis Georgi [Lamiaceae]), Bai-Wei (Vincetoxicum atratum (Bunge) C. Morren and Decne. [Apocynaceae]), E-Zhu (Curcuma aromatica Salisb. [Zingiberaceae]) and Bai-Zhu (Atractylodes macrocephala Koidz. [Asteraceae]). Formula X inhibited the growth of various cancer cells and decreased the expression levels of a panel of proteins, including CD133, Myc, PD-L1, and Slug, in cancer cells. We further found that the inhibition of growth and protein expression were exerted by Huang-Lian, Huang-Qin, and Bai-Wei (formula HHB), which exhibited the same biological effects as those of Formula X. Furthermore, we selected three active chemicals, berberine, baicalin, and saponin from Huang-Lian, Huang-Qin, and Bai-Wei, respectively, to produce a chemical formulation (formula BBS), which exhibited similar effects on cell growth and protein expression as those induced by formula HHB. Both the formulae HHB and BBS suppressed tumor growth in an animal study. Moreover, they decreased the protein levels of Myc and PD-L1 in tumor cells in vivo. In summary, we established a novel Chinese herbal formula and a chemical formula that targeted three important processes, tumor maintenance (tumor stem cells), progression, and metastasis, and that influenced the response of tumors to host immunosuppression, for the potentially effective treatment of cancer patients.

Future Directions for the Discovery of Natural Product-Derived Immunomodulating Drugs

Drug discovery from natural sources is going through a renaissance, having spent many decades in the shadow of synthetic molecule drug discovery, despite the fact that natural product-derived compounds occupy a much greater chemical space than those created through synthetic chemistry methods. With this new era comes new possibilities, not least the novel targets that have emerged in recent times and the development of state-of-the-art technologies that can be applied to drug discovery from natural sources. Although progress has been made with some immunomodulating drugs, there remains a pressing need for new agents that can be used to treat the wide variety of conditions that arise from disruption, or over-activation, of the immune system; natural products may therefore be key in filling this gap. Recognising that, at present, there is no authoritative article that details the current state-of-the-art of the immunomodulatory activity of natural products, this in-depth review has arisen from a joint effort between the International Union of Basic and Clinical Pharmacology (IUPHAR) Natural Products and Immunopharmacology, with contributions from a Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation number of world-leading researchers in the field of natural product drug discovery, to provide a "position statement" on what natural products has to offer in the search for new immunomodulatory argents. To this end, we provide a historical look at previous discoveries of naturally occurring immunomodulators, present a picture of the current status of the field and provide insight into the future opportunities and challenges for the discovery of new drugs to treat immune-related diseases.

Multi-parametric cellular imaging coupled with multi-component quantitative profiling for screening of hepatotoxic equivalent markers from Psoraleae Fructus

BACKGROUND

The hepatotoxicity of Chinese herbal medicine (CHM) is an important reason for its restrictive application. Psoraleae Fructus (PF), a commonly used CHM for treatment of osteoporosis and vitiligo etc., has caused serious concern due to the frequent occurrence of liver injury incidents. To date, its hepatotoxic equivalent markers (HEMs) and potential mechanisms are still unclear.

PURPOSE

To discover and validate the HEMs of PF and further explore the potential mechanisms of hepatotoxicity.

METHODS

Multi-parametric cellular imaging was performed by high content screening, and multi-component quantitative profiling was conducted by ultra-high performance liquid chromatography coupled with triple-quadrupole mass spectrometry. The correlations between hepatotoxic features and component contents were modeled by chemometrics including partial least square regression, back propagation-artificial neural network, and hierarchical cluster analysis. Then the candidate HEMs of PF were screened out and subjected to hepatotoxic equivalence assessment in primary hepatocytes, zebrafish, and mice, and the hepatotoxic mechanisms of PF were investigated.

RESULTS

The chemical combination of psoralen and isopsoralen was discovered as the HEMs of PF through pre-screening and verifying process. PF was demonstrated to induce oxidative stress, mitochondrial dysfunction and cellular apoptosis.

CONCLUSIONS

This study not only provides a rational strategy for screening HEMs from CHMs like PF, but also contributes to understanding the underlying mechanisms of PF hepatotoxicity.

Quantitative Confocal Microscopy for Grouping of Dose-Response Data: Deciphering Calcium Sequestration and Subsequent Cell Death in the Presence of Excess Norepinephrine

Fluorescent calcium (Ca²⁺) imaging is one of the preferred methods to record cellular activity during in vitro preclinical studies, high-content drug screening, and toxicity analysis. Visualization and analysis for dose-response data obtained using high-resolution imaging remain challenging, due to the inherent heterogeneity present in the Ca²⁺ spiking. To address this challenge, we propose measurement of cytosolic Ca²⁺ ions using spinning-disk confocal microscopy and machine learning-based analytics that is scalable. First, we implemented uniform manifold approximation and projection (UMAP) for visualizing the multivariate time-series dataset in the two-dimensional (2D) plane using Python. The dataset was obtained through live imaging experiments with norepinephrine-induced Ca²⁺ oscillation in HeLa cells for a large range of doses. Second, we demonstrate that the proposed framework can be used to depict the grouping of the spiking pattern for lower and higher drug doses. To the best of our knowledge, this is the first attempt at UMAP visualization of the time-series dose response and identification of the Ca²⁺ signature during lytic death. Such quantitative microscopy can be used as a component of a high-throughput data analysis workflow for toxicity analysis.

Traditional Chinese Medicine Intervenes in Vascular Dementia: Traditional Medicine Brings New Expectations

Vascular dementia (VD) is one of the most common forms of dementia, referring to a group of symptoms that mainly manifest as advanced neurocognitive dysfunction induced by cerebrovascular disease (CVD). A significant number of studies have shown that traditional Chinese medicine (TCM) has a clinical impact on VD and thus has promising prospects. There have been many discussions regarding the pharmacological mechanisms involved in treatment of the kidney, elimination of turbidity, and promotion of blood circulation. TCM has a prominent effect on improving patients' cognitive function and quality of life. In this review, we summarize the pathogenesis of VD in modern medicine and TCM, traditional prescriptions, single-agent effective ingredients and their pharmacological mechanisms for treating VD, highlight TCM's characteristics, and discuss TCM's multi-targeted mechanism for the treatment of VD.

Dimeric guaianes from leaves of Xylopia vielana as snail inhibitors identified by high content screening

The transcriptional repressor Snail trriggers epithelial-mesenchymal transition (EMT), the process allowing cancer cells with invasive and metastasis properties. In this study, we screened medicinal plants for the Snail inhibitory active components by high content screen (HCS) and found that the crude extract of Xylopia vielana leaves showed potential activity. Subsequently, bioassay-guided isolation of the extract of Xylopia vielana was performed to obtain twenty-four dimeric guaianes (1-24), including 16 new analogues (1-5, 8-11, 13-15, 17, 18, 21, and 22). Their structures were elucidated by the comprehensive application of multiple spectroscopic methods. Compounds 1, 11, 12, and 16 were initially identified as the active compounds. Wound healing assay, transwell migration assay and western blot experiments verified that compounds 1 and 12 inhibited the expression of Snail in a concentration-dependent manner, and compound 12 was verified as a potent tumor migration inhibitory agent. This work showed a practical strategy for the discovery of new Snail inhibitors from natural products and provided potential insights for dimeric guaianes as anticancer lead compounds specifically targeting Snail protein.

A comprehensive application: Molecular docking and network pharmacology for the prediction of bioactive constituents and elucidation of mechanisms of action in component-based Chinese medicine

Traditional Chinese medicine (TCM) has been used for more than 2000 years in China. TCM has received wide attention recently due to its unique charm. At the same time, its main obstacles have attracted wide attention, including vagueness of drug composition and treatment mechanism. With the development of virtual screening technology, more and more Chinese medicine compounds have been studied to discover the potential active components and mechanisms of action. Molecular docking is a computer technology based on structural design. Network pharmacology establishes powerful and comprehensive databases to understand the relationship between TCM and disease network. In this review, emergent uses and applications of two techniques and further superiorities of the two techniques when embarked to boil down into a tidy system were illustrated. A combination of the two provides a theoretical basis and technical support for the construction of modern TCM based on the compatibility of components and accelerates the realization of two basic elements as well, including the clearness of the pharmacodynamic substances and explanation of the effect of TCM.

Recent advances in screening active components from natural products based on bioaffinity techniques

Natural products have provided numerous lead compounds for drug discovery. However, the traditional analytical methods cannot detect most of these active components, especially at their usual low concentrations, from complex natural products. Herein, we reviewed the recent technological advances (2015–2019) related to the separation and screening bioactive components from natural resources, especially the emerging screening methods based on the bioaffinity techniques, including biological chromatography, affinity electrophoresis, affinity mass spectroscopy, and the latest magnetic and optical methods. These screening methods are uniquely advanced compared to other traditional methods, and they can fish out the active components from complex natural products because of the affinity between target and components, without tedious separation works. Therefore, these new tools can reduce the time and cost of the drug discovery process and accelerate the development of more effective and better-targeted therapeutic agents.

Zebrafish-Based Screening of Antiseizure Plants Used in Traditional Chinese Medicine: Magnolia officinalis Extract and Its Constituents Magnolol and Honokiol Exhibit Potent Anticonvulsant Activity in a Therapy-Resistant Epilepsy Model

With the aim to discover interesting lead compounds that could be further developed into compounds active against pharmacoresistant epilepsies, we first collected 14 medicinal plants used in traditional Chinese medicine (TCM) against epilepsy. Of the six extracts that tested positive in a pentylenetetrazole (PTZ) behavioral zebrafish model, only the ethanol and acetone extracts from Magnolia officinalis (M. officinalis) also showed effective antiseizure activity in the ethylketopentenoate (EKP) zebrafish model. The EKP model is regarded as an interesting discovery platform to find mechanistically novel antiseizure drugs, as it responds poorly to a large number of marketed anti-epileptics. We then demonstrated that magnolol and honokiol, two major constituents of M. officinalis, displayed an effective behavioral and electrophysiological antiseizure activity in both the PTZ and the EKP models. Out of six structural analogues tested, only 4-O-methylhonokiol was active and to a lesser extent tetrahydromagnolol, whereas the other analogues (3,3'-dimethylbiphenyl, 2,2'-biphenol, 2-phenylphenol, and 3,3',5,5'-tetra-tert-butyl-[1,1'-biphenyl]-2,2'-diol) were not consistently active in the aforementioned assays. Finally, magnolol was also active in the 6 Hz psychomotor mouse model, an acute therapy-resistant rodent model, thereby confirming the translation of the findings from zebrafish larvae to mice in the field of epilepsy. We also developed a fast and automated power spectral density (PSD) analysis of local field potential (LFP) recordings. The PSD results are in agreement with the visual analysis of LFP recordings using Clampfit software and manually counting the epileptiform events. Taken together, screening extracts of single plants employed in TCM, using a combination of zebrafish- and mouse-based assays, allowed us to identify allyl biphenol as a chemical scaffold for the future development of compounds with potential activity against therapy-resistant epilepsies.