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High content screening for drug discovery from traditional Chinese medicine
Chinese Medicine volume 14, Article number: 5 (2019)
Traditional Chinese medicine (TCM) represents the crystallization of Chinese wisdom and civilization. It has been valued as the renewable source for the discovery of novel drugs, owing to its long-term proved efficacy in human diseases and abundant biologically active components pools. To dissect the mystery of TCM, modern technologies such as omics approaches (proteomics, genomics, metabolomics) and drug screening technologies (high through-put screening, high content screening and virtual screening) have been widely applied to either identify the drug target of TCM or identify the active component with certain bio-activity. The advent of high content screening technology has absolutely contributed to a breakthrough in compounds discovery and influenced the evolution of technology in screening field. The review introduces the concept and principle of high content screening, lists and compares the currently used HCS instruments, and summarizes the examples from ours and others research work which applied HCS in TCM-derived compounds screening. Meanwhile, this article also discusses the advantages and limitations of HSC technology in drug discovery from TCM libraries.
The advancement of optical instruments greatly accelerated the process of modern biology and the drug discovery industry . Fluorescence microscopy emerged as a robust tool substituted for conventional optical equipment, which can analyze spatiotemporal information in biology to uncover the mysterious veils of cellular events . Simultaneously, the development of molecular biology system attributes to the rapid growth of biological probes and fluorophores. After the image acquisition, thousands of figures are scanned to analyze quickly by computational software. Compared with manual screening technique, automatic screening platform avoided the assay artifacts and subjective biases on effective targets to achieve more accurate experiment results. Moreover, the automated drug screening platform saved manpower and resources, and increased the speed and scale of drug screening, which greatly accelerated the drug discovery process. In the early stage of the drug discovery, high throughput screening (HTS) system was extensively used in searching for hit compound for its high-efficiency, high-speed and quantitative characteristics. However, the single-target identification approach sometimes could not meet the need for comprehensive evaluation of compound activity in such a huge compound libraries generated by TCM or chemical synthesis . HCS as a multiple dimension approach, displayed unique strength both in target-based and phenotypic-based screening for drug discovery.
Principle of high content screening
The concept of the high content screening was first proposed in 1997, when it was regarded as a powerful approach to break the bottlenecks in drug discovery . Identifying a hit compound from a large number of compounds libraries requiring the robotic instruments and automatic analysis. Characteristics of high content screening meet the request at the following aspects. First, the establishment of multiple parameters and targets analysis platforms can extract unbiased information on cellular function and morphology at the same time, such as cell shape, growth, differentiation, translocation, apoptosis and metabolism . Second, investigators acquire spatial and temporal information on cellular events in vitro. In this way, researchers can mimic in vivo conditions to evaluate effective treatments on intricate diseases. Third, the robust approach provides more insights into mitochondria, lysosome and nucleus activity to study the subcellular biological events. Finally, lead compound validation by automated imaging analysis and data algorithms made HCS easier to be extensively applied. Above mentioned characteristics of HSC make it widely used by researchers all over the world for the identification the active lead compound .
State-of-the-art progress in HCS technology
Hitherto, numerous high technologies and assays were established to improve the high-content imaging system in the biological field. Diversity of instruments were invented for devising complete experiments and acquiring multiple data analysis. Nowadays, multi-channel detectors have been widely used in imaging analysis systems, enabling the simultaneous analysis of multidimensional targets and phenotypes. Accordingly, several software packages have been implanted to optimize the experiment operation for screening. Meanwhile, Open-source image analysis software has been continuously developed for HCS image-analysis to acquire information in spatial and temporal dimensions , including both quantitative and qualitative assays . These softwares aimed at analyzing specific imaging problems and providing user-friendly operation, can be extensively used in HCS equipment such as cell cognition , ImageJ/Fiji , and EBImage . 3D tissue culture model is a novel technology in biology that researchers acquired tridimensional phenotypes of cells by confocal microscopes . 3D culture assay is an ideal tool to explore cancers, specific organs from stem cells, circulatory and nervous system diseases between monolayer cell culture with animal experiment. Associated with a large number of confocal HCS platforms, the 3D model system attempted to act as a new approach in drug discovery pipeline. 3D culture instruments including the PerkinElmer Opera which contained a spinning disk confocal microscope, the ImageJ Suite combined with an R tool , and 3D Object Counter by Fabrice P. Cordelieres  have been applied in the drug screening on 3D culture-based models.
The application of HCS technology in biological field or pharmaceutical industry firmly bounded to the improvements of hardware, especially in microscopic imaging system and image-analysis software . To a certain extent, both advanced imaging technology and data analysis software caused further development of HCS approaches. These two aspects, as a breakthrough in the exploration and improvement of HCS, make drug screening technology develop rapidly. Over the past 20 years, tremendous changes have taken place in automated microscopes. The adequate resolution and magnification are necessary to capture subcellular structures and phenotypes which reflect the cell events. With the progress of microscope technology and automated imaging system, HCS technology evolved rapidly. It become easier for researchers to get a better overview of cellular phenotypes in organisms, and to identify the hit compounds from the huge compounds library .
Currently, advancement of microscopic technology expanded the range of automated screening for visual phenotypes . Improvements in stable light source and fast autofocus spelt the growth of microscopy techniques. In addition to this, the process in fluorescent probes and novel fluorescent proteins also contributed to expanding the visual phenotypes . Fluorescent labeling assay can be employed to visualize the complicated physiological activity of cells in image-based screening. Fluorescent dyes, fluorescent probes, genetically encoded fluorescent proteins and antibodies allowed direct monitoring of cellular phenotypes under complex conditions through staining cells . Changes in image-based approaches and reliable software workflow facilitate to extract multiple parameters or quantitative information from images. Both robotic microscopy imaging technique and advanced computational analysis software were the rudimentary components of HCS technology. HCS technology combined these two aspects in automated experiment process and avoided of time consuming or uncertainty by human. Under the development of experimental technology, the classification of instruments in HCS has changed with fantastic progress. Currently, HCS detector can be segregated into three categories: high-content of wide field fluorescence microscopy, high-content of confocal fluorescence microscopy, and integration of above two. The current HCS instruments have concluded as follows (Table 1).
HCS applications in drug discovery
High content screening is a technology that combined automated fluorescence microscopy with automated image analysis to track the cellular morphology and intracellular parameters. As a contemporary technology, it differs from the traditional cell-based methods, because it can analyze multiple cell parameters and thousands of individual cells simultaneously (Fig. 1).
Drug target validation has been taken into account to be a pivotal procedure in drug discovery owing to know target points lead the way of discovering novel drugs. Identifying the target point facilitate to have a specific pharmacological mechanism and decide whether the drug screening will be a success. Historically, hundreds of drug targets have been determined, such as a receptor, enzyme, ion channel and nucleic acid . Although the research of drug targets made an enormous progress, there are still unexploited fields need further exploring. In the past years, scientists spared their efforts to study the mechanism of incurable disease, such as cancer or neurodegenerative diseases. However, the lack of effective drug target largely impedes the development of efficient therapies though target-therapy displayed success in certain cancer types. Despite the technologies and approaches have improved a lot, the bottleneck of target identification still existed in such an intricate biological system . The costly and time-consuming target validation required elucidating the protein how to act on specific signaling pathway or process of disease . Overall, identifying the direct target of the compound with advanced screening technique accelerated the process of new drug discovery. How to apply biological assays to novel drug research or how to search for new effective assays on target validation is no doubt a grand challenge in the field of drug devised.
Application of HCS for drug discovery from traditional Chinese medicine
Over the past two decades, traditional Chinese medicine (TCM) has been considered to be a rich source of hit compound for drug development against the diversity of drug target validation. Hitherto, more than half of various drugs certified by FDA are derived from the natural source . TCM and its derivatives had a profound effect on the treatment of the disease because of the diversity of biological activities .
Along with the improvement of high techniques, there were countless numbers of compounds have been isolated from TCM. Hence, it has become increasing difficult to identify completely new compounds with high bioactivity. Rediscovery is an unavoidable and necessary issue but it takes time and money . Therefore, researchers were supposed to devise more efficient experimental assays and simultaneously enhance the screening technologies to identify the valued compound as a novel therapeutic agent. Besides the discovery, the isolation or purification of TCM was similarly a difficulty to defeat . There are a myriad of components exist in TCM, how to isolate single compound, especially with low concentration, from complex compound libraries by chemical separation is still a conundrum . Another intractable problem was how to purify the extract, and it also magnified the difficulties in drug discovery from TCM. In order to solve above issues, effective analytical method should be drawn up and improved to facilitate the drug discovery from TCM successfully.
Traditional Chinese medicine has historically become a rich source of discoverying novel drugs. Since high-content screening technology emerged as a robust tool in drug screening, the development of drug discovery from TCM has improved a lot. Efforts to search for therapeutic agents from TCM libraries have constantly continued in the past years. Researchers discovered some innovative drugs from large libraries with HCS approach to treat complex diseases. At present, more and more research institutions have applied HCS technology in the study of traditional Chinese medicines. HCS can not only clarify the interaction between the sieved samples and the drug targets, but also make it possible to understand other biological changes in the cell, predict the toxicity of the compound and investigate related metabolic pathways by observing the morphology of the cells, which are of great significance for promoting the modernization of traditional Chinese medicine. Recently, we have applied HCS technique in the discovery of autophagy regulator from traditional Chinese medicine for the therapeutic invention in the cancer and neurodegenerative disease models. Our studies demonstrate that the HCS technique is highly efficient and reliable for the identification of autophagy regulators. For example, Corynoxine B , Corynoxine  and curcumin analog C1 were identified as autophagy inducers while dauricine and daurisoline were identified as autophagy inhibitors .
There is an increasing number of studies applying HCS technique in the identification and pharmacological analysis of TCM-derived reagents. A comprehensive summarization of these studies is list in Table 2. Among the studies, the HCS has been used to identify therapeutic compounds for a wide range of human diseases including: cancer, neurodegenerative disease, neurotoxicity, osteoporosis, liver injury, liver fibrosis and inflammation. When analyzing the screening models, multiple cellular and molecular processes have been utilized in the screening as shown in Table 2. Several models mentioned in the table are extremely suitable for the HCS and we conclude here: (1) nuclear translocation of transcript factors: some transcript factors translocate to nuclear to initiate the gene transcription for down-stream cellular events thus the nuclear translocation of transcript factors can be used as a marker for transcription activation. Nuclear translocation of eIF4E, NFATc1, β-catenin, NF-κB and TEFB have been use as the readout for the identification of anti-cancer, anti-inflammation and neuroprotective compounds; (2) Morphological change of cells: Cell morphology changes are important marker of cell activation status, cell viability, cell growth and cell destiny. In the studies, the microtubules network, the outgrowth of neurites of neuronal cells and nuclei morphology have been monitored to evaluate the anti-tumor and neuroprotective properties of candidate compounds; (3) the function and distribution pattern of organelles: intracellular organelles play vital role in the cell survival and proliferation. The membrane potential of mitochondria and the distribution pattern of lysosomes have been used as markers for anti-cancer property evaluation of candidate compounds; (4) autophagosome formation: autophagy is a highly conserved cellular degradation process involved in neurodegenerative diseases and cancer. The formation of autophagosome has been widely used as marker for identification of autophagy regulators. In the listed studies, the autophagy inhibitors and inducers have been identified for the anti-cancer purpose and neuroprotective purpose. These successful examples strongly support the strength of HCS in the TCM research.
In the past two decades, movements forward in instruments and software made the HCS become the powerful technique in drug discovery. HCS has in fact applied to identify drug candidates at various stages of the drug discovery pipeline: target validation, primary screening, candidate optimization and in vitro toxicology. It is undeniable that applying HCS to drug discovery from TCM facilitated the leading compounds identification, as well as the pharmacological study on the TCM. The application of the HCS elucidated the mechanisms, features and target points in individual cells or organisms and provided more insights into biological processes.
Although HCS technology improved a lot, scientists still have challenges on copious amounts of data analysis . Thus, HCS dataset enable researchers to develop automated and advanced machine to quantify multiple cellular events or genetic information. When open source software gradually became more widespread, the analysis of HCS images seems to be more convenient and accurate. In addition, 3D tissue culture also has obstacles to surmount that 3D image processing software had difficulties in complicated 3D animal models. Along with the continuous progress of biotechnology, high-content screening will take a deeper optimization and become more authoritative and widespread. Though the robust assay was too overwhelming to handle a lot of barriers people met before, it is expected that future improvements in experimental approaches and computational instruments would add value to HCS in the future.
Traditional Chinese medicine contains thousands of compounds which regulate cellular function as a combination of multiple pharmacological activities, thus making it very challenging to understand the exact mechanism of drug activity. HCS provides a new technical means for studying Chinese medicine as a whole rather than as the isolated compounds, which better meet the complex factors of traditional Chinese medicine research and is in according with clinic use of TCM. Specifically, HCS has the following advantages for traditional Chinese medicine research: First, HCS can be used to study the function of cells as a whole, making the results more comprehensive and objective. Secondly, HCS can be used to screen multiple components of traditional Chinese medicine to find active components or components. Thirdly, HCS can help the exploration of the mechanism of traditional Chinese medicine from multiple levels and multiple targets, which are easily missed during traditional highly specific single-target screening. However, the difficulties of the application of HCS on TCM comparing to the pure chemical compounds are also obvious: (1) different compounds in TCM may compete with each other on the signaling pathways (inhibition or activation of same signaling pathway) or targets (agonist or antagonist) so as to mask the potential activity; (2) when a desired pharmacological activity were identified, it is difficult to figure out which compound is responsible that activity. Recent advance in the chemical biology and high-resolution separation science to fish the specific compound from the TCM pool use purified protein as bait is one of the solution for these difficulties. Moreover, the rapid development of “omics” approaches and pharmacological network analysis tool are making the attempt of deciphering the mystery of TCM much easier.
HCS technology has been extensively invoked as a powerful tool for a rapid explosion in resolution and data processing both in the pharmaceutical industry or biological field. Traditional Chinese medicine has been valued as a rich source for drug discovery because of the well documented therapeutic efficacies since ancient time. However, lack of knowledge on the pharmacology mechanism and drug targets limited the further development of TCM. Applying the HCS technique will narrow the gap between therapeutic potential and molecular mechanism, thus strengthen the process for drug discovery from TCM.
traditional Chinese medicine
high content screening
high throughput screening
Korn K, Krausz E. Cell-based high-content screening of small-molecule libraries. Curr Opin Chem Biol. 2007;11(5):503–10.
Zanella F, Lorens JB, Link W. High content screening: seeing is believing. Trends Biotechnol. 2010;28(5):237–45.
Dove A. Screening for content—the evolution of high throughput. Nat Biotechnol. 2003;21(8):859–64.
Giuliano KA, Debiasio RL, Dunlay RT, Gough A, Volosky JM, Zock J, Pavlakis GN, Taylor DL. High-content screening: a new approach to easing key bottlenecks in the drug discovery process. J Biomol Screen. 1997;2(4):249–59.
Rabal O, Link W, Serelde BG, Bischoff JR, Oyarzabal J. An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries. Mol BioSyst. 2010;6(4):711–20.
Marc Bickle. The beautiful cell: high-content screening in drug discovery. Anal Bioanal Chem. 2010;398(1):219–26.
Prodanov D. Open source image analysis software toolboxes for microscopic applications. Front Neuroinf. 2013. https://doi.org/10.3389/conf.fninf.2013.10.00005.
Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin DA, Chang JH, Lindquist RA, Moffat J, Golland P, Sabatini DM. Cell Profiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 2006;7(10):R100.
Held M, Schmitz MH, Fischer B, Walter T, Neumann B, Olma MH, Peter M, Ellenberg Jand Gerlich DW. Cell Cognition: time-resolved phenotype annotation in high-throughput live cell imaging. Nat Methods. 2010;7(9):747–54.
Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld SSB. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9(7):676–82.
Pau G, Fuchs F, Sklyar O, Boutros M, Huber W. EBImage—an R package for image processing with applications to cellular phenotypes. Bioinformatics. 2010;26(7):979–81.
Kriston-Vizi J, Flotow H. Getting the whole picture: high content screening using three-dimensional cellular model systems and whole animal assays. Cytom Part A. 2016;91(2):152–9.
Ollion J, Cochennec J, Loll F, Escude C, Boudier T. TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization. Bioinformatics. 2013;29(14):1840–1.
Bolte S, Cordelières FP. A guided tour into subcellular colocalization analysis in light microscopy. J Microsc. 2006;224(Pt 3):213–32.
Wang MM, Ling HE, Mei HU, Zhao C. The development of high-content screening technique and its application in pharmaceutical research. Prog Pharm Sci. 2011;7(6):767–83.
Lang P, Yeow K, Nichols A, Scheer A. Cellular imaging in drug discovery. Nat Rev Drug Discov. 2006;5(4):343–56.
Boutros M, Heigwer F, Laufer C. Microscopy-based high-content screening. Cell. 2015;163(6):1314–25.
Eliceiri KW, Berthold MR, Goldberg IG, Ibáñez L, Manjunath BS, Martone ME, Murphy RF, Peng H, Plant AL, Roysam B. Biological imaging software tools. Nat Methods. 2012;9(7):697–710.
Kiger AA, Baum B, Jones S, Jones MR, Coulson A, Echeverri C, Perrimon N. A functional genomic analysis of cell morphology using RNA interference. J Biol. 2003;2(4):1–15.
Terstappen GC, Schlüpen C, Raggiaschi R, Gaviraghi G. Target deconvolution strategies in drug discovery. Nat Rev Drug Discov. 2007;6(11):891–903.
Peng LF, Stanton BZ, Maloof N. Syntheses of aminoalcohol-derived macrocycles leading to a small-molecule binder to and inhibitor of Sonic Hedgehog. Bioorg Med Chem Lett. 2009;19(22):6319–25.
Wyatt Paul G. Target validation: linking target and chemical properties to desired product profile. Curr Top Med Chem. 2010;11(10):1275–83.
Schulze C, Bray W, Woerhmann M, Stuart J, Lokey R, Scottand LR. “Function-First” lead discovery: mode of action profiling of natural product libraries using image-based screening. Chem Biol. 2013;20(2):285–95.
Lin AX, Chan G, Hu Y, Ouyang D, Ung COL, Shi LHH. Internationalization of traditional Chinese medicine: current international market, internationalization challenges and prospective suggestions. Chin Med. 2018;13(1):9.
Kurita KL, Linington RG. Connecting phenotype and chemotype: high-content discovery strategies for natural products research. J Nat Prod. 2015;78(3):587–96.
Yulin Zhang, Chengwei Liang Yeerand He. Anticancer activities and mechanisms of heat-clearing and detoxicating traditional Chinese herbal medicine. Chinese medicine. 2017;12(1):20.
Koehn FE, Carter GT. The evolving role of natural products in drug discovery. Nat Rev Drug Discov. 2005;4(3):206–20.
Lu J-H, Tan J-Q, Durairajan SSK, Liu L-F, Zhang Z-H, Ma L, Shen H-M, Chan HY, Min EL. Isorhynchophylline, a natural alkaloid, promotes the degradation of alpha-synuclein in neuronal cells via inducing autophagy. Autophagy. 2012;8(1):98–108.
Chen LL, Song JX, Lu JH, Yuan ZW, Liu LF, Durairajan SS, Li M. Corynoxine, a natural autophagy enhancer, promotes the clearance of alpha-synuclein via Akt/mTOR pathway. J Neuroimmune Pharmacol. 2014;9(3):380–7.
Lu J-H, Ardah MT, Durairajan SSK, Liu L-F, Xie L-X, Fong W-F, Hasan MY, Huang J-D, El-Agnaf OM, Li M. Baicalein inhibits formation of α-synuclein oligomers within living cells and prevents Aβ peptide fibrillation and oligomerisation. ChemBioChem. 2011;12(4):615–24.
Yan J, Zhou H, Kong L, Zhang J, Zhao Q, Li Y. Identification of two novel inhibitors of mTOR signaling pathway based on high content screening. Cancer Chemother Pharmacol. 2013;72(4):799–808.
Zhang XW, Zhou C, Zhu HD, Shao W, You Y, Peng J, Yin S, Shen X. Inhibition of osteoclastogenesis by 6-[10′(Z)-heptadecenyl] salicylic acid from Syzygium tetragonum Wall via preventing nuclear translocation of NFATc1. Phytomedicine. 2014;21(7):960–5.
Xu D, Lao Y, Xu N, Hu H, Fu W, Tan H, Gu Y, Song Z, Cao P, Xu H. Identification and characterization of anticancer compounds targeting apoptosis and autophagy from Chinese native Garcinia species. Planta Med. 2014;81(1):79–89.
Ngoc Tran Tuyen Thi, Claas Gerding-Reimers, Beate Schölermann, Bettina Stanitzki, Thomas Henkel, Slava Waldmann Herbertand Ziegler. Podoverine A—a novel microtubule destabilizing natural product from the Podophyllum species. Bioorg Med Chem. 2014;22(18):5110–6.
Chen LH, Sun YT, Chen YF, Lee MY, Chang LY, Chang JY, Shen MR. Integrating image-based high-content screening with mouse models identifies 5-hydroxydecanoate as a neuroprotective drug for paclitaxel-induced neuropathy. Mol Cancer Ther. 2015;14(10):2206–14.
Kurita KL, Glassey E, Linington RG. Integration of high-content screening and untargeted metabolomics for comprehensive functional annotation of natural product libraries. Proc Natl Acad Sci. 2015;112(39):11999–2004.
Zou Y, Yang J, Jiang D. Resveratrol inhibits canonical Wnt signaling in human MG-63 osteosarcoma cells. Mol Med Rep. 2015;12(5):7221–6.
Circu ML, Dykes SS, Carroll J, Kelly K, Galiano F, Greer A, Cardelli J, El-Osta H. A novel high content imaging-based screen identifies the anti-helminthic niclosamide as an inhibitor of lysosome anterograde trafficking and prostate cancer cell invasion. PLoS ONE. 2016;11(1):e0146931.
Chen M, Du Y, Qui M, Wang M, Chen K, Huang Z, Jiang M, Xiong F, Chen J, Zhou J. Ophiopogonin B-induced autophagy in non-small cell lung cancer cells via inhibition of the PI3K/Akt signaling pathway. Oncol Rep. 2013;29(2):430–6.
Vogt A, Tamewitz A, Skoko J, Sikorski RP, Giuliano KA, Lazo JS. The benzo[c]phenanthridine alkaloid, sanguinarine, is a selective, cell-active inhibitor of mitogen-activated protein kinase phosphatase-1. J Biol Chem. 2005;280(19):19078–86.
Yan X, Zhou T, Tao Y, Wang Q, Liu P, Liu C. Salvianolic acid B attenuates hepatocyte apoptosis by regulating mediators in death receptor and mitochondrial pathways. Exp Biol Med. 2010;235(5):623–32.
Chong CM, Kou MT, Pan P, Zhou H, Ai N, Li C, Zhong HJ, Leung CH, Hou T, Lee SM. Discovery of a novel ROCK2 inhibitor with anti-migration effects via docking and high-content drug screening. Mol BioSyst. 2016;12(9):2713–21.
Yang T, Shen DP, Wang QL, Tao YY, Liu CH. Investigation of the absorbed and metabolized components of Danshen from Fuzheng Huayu recipe and study on the anti-hepatic fibrosis effects of these components. J Ethnopharmacol. 2013;148(2):691–700.
Bi L, Yan X, Chen W, Gao J, Qian L, Qiu S. Antihepatocellular carcinoma potential of tetramethylpyrazine induces cell cycle modulation and mitochondrial-dependent apoptosis: regulation of p53 signaling pathway in HepG2 cells in vitro. Integr Cancer Ther. 2016;15(2):226–36.
Wilson CJ, Si Y, Thompsons CM, Smellie A, Ashwell MA, Liu JF, Ye P, Yohannes D, Ng SC. Identification of a small molecule that induces mitotic arrest using a simplified high-content screening assay and data analysis method. J Biomol Screen. 2006;11(1):21–8.
Ahmadipour F, Noordin MI, Mohan S, Arya A, Paydar M, Looi CY, Keong YS, Siyamak EN, Fani S, Firoozi M, Yong CL. Koenimbin, a natural dietary compound of Murraya koenigii (L) Spreng: inhibition of MCF7 breast cancer cells and targeting of derived MCF7 breast cancer stem cells (CD44 +/CD24 −/low): an in vitro study. Drug Design Dev Ther. 2015;9:1193–208.
Hou L, Xu B, Guo W, Ran FX, Liu JT, Yuan X, Fu HZ, Cui JR. Pseudolaric acid B inhibits inducible cyclooxygenase-2 expression via downregulation of the NF-κB pathway in HT-29 cells. J Cancer Res Clin Oncol. 2012;138(5):885–96.
Cheah SC, Appleton DR, Lee ST, Lam ML, Hadi AH, Mustafa MR. Panduratin A inhibits the growth of A549 cells through induction of apoptosis and inhibition of NF-kappaB translocation. Molecules. 2011;16(3):2583–98.
Yi Wang, Xiaoping Zhao, Xiumei Gao, Xiaojing Nie, Xiaohui Yang Yingxinand Fan. Development of fluorescence imaging-based assay for screening cardioprotective compounds from medicinal plants. Anal Chim Acta. 2011;702(1):87–94.
Wu MY, Wang SF, Cai CZ, Tan JQ, Li M, Lu JJ, Chen XP, Wang YT, Zheng W, Lu JH. Natural autophagy blockers, dauricine (DAC) and daurisoline (DAS), sensitize cancer cells to camptothecin-induced toxicity. Oncotarget. 2017;8(44):77673.
Ju-Xian Song, Yue-Ru Sun, Ivana Peluso, Zeng Yu, Yu Xing Lu, Zheng Jia-Hong, Xu, Ming-Zhong Wang, Ying-Yu Liu Liang-Fengand Huang. A novel curcumin analog binds to and activates TFEB in vitro and in vivo independent of MTOR inhibition. Autophagy. 2016;12(8):1372–89.
Prisca Liberali, Lucas Snijder Berendand Pelkmans. Single-cell and multivariate approaches in genetic perturbation screens. Nat Rev Genet. 2015;16(1):18–32.
JW, JHL designed the study. JW drafted the manuscript. MYW, JQT, ML and JHL were major contributors in reviewing the manuscript. Based on the contributions, JW was listed as the first author while JHL was the correspondence. All authors read and approved the final manuscript.
We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.
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This study was supported by the Grants of China NSFC-31500831, Macau government grants FDCT-022/2015/A1, FDCT-092-2015-A3, and SKL-QRCM-2014-2016, and the University of Macau grant MYRG2016-0019-ICMS-QRCM, and the joint grant EF001/ICMS-LJH/2016/HKBU awarded to Jiahong Lu.
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Wang, J., Wu, MY., Tan, JQ. et al. High content screening for drug discovery from traditional Chinese medicine. Chin Med 14, 5 (2019). https://doi.org/10.1186/s13020-019-0228-y
- Drug discovery
- High-content screening
- Advanced models
- Progressive instruments
- Traditional Chinese medicine