Identification of baicalein as a ferroptosis inhibitor by natural product library screening

2016 ◽  
Vol 473 (4) ◽  
pp. 775-780 ◽  
Author(s):  
Yangchun Xie ◽  
Xinxin Song ◽  
Xiaofang Sun ◽  
Jin Huang ◽  
Meizuo Zhong ◽  
...  
Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
P Jiao ◽  
J Zhao ◽  
J Yeop Lee ◽  
J Tseng-Crank ◽  
B Corneliusen ◽  
...  

Planta Medica ◽  
2013 ◽  
Vol 79 (10) ◽  
Author(s):  
DB Divlianska ◽  
AE Wright ◽  
S Francis ◽  
MA Walters ◽  
CE Salomon ◽  
...  

Author(s):  
Saranyadevi Subburaj ◽  
Tanvi Anand Nagrale ◽  
Mohd. Mustufa Khan ◽  
Nivya James ◽  
Ramanathan Karuppasamy ◽  
...  

2012 ◽  
Vol 56 (6) ◽  
pp. 3399-3401 ◽  
Author(s):  
Kevin D. McCormick ◽  
Shufeng Liu ◽  
Jana L. Jacobs ◽  
Ernesto T. A. Marques ◽  
Nicolas Sluis-Cremer ◽  
...  

ABSTRACTWe have developed a robust cytopathic effect-based high-throughput screening assay to identify inhibitors of dengue virus (DENV) infection. Screening of a small natural product library yielded 11 hits. Four of these were found to be potent inhibitors of DENV, although serotype differences were noted. Taken together, these data suggest that screening of larger and more complex molecule libraries may result in the identification of more potent and specific DENV inhibitors.


2016 ◽  
Vol 79 (8) ◽  
pp. 1982-1989 ◽  
Author(s):  
Marie-Laure Vial ◽  
Dusan Zencak ◽  
Tanja Grkovic ◽  
Alain-Dominique Gorse ◽  
Alan Mackay-Sim ◽  
...  

2017 ◽  
Author(s):  
Eric J Buenz

Natural product libraries are important tools for drug discovery. However, until now, there has not been a system to allow projections of the potential number of hits from creating these libraries. The objective of this study was to develop a stochastic model system that predicts the number of hits from creating a natural product library. A Monte Carlo simulation was developed with data from the peer-reviewed literature. Using types of endemic New Zealand terrestrial flora as examples, the number of antibacterial hits expected from creating natural product libraries were calculated. The model predicts the following bounds for the 90% range of validated antibiotic leads for the categories of the terrestrial endemic flora of New Zealand with a right skewed distribution: [grasses: 1.43-6.50; liverworts: 2.75-12.5; fungi: 45.2-207; mosses: 0.98-4.48; vascular plants: 21.4-97.8]. Furthermore, per full-time equivalent (FTE) person employed on the project, a mean of 1.31 hits (90% range 0.48-2.42) is expected. This model system allows the number of expected hits to be calculated when developing a natural product library for a therapeutic target. There is an opportunity to create a natural product library from New Zealand endemic terrestrial flora. This model is scalable to other geographic areas as well as to other therapeutic targets and screening systems.


2020 ◽  
Author(s):  
R.P. Vivek-Ananth ◽  
Ajaya Kumar Sahoo ◽  
Kavyaa Kumaravel ◽  
Karthikeyan Mohanraj ◽  
Areejit Samal

AbstractFungi are a rich source of secondary metabolites which constitutes a valuable and diverse chemical space of natural products. Medicinal fungi have been used in traditional medicine to treat human ailments for centuries. To date, there is no devoted resource on secondary metabolites and therapeutic uses of medicinal fungi. Such a dedicated resource compiling dispersed information on medicinal fungi across published literature will facilitate ongoing efforts towards natural product based drug discovery. Here, we present the first comprehensive manually curated database on Medicinal Fungi Secondary metabolites And Therapeutics (MeFSAT) that compiles information on 184 medicinal fungi, 1830 secondary metabolites and 149 therapeutics uses. Importantly, MeFSAT contains a non-redundant in silico natural product library of 1830 secondary metabolites along with information on their chemical structures, computed physicochemical properties, drug-likeness properties, predicted ADMET properties, molecular descriptors and predicted human target proteins. By comparing the physicochemical properties of secondary metabolites in MeFSAT with other small molecules collections, we find that fungal secondary metabolites have high stereochemical complexity and shape complexity similar to other natural product libraries. Based on multiple scoring schemes, we have filtered a subset of 228 drug-like secondary metabolites in MeFSAT database. By constructing and analyzing chemical similarity networks, we show that the chemical space of secondary metabolites in MeFSAT is highly diverse. The compiled information in MeFSAT database is openly accessible at: https://cb.imsc.res.in/mefsat/.


2021 ◽  
pp. 105210
Author(s):  
Liang Zhou ◽  
Jia Zhou ◽  
Tongling Chen ◽  
Xiaojing Chi ◽  
Xiuying Liu ◽  
...  

2008 ◽  
Vol 71 (10) ◽  
pp. 1792-1792 ◽  
Author(s):  
Ronald J. Quinn ◽  
Anthony R. Carroll ◽  
Ngoc B. Pham ◽  
Paul Baron ◽  
Meredith E. Palframan ◽  
...  

Biomolecules ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1467
Author(s):  
Thanh-Diep Ly ◽  
Anika Kleine ◽  
Bastian Fischer ◽  
Vanessa Schmidt ◽  
Doris Hendig ◽  
...  

Fibroproliferative diseases are characterized by excessive accumulation of extracellular matrix (ECM) components leading to organ dysfunction. This process is characterized by an increase in myofibroblast content and enzyme activity of xylosyltransferase-I (XT-I), the initial enzyme in proteoglycan (PG) biosynthesis. Therefore, the inhibition of XT-I could be a promising treatment for fibrosis. We used a natural product-inspired compound library to identify non-substrate-based inhibitors of human XT-I by UPLC-MS/MS. We combined this cell-free approach with virtual and molecular biological analyses to confirm and prioritize the inhibitory potential of the compounds identified. The characterization for compound potency in TGF-β1-driven XYLT1 transcription regulation in primary dermal human fibroblasts (key cells in ECM remodeling) was addressed by gene expression analysis. Consequently, we identified amphotericin B and celastrol as new non-substrate-based XT-I protein inhibitors. Their XT-I inhibitory effects were mediated by an uncompetitive or a competitive inhibition mode, respectively. Both compounds reduced the cellular XYLT1 expression level and XT-I activity. We showed that these cellular inhibitor-mediated changes involve the TGF-β and microRNA-21 signaling pathway. The results of our study provide a strong rationale for the further optimization and future usage of the XT-I inhibitors identified as promising therapeutic agents of fibroproliferative diseases.


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