Novel Applications of Metabolomics in Drug Discovery

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Medicinal Chemistry".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 13180

Special Issue Editors

Department of Pharmaceutical Analysis, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
Interests: network pharmacology; metabolomics; machine learning; chemotherapy toxicity; Chinese medicine
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Guest Editor
Key Laboratory of Drug Quality Control and Pharmacovigilance, China Pharmaceutical University, Ministry of Education, Nanjing 210009, China
Interests: functional metabolomics; bioanalysis; LC/MS; quality control; Chinese medicine
Center for Biotechnology, Anhui Agricultural University, Hefei 230036, China
Interests: mass spectrometry; natural products; antioxidation; diabetes; lipidomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Metabolomics is changing drug research. With improved analytical techniques and detailed metabolic network models, metabolomics is increasingly valuable for a wide range of pharmaceutical applications. Metabolomics has already revealed unexpected metabolite biomarkers and metabolic causes for several complex diseases, such as Alzheimer's disease, ischemic stroke, and cancer. These findings provide previously unsuspected drug targets and potential novel therapeutic strategies. Metabolomics can play a role in reducing drug failures due to toxicity in early-phase trials or drug withdrawals in late-phase trials. Meanwhile, metabolomics is also an effective means of mechanism exploration and drug discovery of natural products. 

This Special Issue seeks novel research contributions, with particular emphasis on the following areas: 

  • Metabolomics-based strategy for drug discovery;
  • Metabolic signatures for drug safety evaluation;
  • Targets identification for drug discovery;
  • The function of bioactive metabolites;
  • Artificial intelligence and metabolomics “big data”;
  • Novel metabolic network models for drug discovery. 

Areas such as metabolic profiling and fingerprinting of herbal medicines, metabolite target analysis, and metabolomics in systems biology are included in the scope of this Special Issue. Manuscripts describing research not involving drugs and metabolites will not be considered. 

We welcome and look forward to your submissions. 

Dr. Yin Huang
Prof. Dr. Zunjian Zhang
Dr. Huimin Guo
Guest Editors

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Keywords

  • metabolomics-driven drug discovery
  • metabolic network
  • pharmaceutical application
  • lipidomics
  • drug target
  • metabolic biomarker
  • complex diseases
  • toxicity

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Published Papers (5 papers)

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Research

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13 pages, 4016 KiB  
Article
Study on the Intervention Mechanism of Cryptotanshinone on Human A2780 Ovarian Cancer Cell Line Using GC-MS-Based Cellular Metabolomics
by Tong Wang, Shusheng Yin, Juan Gu, Jingjing Li, Mengmeng Zhang, Jinjun Shan, Xiao Wu and Yongming Li
Pharmaceuticals 2023, 16(6), 861; https://doi.org/10.3390/ph16060861 - 9 Jun 2023
Cited by 3 | Viewed by 1961
Abstract
Cryptotanshinone (CT), an active component of the traditional Chinese medicine Salvia miltiorrhiza Bunge, exhibits a wide range of biological and pharmacological activities. Although the anticancer activity of CT is well known, the knowledge of its effect on the regulation of cancer cell metabolism [...] Read more.
Cryptotanshinone (CT), an active component of the traditional Chinese medicine Salvia miltiorrhiza Bunge, exhibits a wide range of biological and pharmacological activities. Although the anticancer activity of CT is well known, the knowledge of its effect on the regulation of cancer cell metabolism is relatively new. The present study investigated the anticancer mechanism of CT in ovarian cancer with a focus on cancer metabolism. CCK8 assays, apoptosis assays, and cell cycle assays were conducted to reveal the growth-suppressive effect of CT on ovarian cancer A2780 cells. To explore the potential underlying mechanisms of CT, the changes in endogenous metabolites in A2780 cells before and after CT intervention were investigated using the gas chromatography–mass spectrometry (GC-MS) approach. A total of 28 important potential biomarkers underwent significant changes, mainly involving aminoacyl-tRNA biosynthesis, energy metabolism, and other pathways. Changes in the ATP and amino acid contents were verified with in vitro and in vivo experiments. Our results indicate that CT may exert an anti-ovarian cancer effect by inhibiting ATP production, promoting the protein catabolic process, and inhibiting protein synthesis, which may lead to cell cycle arrest and apoptosis. Full article
(This article belongs to the Special Issue Novel Applications of Metabolomics in Drug Discovery)
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13 pages, 4862 KiB  
Article
Metabolomics and Network Analyses Reveal Phenylalanine and Tyrosine as Signatures of Anthracycline-Induced Hepatotoxicity
by Peipei Liu, Jing Wu, Xinyue Yu, Linling Guo, Ling Zhao, Tao Ban and Yin Huang
Pharmaceuticals 2023, 16(6), 797; https://doi.org/10.3390/ph16060797 - 26 May 2023
Cited by 4 | Viewed by 1906
Abstract
The chemotherapy drug doxorubicin (DOX) is an anthracycline with over 30% incidence of liver injury in breast cancer patients, yet the mechanism of its hepatotoxicity remains unclear. To identify potential biomarkers for anthracycline-induced hepatotoxicity (AIH), we generated clinically-relevant mouse and rat models administered [...] Read more.
The chemotherapy drug doxorubicin (DOX) is an anthracycline with over 30% incidence of liver injury in breast cancer patients, yet the mechanism of its hepatotoxicity remains unclear. To identify potential biomarkers for anthracycline-induced hepatotoxicity (AIH), we generated clinically-relevant mouse and rat models administered low-dose, long-term DOX. These models exhibited significant liver damage but no decline in cardiac function. Through untargeted metabolic profiling of the liver, we identified 27 differential metabolites in a mouse model and 28 in a rat model. We then constructed a metabolite-metabolite network for each animal model and computationally identified several potential metabolic markers, with particular emphasis on aromatic amino acids, including phenylalanine, tyrosine, and tryptophan. We further performed targeted metabolomics analysis on DOX-treated 4T1 breast cancer mice for external validation. We found significant (p < 0.001) reductions in hepatic levels of phenylalanine and tyrosine (but not tryptophan) following DOX treatment, which were strongly correlated with serum aminotransferases (ALT and AST) levels. In summary, the results of our study present compelling evidence supporting the use of phenylalanine and tyrosine as metabolic signatures of AIH. Full article
(This article belongs to the Special Issue Novel Applications of Metabolomics in Drug Discovery)
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20 pages, 8720 KiB  
Article
Parsing the Q-Markers of Baoyin Jian to Treat Abnormal Uterine Bleeding by High-Throughput Chinmedomics Strategy
by Qiuhan Li, Junling Ren, Le Yang, Hui Sun, Xiwu Zhang, Guangli Yan, Ying Han and Xijun Wang
Pharmaceuticals 2023, 16(5), 719; https://doi.org/10.3390/ph16050719 - 9 May 2023
Cited by 2 | Viewed by 2361
Abstract
Abnormal uterine bleeding (AUB) is a common and frequently occurring disease in gynecology, seriously threatening women’s health. Baoyin Jian (BYJ) is a classical prescription for treating AUB. However, the lack of quality control standards of BYJ for AUB have limited the development and [...] Read more.
Abnormal uterine bleeding (AUB) is a common and frequently occurring disease in gynecology, seriously threatening women’s health. Baoyin Jian (BYJ) is a classical prescription for treating AUB. However, the lack of quality control standards of BYJ for AUB have limited the development and applications of BYJ. This experiment aims to explore the mechanism of action and screen the quality markers (Q-markers) of BYJ against AUB through the Chinmedomics strategy to improve the quality standards of Chinese medicine and provide scientific basis for its further development. BYJ has hemostatic effects in rats, as well as the ability to regulate the coagulation system following incomplete medical abortion. According to the results of histopathology, biochemical indexes and urine metabolomics, a total of 32 biomarkers of ABU in rats were identified, 16 of which can be significantly regulated by BYJ. Using traditional Chinese medicine (TCM) serum pharmacochemistry technology, 59 effective components were detected in vivo, of which 13 were highly correlated with efficacy, and 9 components, namely catalpol, rehmannioside D, paeoniflorin, berberine, phellodendrine, baicalin, asperosaponinVI, liquiritin, and glycyrrhizic acid, were screened out as the Q-markers of BYJ based on the “Five Principles” of Q-markers. In sum, BYJ can effectively alleviate abnormal bleeding symptoms and metabolic abnormalities in AUB rats. The study shows that Chinmedomics is an effective tool for screening Q-markers and provides scientific support for the further development and clinical use of BYJ. Full article
(This article belongs to the Special Issue Novel Applications of Metabolomics in Drug Discovery)
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18 pages, 2223 KiB  
Article
Metabolomic Analysis of Stephania tetrandraAstragalus membranaceus Herbal Pair-Improving Nephrotic Syndrome Identifies Activation of IL-13/STAT6 Signaling Pathway
by Baiyang Xu, Mengxue Yao, Zilu Liu, Shanshan Zhang, Bin Wang, Yanquan Han, Jiarong Gao, Deling Wu and Xiaoli Wang
Pharmaceuticals 2023, 16(1), 88; https://doi.org/10.3390/ph16010088 - 8 Jan 2023
Cited by 5 | Viewed by 2464
Abstract
The Stephania tetrandraAstragalus membranaceus herbal pair (FH) is a classic herbal pair widely used in the treatment of nephrotic syndrome (NS). The effects of Stephania tetrandra (FJ) and Astragalus membranaceus (HQ) on NS have been reported, but the mechanism of their [...] Read more.
The Stephania tetrandraAstragalus membranaceus herbal pair (FH) is a classic herbal pair widely used in the treatment of nephrotic syndrome (NS). The effects of Stephania tetrandra (FJ) and Astragalus membranaceus (HQ) on NS have been reported, but the mechanism of their combination on the improvement of NS are still unclear. The NS model was established by injecting adriamycin into the tail vein. FH intervention reduced the levels of serum triglyceride, total cholesterol, interleukin-6 (IL-6), blood urea nitrogen (BUN), urinary protein, and the gene expression levels of aquaporin 2 (AQP2) and arginine vasopressin (AVP) in NS rats. In addition, FH improved kidney injury in NS rats by inhibiting the expression of interleukin 13 (IL-13), phospho-signal transducers, and activators of transcription 6 (p-STAT6), Bax, cleaved-caspase3, while promoting the expression of Bcl-2. By comprehensive comparison of multiple indexes, the effects of FH on lipid metabolism, glomerular filtration rate, and inflammation were superior to that of FJ and HQ. Metabonomic studies showed that, compared with FJ and HQ, FH intervention significantly regulated tricarboxylic acid (TCA) cycle, cysteine and methionine metabolism, and alanine, aspartic acid and glutamic acid metabolism. Pearson correlation analysis showed that succinic acid and L-aspartic acid were negatively correlated with urinary protein, cystatin C (Cys C) and BUN (p < 0.05). In summary, FH could reduce renal injury and improve NS through inhibiting the IL-13/STAT6 signal pathway, regulating endogenous metabolic pathways, such as TCA cycle, and inhibiting the expression of AQP2 and AVP genes. This study provides a comprehensive strategy to reveal the mechanism of FH on the treatment of NS, and also provides a reasonable way to clarify the compatibility of traditional Chinese medicine. Full article
(This article belongs to the Special Issue Novel Applications of Metabolomics in Drug Discovery)
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Review

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25 pages, 3434 KiB  
Review
Active Compounds of Panax ginseng in the Improvement of Alzheimer’s Disease and Application of Spatial Metabolomics
by Meng Zhang, Huazhou Niu, Qingqing Li, Lili Jiao, Hui Li and Wei Wu
Pharmaceuticals 2024, 17(1), 38; https://doi.org/10.3390/ph17010038 - 26 Dec 2023
Cited by 3 | Viewed by 2987
Abstract
Panax ginseng C.A. Meyer (P. ginseng) is one of the more common traditional Chinese medicines (TCMs). It contains numerous chemical components and exhibits a range of pharmacological effects. An enormous burden is placed on people’s health and life by Alzheimer’s disease [...] Read more.
Panax ginseng C.A. Meyer (P. ginseng) is one of the more common traditional Chinese medicines (TCMs). It contains numerous chemical components and exhibits a range of pharmacological effects. An enormous burden is placed on people’s health and life by Alzheimer’s disease (AD), a neurodegenerative condition. Recent research has shown that P. ginseng’s chemical constituents, particularly ginsenosides, have a significant beneficial impact on the prevention and management of neurological disorders. To understand the current status of research on P. ginseng to improve AD, this paper discusses the composition of P. ginseng, its mechanism of action, and its clinical application. The pathogenesis of AD includes amyloid beta protein (Aβ) generation and aggregation, tau protein hyperphosphorylation, oxidant stress, neuroinflammation, mitochondrial damage, and neurotransmitter and gut microbiota disorders. This review presents the key molecular mechanisms and signaling pathways of the active ingredients in P. ginseng involved in improving AD from the perspective of AD pathogenesis. A P. ginseng-related signaling pathway network was constructed to provide effective targets for the treatment of AD. In addition, the application of spatial metabolomics techniques in studying P. ginseng and AD is discussed. In summary, this paper discusses research perspectives for the study of P. ginseng in the treatment of AD, including a systematic and in-depth review of the mechanisms of action of the active substances in P. ginseng, and evaluates the feasibility of applying spatial metabolomics in the study of AD pathogenesis and pharmacological treatment. Full article
(This article belongs to the Special Issue Novel Applications of Metabolomics in Drug Discovery)
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