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Pan F, Wang CN, Yu ZH, Wu ZR, Wang Z, Lou S, Li WH, Liu GX, Li T, Zhao YZ, Tang Y. NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods. Acta Pharmacol Sin 2024:10.1038/s41401-024-01324-6. [PMID: 38902503 DOI: 10.1038/s41401-024-01324-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 05/26/2024] [Indexed: 06/22/2024] Open
Abstract
Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 μM, with Oxyberberine showing promising effects even at 10 μM. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.
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Affiliation(s)
- Fei Pan
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Cheng-Nuo Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Zhuo-Hang Yu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Zeng-Rui Wu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Ze Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Shang Lou
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Wei-Hua Li
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Gui-Xia Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Ting Li
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
| | - Yu-Zheng Zhao
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
| | - Yun Tang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
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Deng J, Lin X, Qin J, Li Q, Zhang Y, Zhang Q, Ji C, Shen S, Li Y, Zhang B, Lin N. SPTBN2 suppresses ferroptosis in NSCLC cells by facilitating SLC7A11 membrane trafficking and localization. Redox Biol 2024; 70:103039. [PMID: 38241838 PMCID: PMC10825533 DOI: 10.1016/j.redox.2024.103039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 01/21/2024] Open
Abstract
The function of SLC7A11 in the process of ferroptosis is well-established, as it regulates the synthesis of glutathione (GSH), thereby influencing tumor development along with drug resistance in non-small cell lung cancer (NSCLC). However, the determinants governing SLC7A11's membrane trafficking and localization remain unknown. Our study identified SPTBN2 as a ferroptosis suppressor, enhancing NSCLC cells resistance to ferroptosis inducers. Mechanistically, SPTBN2, through its CH domain, interacted with SLC7A11 and connected it with the motor protein Arp1, thus facilitating the membrane localization of SLC7A11 - a prerequisite for its role as System Xc-, which mediates cystine uptake and GSH synthesis. Consequently, SPTBN2 suppressed ferroptosis through preserving the functional activity of System Xc- on the membrane. Moreover, Inhibiting SPTBN2 increased the sensitivity of NSCLC cells to cisplatin through ferroptosis induction, both in vitro and in vivo. Using Abrine as a potential SPTBN2 inhibitor, its efficacy in promoting ferroptosis and sensitizing NSCLC cells to cisplatin was validated. Collectively, SPTBN2 is a potential therapeutic target for addressing ferroptosis dysfunction and cisplatin resistance in NSCLC.
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Affiliation(s)
- Jun Deng
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China; Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, GuangXi, 530021, China
| | - Xu Lin
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Jiajia Qin
- Department of Pharmacy, The second Affiliated Hospital of Guangxi Medical University, GuangXi, 530007, China
| | - Qi Li
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China
| | - Yingqiong Zhang
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China
| | - Qingyi Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Cong Ji
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 311402, China
| | - Shuying Shen
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 311402, China
| | - Yangling Li
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China
| | - Bo Zhang
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China.
| | - Nengming Lin
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, China; Westlake Laboratory of Life Sciences and Biomedicine of Zhejiang Province, Westlake University, Hangzhou, 310024, China; Cancer Center, Zhejiang University, Hangzhou, 310058, China.
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Cao S, Wei Y, Yue Y, Chen Y, Liao S, Li A, Liu P, Xiong A, Zeng H. Targeting ferroptosis unveils a new era for traditional Chinese medicine: a scientific metrology study. Front Pharmacol 2024; 15:1366852. [PMID: 38464725 PMCID: PMC10921231 DOI: 10.3389/fphar.2024.1366852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 02/02/2024] [Indexed: 03/12/2024] Open
Abstract
In the past 11 years, there has been a surge in studies exploring the regulatory effect of Traditional Chinese Medicine (TCM) on ferroptosis. However, a significant gap persists in comprehensive scientometric analysis and scientific mapping research, especially in tracking the evolution, primary contributors, and emerging research focal points. This study aims to comprehensively update the advancements in targeting ferroptosis with various TCMs during the previous 11 years. The data, covering the period from 1 January 2012, to 30 November 2023, were retrieved from the Web of Science database. For in-depth scientometric and visualized analyses, a series of advanced analytical instruments were employed. The findings highlight China's predominant role, accounting for 71.99% of total publications and significantly shaping research in this domain. Noteworthy productivity was observed at various institutions, including Guangzhou University of Chinese Medicine, Chengdu University of Traditional Chinese Medicine, and Zhejiang University. Thomas Efferth emerged as the foremost author within this field, while Frontiers in Pharmacology boasted the highest publication count. This study pinpointed hepatocellular carcinoma, chemical and drug-induced liver injury, mitochondrial diseases, acute kidney injury, and liver failure as the most critical disorders addressed in this research realm. The research offers a comprehensive bibliometric evaluation, enhancing our understanding of the present status of TCM therapy in managing ferroptosis-related diseases. Consequently, it aids both seasoned researchers and newcomers by accelerating access to vital information and fostering innovative concept extraction within this specialized field.
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Affiliation(s)
- Siyang Cao
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Yihao Wei
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Yaohang Yue
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Yingqi Chen
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Shuai Liao
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Aikang Li
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Peng Liu
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Ao Xiong
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Hui Zeng
- National and Local Joint Engineering Research Centre of Orthopaedic Biomaterials, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Key Laboratory of Orthopaedic Diseases and Biomaterials Research, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
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Yu Z, Wu Z, Wang Z, Wang Y, Zhou M, Li W, Liu G, Tang Y. Network-Based Methods and Their Applications in Drug Discovery. J Chem Inf Model 2024; 64:57-75. [PMID: 38150548 DOI: 10.1021/acs.jcim.3c01613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
Drug discovery is time-consuming, expensive, and predominantly follows the "one drug → one target → one disease" paradigm. With the rapid development of systems biology and network pharmacology, a novel drug discovery paradigm, "multidrug → multitarget → multidisease", has emerged. This new holistic paradigm of drug discovery aligns well with the essence of networks, leading to the emergence of network-based methods in the field of drug discovery. In this Perspective, we initially introduce the concept and data sources of networks and highlight classical methodologies employed in network-based methods. Subsequently, we focus on the practical applications of network-based methods across various areas of drug discovery, such as target prediction, virtual screening, prediction of drug therapeutic effects or adverse drug events, and elucidation of molecular mechanisms. In addition, we provide representative web servers for researchers to use network-based methods in specific applications. Finally, we discuss several challenges of network-based methods and the directions for future development. In a word, network-based methods could serve as powerful tools to accelerate drug discovery.
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Affiliation(s)
- Zhuohang Yu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Zengrui Wu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Ze Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yimeng Wang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Moran Zhou
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Weihua Li
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yun Tang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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Lv S, Wang Q, Zhang X, Ning F, Liu W, Cui M, Xu Y. Mechanisms of multi-omics and network pharmacology to explain traditional chinese medicine for vascular cognitive impairment: A narrative review. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 123:155231. [PMID: 38007992 DOI: 10.1016/j.phymed.2023.155231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/07/2023] [Accepted: 11/18/2023] [Indexed: 11/28/2023]
Abstract
BACKGROUND The term "vascular cognitive impairment" (VCI) describes various cognitive conditions that include vascular elements. It increases the risk of morbidity and mortality in the elderly population and is the most common cognitive impairment associated with cerebrovascular disease. Understanding the etiology of VCI may aid in identifying approaches to target its possible therapy for the condition. Treatment of VCI has focused on vascular risk factors. There are no authorized conventional therapies available right now. The medications used to treat VCI are solely approved for symptomatic relief and are not intended to prevent or slow the development of VCI. PURPOSE The function of Chinese medicine in treating VCI has not yet been thoroughly examined. This review evaluates the preclinical and limited clinical evidence to comprehend the "multi-component, multi-target, multi-pathway" mechanism of Traditional Chinese medicine (TCM). It investigates the various multi-omics approaches in the search for the pathological mechanisms of VCI, as well as the new research strategies, in the hopes of supplying supportive evidence for the clinical treatment of VCI. METHODS This review used the Preferred Reporting Items for Preferred reporting items for systematic reviews and meta-analyses (PRISMA) statements. Using integrated bioinformatics and network pharmacology approaches, a thorough evaluation and analysis of 25 preclinical studies published up to July 1, 2023, were conducted to shed light on the mechanisms of TCM for vascular cognitive impairment. The studies for the systematic review were located using the following databases: PubMed, Web of Science, Scopus, Cochrane, and ScienceDirect. RESULTS We discovered that the multi-omics analysis approach would hasten the discovery of the role of TCM in the treatment of VCI. It will explore components, compounds, targets, and pathways, slowing the progression of VCI from the perspective of inhibiting oxidative stress, stifling neuroinflammation, increasing cerebral blood flow, and inhibiting iron deposition by a variety of molecular mechanisms, which have significant implications for the treatment of VCI. CONCLUSION TCM is a valuable tool for developing dementia therapies, and further research is needed to determine how TCM components may affect the operation of the neurovascular unit. There are still some limitations, although several research have offered invaluable resources for searching for possible anti-dementia medicines and treatments. To gain new insights into the molecular mechanisms that precisely modulate the key molecules at different levels during pharmacological interventions-a prerequisite for comprehending the mechanism of action and determining the potential therapeutic value of the drugs-further research should employ more standardized experimental methods as well as more sophisticated science and technology. Given the results of this review, we advocate integrating chemical and biological component analysis approaches in future research on VCI to provide a more full and objective assessment of the standard of TCM. With the help of bioinformatics, a multi-omics analysis approach will hasten the discovery of the role of TCM in the treatment of VCI, which has significant implications for the treatment of VCI.
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Affiliation(s)
- Shi Lv
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China
| | - Qian Wang
- Department of Central Laboratory, The Affiliated Taian City Central Hospital of Qingdao University, Taian 271000, China
| | - Xinlei Zhang
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China
| | - Fangli Ning
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China
| | - Wenxin Liu
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China
| | - Mengmeng Cui
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China
| | - Yuzhen Xu
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China.
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Zhu X, Yao Q, Yang P, Zhao D, Yang R, Bai H, Ning K. Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine. Front Pharmacol 2022; 13:1031051. [PMID: 36506559 PMCID: PMC9732109 DOI: 10.3389/fphar.2022.1031051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 11/15/2022] [Indexed: 11/27/2022] Open
Abstract
Traditional Chinese Medicine (TCM) is extensively utilized in clinical practice due to its therapeutic and preventative treatments for various diseases. With the development of high-throughput sequencing and systems biology, TCM research was transformed from traditional experiment-based approaches to a combination of experiment-based and omics-based approaches. Numerous academics have explored the therapeutic mechanism of TCM formula by omics approaches, shifting TCM research from the "one-target, one-drug" to "multi-targets, multi-components" paradigm, which has greatly boosted the digitalization and internationalization of TCM. In this review, we concentrated on multi-omics approaches in principles and applications to gain a better understanding of TCM formulas against various diseases from several aspects. We first summarized frequently used TCM quality assessment methods, and suggested that incorporating both chemical and biological ingredients analytical methods could lead to a more comprehensive assessment of TCM. Secondly, we emphasized the significance of multi-omics approaches in deciphering the therapeutic mechanism of TCM formulas. Thirdly, we focused on TCM network analysis, which plays a vital role in TCM-diseases interaction, and serves for new drug discovery. Finally, as an essential source for storing multi-omics data, we evaluated and compared several TCM databases in terms of completeness and reliability. In summary, multi-omics approaches have infiltrated many aspects of TCM research. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired or will be gained in the future.
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Affiliation(s)
- Xue Zhu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qi Yao
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Pengshuo Yang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dan Zhao
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ronghua Yang
- Dovetree Synbio Company Limited, Shenyang, China,*Correspondence: Ronghua Yang, ; Hong Bai, ; Kang Ning,
| | - Hong Bai
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China,*Correspondence: Ronghua Yang, ; Hong Bai, ; Kang Ning,
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China,*Correspondence: Ronghua Yang, ; Hong Bai, ; Kang Ning,
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Wang W, He J, Yang J, Zhang C, Cheng Z, Zhang Y, Zhang Q, Wang P, Tang S, Wang X, Liu M, Lu W, Zhang HK. Scaffold Hopping Strategy to Identify Prostanoid EP4 Receptor Antagonists for Cancer Immunotherapy. J Med Chem 2022; 65:7896-7917. [PMID: 35640059 DOI: 10.1021/acs.jmedchem.2c00448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Cancer cells can effectively suppress the natural immune response in humans, and prostaglandin E2 (PGE2) is a key mediator in the development of tumor cell resistance to immunotherapy. As a major contributor to PGE2-elicited immunosuppressive activity, the EP4 receptor promotes tumor development and progression in the tumor microenvironment, and the development of selective and potent EP4 receptor antagonists should have promising potential for tumor immunotherapy. Aiming at improving the drug-like properties, a series of 4,7-dihydro-5H-thieno[2,3-c]pyran derivatives were designed and synthesized through a scaffold hopping strategy. The most promising compound 47 exhibited good EP4 antagonistic activity and excellent subtype selectivity, as well as favorable drug-like properties. It effectively suppressed the expression of multiple immunosuppression-related genes in macrophages. Meanwhile, oral administration of compound 47, alone or in combination with anti-PD-1 antibody, significantly enhanced the antitumor immune response and inhibited tumor growth in the mouse CT26 colon carcinoma model.
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Affiliation(s)
- Wei Wang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Jiacheng He
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Junjie Yang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Chan Zhang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Zhiyuan Cheng
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Yao Zhang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Qiansen Zhang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Peili Wang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Shuowen Tang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Xin Wang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Mingyao Liu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Weiqiang Lu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
| | - Han-Kun Zhang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
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Selvaraj N, Swaroop AK, Nidamanuri BSS, Kumar R R, Natarajan J, Selvaraj J. Network-based drug repurposing: A critical review. Curr Drug Res Rev 2022; 14:116-131. [PMID: 35156575 DOI: 10.2174/2589977514666220214120403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/17/2021] [Accepted: 11/30/2021] [Indexed: 11/22/2022]
Abstract
New drug development for a disease is a tedious time taking, complex and expensive process. Even if it is done, still the chances for success of newly developed drugs are very low. Modern reports state that repurposing the pre-existing drugs will have more efficient functioning than newly developed drugs. This repurposing process will save time, reduce expenses and provide more success rate. The only limitation for this repurposing is getting a desired pharmacological and characteristic parameter of various drugs from vast data available about a huge number of drugs, their effects, and target mechanisms. This drawback can be avoided by introducing computational methods of analysis. This includes various network analysis types that use various biological processes and relationships with various drugs to make data interpretation a simple process. Some of the data sets now available in standard and simplified forms include gene expression, drug-target interactions, protein networks, electronic health records, clinical trial results, and drug adverse event reports. Integrating various data sets and interpretation methods gives way for a more efficient and easy way to repurpose an exact drug for desired target and effect. In this review, we are going to discuss briefly various computational biological network analysis methods like gene regulatory networks, metabolic networks, protein-protein interaction networks, drug-target interaction networks, drug-disease association networks, drug-drug interaction networks, drug-side effects networks, integrated network-based methods, semantic link networks, and isoform-isoform networks. Along with these, we have also briefly presented limitations, predicting methods, data sets used of various biological networks used of the drug for drug repurposing.
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Affiliation(s)
- Nagaraj Selvaraj
- Department of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education &Research Ooty, Nilgiris, Tamilnadu, India
| | - Akey Krishna Swaroop
- Department of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education &Research Ooty, Nilgiris, Tamilnadu, India
| | - Bala Sai Soujith Nidamanuri
- Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education &Research Ooty, Nilgiris, Tamilnadu, India
| | - Rajesh Kumar R
- Department of Pharmaceutical Biotechnology, JSS College of Pharmacy, JSS Academy of Higher Education &Research Ooty, Nilgiris, Tamilnadu, India
| | - Jawahar Natarajan
- Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education &Research Ooty, Nilgiris, Tamilnadu, India
| | - Jubie Selvaraj
- Department of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education &Research Ooty, Nilgiris, Tamilnadu, India
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9
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Wu Z, Ma H, Liu Z, Zheng L, Yu Z, Cao S, Fang W, Wu L, Li W, Liu G, Huang J, Tang Y. wSDTNBI: a novel network-based inference method for virtual screening. Chem Sci 2022; 13:1060-1079. [PMID: 35211272 PMCID: PMC8790893 DOI: 10.1039/d1sc05613a] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/15/2021] [Indexed: 12/21/2022] Open
Abstract
In recent years, the rapid development of network-based methods for the prediction of drug-target interactions (DTIs) provides an opportunity for the emergence of a new type of virtual screening (VS), namely, network-based VS. Herein, we reported a novel network-based inference method named wSDTNBI. Compared with previous network-based methods that use unweighted DTI networks, wSDTNBI uses weighted DTI networks whose edge weights are correlated with binding affinities. A two-pronged approach based on weighted DTI and drug-substructure association networks was employed to calculate prediction scores. To show the practical value of wSDTNBI, we performed network-based VS on retinoid-related orphan receptor γt (RORγt), and purchased 72 compounds for experimental validation. Seven of the purchased compounds were confirmed to be novel RORγt inverse agonists by in vitro experiments, including ursonic acid and oleanonic acid with IC50 values of 10 nM and 0.28 μM, respectively. Moreover, the direct contact between ursonic acid and RORγt was confirmed using the X-ray crystal structure, and in vivo experiments demonstrated that ursonic acid and oleanonic acid have therapeutic effects on multiple sclerosis. These results indicate that wSDTNBI might be a powerful tool for network-based VS in drug discovery.
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Affiliation(s)
- Zengrui Wu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Hui Ma
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Zehui Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Lulu Zheng
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Zhuohang Yu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Shuying Cao
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Wenqing Fang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Lili Wu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Weihua Li
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Guixia Liu
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Jin Huang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
| | - Yun Tang
- Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology 130 Meilong Road Shanghai 200237 China
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10
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Ye Q, Hsieh CY, Yang Z, Kang Y, Chen J, Cao D, He S, Hou T. A unified drug-target interaction prediction framework based on knowledge graph and recommendation system. Nat Commun 2021; 12:6775. [PMID: 34811351 PMCID: PMC8635420 DOI: 10.1038/s41467-021-27137-3] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 11/05/2021] [Indexed: 02/06/2023] Open
Abstract
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfecting DTI prediction, existing methods still suffer from the high sparsity of DTI datasets and the cold start problem. Here, we develop KGE_NFM, a unified framework for DTI prediction by combining knowledge graph (KG) and recommendation system. This framework firstly learns a low-dimensional representation for various entities in the KG, and then integrates the multimodal information via neural factorization machine (NFM). KGE_NFM is evaluated under three realistic scenarios, and achieves accurate and robust predictions on four benchmark datasets, especially in the scenario of the cold start for proteins. Our results indicate that KGE_NFM provides valuable insight to integrate KG and recommendation system-based techniques into a unified framework for novel DTI discovery.
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Affiliation(s)
- Qing Ye
- grid.13402.340000 0004 1759 700XInnovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058 Zhejiang China ,grid.13402.340000 0004 1759 700XCollege of Control Science and Engineering, Zhejiang University, Hangzhou, 310027 Zhejiang China ,grid.13402.340000 0004 1759 700XState Key Lab of CAD&CG, Zhejiang University, Hangzhou, Zhejiang 310058 China
| | - Chang-Yu Hsieh
- Tencent Quantum Laboratory, Shenzhen, 518057 Guangdong China
| | - Ziyi Yang
- Tencent Quantum Laboratory, Shenzhen, 518057 Guangdong China
| | - Yu Kang
- grid.13402.340000 0004 1759 700XInnovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058 Zhejiang China
| | - Jiming Chen
- grid.13402.340000 0004 1759 700XCollege of Control Science and Engineering, Zhejiang University, Hangzhou, 310027 Zhejiang China
| | - Dongsheng Cao
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410013, Hunan, China.
| | - Shibo He
- College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, Zhejiang, China.
| | - Tingjun Hou
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China. .,State Key Lab of CAD&CG, Zhejiang University, Hangzhou, Zhejiang, 310058, China.
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11
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Wu Z, Wang Q, Yang H, Wang J, Li W, Liu G, Yang Y, Zhao Y, Tang Y. Discovery of Natural Products Targeting NQO1 via an Approach Combining Network-Based Inference and Identification of Privileged Substructures. J Chem Inf Model 2021; 61:2486-2498. [PMID: 33955748 DOI: 10.1021/acs.jcim.1c00260] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
NAD(P)H:quinone oxidoreductase 1 (NQO1) has been shown to be a potential therapeutic target for various human diseases, such as cancer and neurodegenerative disorders. Recent advances in computational methods, especially network-based methods, have made it possible to identify novel compounds for a target with high efficiency and low cost. In this study, we designed a workflow combining network-based methods and identification of privileged substructures to discover new compounds targeting NQO1 from a natural product library. According to the prediction results, we purchased 56 compounds for experimental validation. Without the assistance of privileged substructures, 31 compounds (31/56 = 55.4%) showed IC50 < 100 μM, and 11 compounds (11/56 = 19.6%) showed IC50 < 10 μM. With the assistance of privileged substructures, the two success rates were increased to 61.8 and 26.5%, respectively. Seven natural products further showed inhibitory activity on NQO1 at the cellular level, which may serve as lead compounds for further development. Moreover, network analysis revealed that osthole may exert anticancer effects against multiple cancer types by inhibiting not only carbonic anhydrases IX and XII but also NQO1. Our workflow and computational methods can be easily applied in other targets and become useful tools in drug discovery and development.
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Affiliation(s)
- Zengrui Wu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Qiaohui Wang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.,Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Hongbin Yang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Jiye Wang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Weihua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yi Yang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuzheng Zhao
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.,Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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12
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Wang C, Kurgan L. Survey of Similarity-Based Prediction of Drug-Protein Interactions. Curr Med Chem 2021; 27:5856-5886. [PMID: 31393241 DOI: 10.2174/0929867326666190808154841] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Revised: 04/16/2018] [Accepted: 10/23/2018] [Indexed: 12/20/2022]
Abstract
Therapeutic activity of a significant majority of drugs is determined by their interactions with proteins. Databases of drug-protein interactions (DPIs) primarily focus on the therapeutic protein targets while the knowledge of the off-targets is fragmented and partial. One way to bridge this knowledge gap is to employ computational methods to predict protein targets for a given drug molecule, or interacting drugs for given protein targets. We survey a comprehensive set of 35 methods that were published in high-impact venues and that predict DPIs based on similarity between drugs and similarity between protein targets. We analyze the internal databases of known PDIs that these methods utilize to compute similarities, and investigate how they are linked to the 12 publicly available source databases. We discuss contents, impact and relationships between these internal and source databases, and well as the timeline of their releases and publications. The 35 predictors exploit and often combine three types of similarities that consider drug structures, drug profiles, and target sequences. We review the predictive architectures of these methods, their impact, and we explain how their internal DPIs databases are linked to the source databases. We also include a detailed timeline of the development of these predictors and discuss the underlying limitations of the current resources and predictive tools. Finally, we provide several recommendations concerning the future development of the related databases and methods.
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Affiliation(s)
- Chen Wang
- Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23284, United States
| | - Lukasz Kurgan
- Department of Computer Science, Virginia Commonwealth University, Richmond, VA 23284, United States
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13
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Lu W, Yu W, He J, Liu W, Yang J, Lin X, Zhang Y, Wang X, Jiang W, Luo J, Zhang Q, Yang H, Peng S, Yi Z, Ren S, Chen J, Siwko S, Nussinov R, Cheng F, Zhang H, Liu M. Reprogramming immunosuppressive myeloid cells facilitates immunotherapy for colorectal cancer. EMBO Mol Med 2021; 13:e12798. [PMID: 33283987 PMCID: PMC7799360 DOI: 10.15252/emmm.202012798] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 11/03/2020] [Accepted: 11/05/2020] [Indexed: 12/24/2022] Open
Abstract
Immune checkpoint blockade (ICB) has a limited effect on colorectal cancer, underlining the requirement of co-targeting the complementary mechanisms. Here, we identified prostaglandin E2 (PGE2 ) receptor 4 (EP4) as the master regulator of immunosuppressive myeloid cells (IMCs), which are the major driver of resistance to ICB therapy. PGE2 -bound EP4 promotes the differentiation of immunosuppressive M2 macrophages and myeloid-derived suppressor cells (MDSCs) and reduces the expansion of immunostimulated M1 macrophages. To explore the immunotherapeutic role of EP4 signaling, we developed a novel and selective EP4 antagonist TP-16. TP-16 effectively blocked the function of IMCs and enhanced cytotoxic T-cell-mediated tumor elimination in vivo. Cell co-culture experiments revealed that TP-16 promoted T-cell proliferation, which was impaired by tumor-derived CD11b+ myeloid cells. Notably, TP-16 and anti-PD-1 combination therapy significantly impeded tumor progression and prolonged mice survival. We further demonstrated that TP-16 increased responsiveness to anti-PD-1 therapy in an IMC-related spontaneous colorectal cancer mouse model. In summary, this study demonstrates that inhibition of EP4-expressing IMCs may offer a potential strategy for enhancing the efficacy of immunotherapy for colorectal cancer.
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Affiliation(s)
- Weiqiang Lu
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Weiwei Yu
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Jiacheng He
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Wenjuan Liu
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Junjie Yang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Xianhua Lin
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Yuanjin Zhang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Xin Wang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Wenhao Jiang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Jian Luo
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Qiansen Zhang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Huaiyu Yang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Shihong Peng
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Zhengfang Yi
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Shancheng Ren
- Department of UrologyChanghai HospitalSecond Military UniversityShanghaiChina
| | - Jing Chen
- School of Basic Medical SciencesNingxia Medical UniversityYinchuanChina
| | - Stefan Siwko
- Department of Molecular and Cellular MedicineInstitute of Biosciences and TechnologyTexas A&M University Health Science CenterHoustonTXUSA
| | - Ruth Nussinov
- Cancer and Inflammation ProgramLeidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research Sponsored by the National Cancer InstituteFrederickMDUSA
- Department of Human Molecular Genetics and BiochemistrySackler School of MedicineTel Aviv UniversityTel AvivIsrael
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research InstituteCleveland ClinicClevelandOHUSA
- Department of Molecular MedicineCleveland Clinic Lerner College of MedicineCase Western Reserve UniversityClevelandOHUSA
- Case Comprehensive Cancer CenterCase Western Reserve University School of MedicineClevelandOHUSA
| | - Hankun Zhang
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
| | - Mingyao Liu
- Shanghai Key Laboratory of Regulatory BiologyInstitute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghaiChina
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14
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Yang D, Zhou Q, Labroska V, Qin S, Darbalaei S, Wu Y, Yuliantie E, Xie L, Tao H, Cheng J, Liu Q, Zhao S, Shui W, Jiang Y, Wang MW. G protein-coupled receptors: structure- and function-based drug discovery. Signal Transduct Target Ther 2021; 6:7. [PMID: 33414387 PMCID: PMC7790836 DOI: 10.1038/s41392-020-00435-w] [Citation(s) in RCA: 242] [Impact Index Per Article: 80.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/30/2020] [Accepted: 12/05/2020] [Indexed: 02/08/2023] Open
Abstract
As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.
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Affiliation(s)
- Dehua Yang
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China
| | - Qingtong Zhou
- School of Basic Medical Sciences, Fudan University, 200032, Shanghai, China
| | - Viktorija Labroska
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Shanshan Qin
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Sanaz Darbalaei
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Yiran Wu
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Elita Yuliantie
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Linshan Xie
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Houchao Tao
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Jianjun Cheng
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Qing Liu
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China
| | - Suwen Zhao
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China. .,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
| | - Yi Jiang
- The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.
| | - Ming-Wei Wang
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China. .,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China. .,School of Basic Medical Sciences, Fudan University, 200032, Shanghai, China. .,University of Chinese Academy of Sciences, 100049, Beijing, China. .,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China. .,School of Pharmacy, Fudan University, 201203, Shanghai, China.
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15
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Wu Z, Peng Y, Yu Z, Li W, Liu G, Tang Y. NetInfer: A Web Server for Prediction of Targets and Therapeutic and Adverse Effects via Network-Based Inference Methods. J Chem Inf Model 2020; 60:3687-3691. [PMID: 32687354 DOI: 10.1021/acs.jcim.0c00291] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In this study, we developed a web server named NetInfer for prediction of targets and therapeutic and adverse effects via network-based inference methods. Compared with our previously developed standalone version of NetInfer, this web server provides a user-friendly interface. With the web server, users can easily predict potential target proteins, microRNAs, Anatomical Therapeutic Chemical (ATC) classification codes, or adverse drug events for small molecules of their interests in a few steps. Most of the prediction models were constructed on the basis of our previous studies, where those models have been evaluated systematically and demonstrated high performance. The high-quality models can generate accurate predictions. As a case study, we predicted ATC codes and target proteins for several drugs. The predicted therapeutic effects of these drugs on cardiovascular diseases and their potential molecular mechanisms were validated by the literature. This successful case study demonstrated that our web server would be a powerful tool in drug repositioning and systems pharmacology. The web server of NetInfer is freely available at http://lmmd.ecust.edu.cn/netinfer/.
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Affiliation(s)
- Zengrui Wu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yayuan Peng
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Zhuohang Yu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Weihua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
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16
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Yang JJ, Yu WW, Hu LL, Liu WJ, Lin XH, Wang W, Zhang Q, Wang PL, Tang SW, Wang X, Liu M, Lu W, Zhang HK. Discovery and Characterization of 1 H-1,2,3-Triazole Derivatives as Novel Prostanoid EP4 Receptor Antagonists for Cancer Immunotherapy. J Med Chem 2020; 63:569-590. [PMID: 31855426 DOI: 10.1021/acs.jmedchem.9b01269] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The prostanoid EP4 receptor is one of the key receptors associated with inflammatory mediator PGE2-elicited immunosuppression in the tumor microenvironment. Blockade of EP4 signaling to enhance immunity-mediated tumor elimination has recently emerged as a promising strategy for cancer immunotherapy. In our efforts to discover novel subtype-selective EP4 antagonists, we designed and synthesized a class of 1H-1,2,3-triazole-based ligands that display low nanomolar antagonism activity toward the human EP4 receptor and excellent subtype selectivity. The most promising compound 59 exhibits single-digit nanomolar potency in the EP4 calcium flux and cAMP-response element reporter assays and effectively suppresses the expression of multiple immunosuppression-related genes in macrophage cells. On the basis of its favorable ADMET properties, compound 59 was chosen for further in vivo biological evaluation. Oral administration of compound 59 significantly inhibited tumor growth in the mouse CT26 colon carcinoma model accompanied by enhanced infiltration of cytotoxic T lymphocytes in the tumor tissue.
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Affiliation(s)
- Jun-Jie Yang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Wei-Wei Yu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Long-Long Hu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Wen-Juan Liu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Xian-Hua Lin
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Wei Wang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Qiansen Zhang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Pei-Li Wang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Shuo-Wen Tang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Xin Wang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Mingyao Liu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Weiqiang Lu
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
| | - Han-Kun Zhang
- Drug Discovery Unit, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences , East China Normal University , 500 Dongchuan Road , Shanghai 200241 , China
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17
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Medvedev KE, Kinch LN, Schaeffer RD, Grishin NV. Functional analysis of Rossmann-like domains reveals convergent evolution of topology and reaction pathways. PLoS Comput Biol 2019; 15:e1007569. [PMID: 31869345 PMCID: PMC6957218 DOI: 10.1371/journal.pcbi.1007569] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 01/13/2020] [Accepted: 11/26/2019] [Indexed: 12/18/2022] Open
Abstract
Rossmann folds are ancient, frequently diverged domains found in many biological reaction pathways where they have adapted for different functions. Consequently, discernment and classification of their homologous relations and function can be complicated. We define a minimal Rossmann-like structure motif (RLM) that corresponds for the common core of known Rossmann domains and use this motif to identify all RLM domains in the Protein Data Bank (PDB), thus finding they constitute about 20% of all known 3D structures. The Evolutionary Classification of protein structure Domains (ECOD) classifies RLM domains in a number of groups that lack evidence for homology (X-groups), which suggests that they could have evolved independently multiple times. Closely related, homologous RLM enzyme families can diverge to bind different ligands using similar binding sites and to catalyze different reactions. Conversely, non-homologous RLM domains can converge to catalyze the same reactions or to bind the same ligand with alternate binding modes. We discuss a special case of such convergent evolution that is relevant to the polypharmacology paradigm, wherein the same drug (methotrexate) binds to multiple non-homologous RLM drug targets with different topologies. Finally, assigning proteins with RLM domain to the Enzyme Commission classification suggest that RLM enzymes function mainly in metabolism (and comprise 38% of reference metabolic pathways) and are overrepresented in extant pathways that represent ancient biosynthetic routes such as nucleotide metabolism, energy metabolism, and metabolism of amino acids. In fact, RLM enzymes take part in five out of eight enzymatic reactions of the Wood-Ljungdahl metabolic pathway thought to be used by the last universal common ancestor (LUCA). The prevalence of RLM domains in this ancient metabolism might explain their wide distribution among enzymes.
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Affiliation(s)
- Kirill E. Medvedev
- Departments of Biophysics and Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Lisa N. Kinch
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - R. Dustin Schaeffer
- Departments of Biophysics and Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Nick V. Grishin
- Departments of Biophysics and Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
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Top-100 Most Cited Publications Concerning Network Pharmacology: A Bibliometric Analysis. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2019; 2019:1704816. [PMID: 31467569 PMCID: PMC6701366 DOI: 10.1155/2019/1704816] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 06/26/2019] [Accepted: 07/01/2019] [Indexed: 12/16/2022]
Abstract
Background Network pharmacology (NP) has become an increasingly important focus in the drug research field over the past decade. However, no study to date has mapped the current status of NP. Therefore, we performed a bibliometric study to evaluate the top 100 cited papers on NP. Methods We searched the Web of Science Core Collection from its inception to February 25, 2019, using the terms “network pharmacology” and “systems pharmacology.” Key data, including title, publication year, number of citations, authors, countries/regions, organizations, and journals, were retrieved and analyzed using Excel 2016 and VOSviewer 1.6.10. Results The total number of citations for the 100 cited papers ranged from 21 to 1,238, published in 53 journals, from 2005 to 2017. The top three journals with the most publications on NP were Clinical Pharmacology & Therapeutics (n = 8, IF2017 = 6.544), Journal of Ethnopharmacology (n = 8, IF2017 = 3.115), and PLoS One (n = 7, IF2017 = 2.766). Most published articles were from the USA (n = 41) and China (n = 35). The most active author was Wang Yonghua from the Northwest A&F University, and of the 100 publications, 14 listing his name. The most frequently used substantive terms included “drug discovery,” “traditional Chinese medicine (TCM),” “in-vitro,” “cancer,” and “cardiovascular disease.” Conclusions. The USA and China made the greatest contribution to NP research. The current NP research mainly focused on NP methods (including experimental validation) and using them to explore the molecular mechanisms of TCM for some critical diseases such as cardiovascular diseases and cancers. Furthermore, we believe some guidelines should be developed to regulate NP studies.
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Zhang W, Huai Y, Miao Z, Chen C, Shahen M, Rahman SU, Alagawany M, El-Hack MEA, Zhao H, Qian A. Systems pharmacology approach to investigate the molecular mechanisms of herb Rhodiola rosea L. radix. Drug Dev Ind Pharm 2018; 45:456-464. [PMID: 30449200 DOI: 10.1080/03639045.2018.1546316] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Rhodiola rosea L. radix (RRL) is one of the most popular medical herb which has been widely used for the treatment of different diseases effectively, including cardiovascular diseases and nerve system diseases. However, due to the multiple compounds in RRL, the underlying molecular mechanisms of RRL are remained unclear. To decipher the action mechanisms of RRL from a systematic perspective, a systems pharmacology approach integrated absorption, distribution, metabolism, and excretion (ADME) system, drug targeting, and network analysis was introduced. First, by the ADME screening system and the target fishing process, 56 potential active compounds and 62 targets were obtained, respectively. In addition, compound-target network demonstrated that most compounds interacted with multiple targets, indicating that RRL may enhance its therapeutic effects probably through hitting on multiple targets in a holistic level. Moreover, target-pathway network and gene ontology analysis showed that multiple targets of RRL were involved in several biological pathways, i.e. Neuroactive ligand-receptor interaction, calcium signaling pathway, adrenergic signaling in cardiomyocytes, and VEGF signaling pathway, which dissecting the therapeutic effects of RRL on various diseases, such as cardiovascular diseases, depression, adaptation diseases, etc. In summary, this work successfully explains the potential active compounds and the multi-scale curative action mechanisms of RRL for treating various diseases; meanwhile, it implies that RRL could be applied as a novel therapeutic agent in arthritic diseases. Most importantly, this work provides an in silico strategy to understand the action mechanisms of herbal medicines from molecular/system levels, which will promote the new drug development of traditional Chinese medicine.
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Affiliation(s)
- Wenjuan Zhang
- a Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences , Northwestern Polytechnical University , Xi'an , People's Republic of China
| | - Ying Huai
- a Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences , Northwestern Polytechnical University , Xi'an , People's Republic of China
| | - Zhiping Miao
- a Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences , Northwestern Polytechnical University , Xi'an , People's Republic of China
| | - Chu Chen
- b Clinical Laboratory of Honghui Hospital , Xi'an JiaoTong University College of Medicine , Xi'an , Shaanxi , People's Republic of China
| | - Mohamed Shahen
- c Zoology Department, Faculty of Science , Tanta University , Tanta , Egypt
| | - Siddiq Ur Rahman
- d College of Life Sciences , Northwest A & F University , Yangling , Shaanxi , People's Republic of China
| | - Mahmoud Alagawany
- e Department of Poultry, Faculty of Agriculture , Zagazig University , Zagazig , Egypt
| | - Mohamed E Abd El-Hack
- e Department of Poultry, Faculty of Agriculture , Zagazig University , Zagazig , Egypt
| | - Heping Zhao
- b Clinical Laboratory of Honghui Hospital , Xi'an JiaoTong University College of Medicine , Xi'an , Shaanxi , People's Republic of China
| | - Airong Qian
- a Lab for Bone Metabolism, Key Lab for Space Biosciences and Biotechnology, Research Center for Special Medicine and Health Systems Engineering, NPU-UAB Joint Laboratory for Bone Metabolism, School of Life Sciences , Northwestern Polytechnical University , Xi'an , People's Republic of China
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Wu Z, Li W, Liu G, Tang Y. Network-Based Methods for Prediction of Drug-Target Interactions. Front Pharmacol 2018; 9:1134. [PMID: 30356768 PMCID: PMC6189482 DOI: 10.3389/fphar.2018.01134] [Citation(s) in RCA: 111] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Accepted: 09/18/2018] [Indexed: 01/10/2023] Open
Abstract
Drug-target interaction (DTI) is the basis of drug discovery. However, it is time-consuming and costly to determine DTIs experimentally. Over the past decade, various computational methods were proposed to predict potential DTIs with high efficiency and low costs. These methods can be roughly divided into several categories, such as molecular docking-based, pharmacophore-based, similarity-based, machine learning-based, and network-based methods. Among them, network-based methods, which do not rely on three-dimensional structures of targets and negative samples, have shown great advantages over the others. In this article, we focused on network-based methods for DTI prediction, in particular our network-based inference (NBI) methods that were derived from recommendation algorithms. We first introduced the methodologies and evaluation of network-based methods, and then the emphasis was put on their applications in a wide range of fields, including target prediction and elucidation of molecular mechanisms of therapeutic effects or safety problems. Finally, limitations and perspectives of network-based methods were discussed. In a word, network-based methods provide alternative tools for studies in drug repurposing, new drug discovery, systems pharmacology and systems toxicology.
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Affiliation(s)
| | | | | | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
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Wang T, Wu Z, Sun L, Li W, Liu G, Tang Y. A Computational Systems Pharmacology Approach to Investigate Molecular Mechanisms of Herbal Formula Tian-Ma-Gou-Teng-Yin for Treatment of Alzheimer's Disease. Front Pharmacol 2018; 9:668. [PMID: 29997503 PMCID: PMC6028720 DOI: 10.3389/fphar.2018.00668] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 06/04/2018] [Indexed: 12/19/2022] Open
Abstract
Traditional Chinese medicine (TCM) is typically prescribed as formula to treat certain symptoms. A TCM formula contains hundreds of chemical components, which makes it complicated to elucidate the molecular mechanisms of TCM. Here, we proposed a computational systems pharmacology approach consisting of network link prediction, statistical analysis, and bioinformatics tools to investigate the molecular mechanisms of TCM formulae. Taking formula Tian-Ma-Gou-Teng-Yin as an example, which shows pharmacological effects on Alzheimer’s disease (AD) and its mechanism is unclear, we first identified 494 formula components together with corresponding 178 known targets, and then predicted 364 potential targets for these components with our balanced substructure-drug–target network-based inference method. With Fisher’s exact test and statistical analysis we identified 12 compounds to be most significantly related to AD. The target genes of these compounds were further enriched onto pathways involved in AD, such as neuroactive ligand–receptor interaction, serotonergic synapse, inflammatory mediator regulation of transient receptor potential channel and calcium signaling pathway. By regulating key target genes, such as ACHE, HTR2A, NOS2, and TRPA1, the formula could have neuroprotective and anti-neuroinflammatory effects against the progression of AD. Our approach provided a holistic perspective to study the relevance between TCM formulae and diseases, and implied possible pharmacological effects of TCM components.
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Affiliation(s)
- Tianduanyi Wang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Zengrui Wu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Lixia Sun
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Weihua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Guixia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
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