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Zhang Q, He Y, Lu YP, Wei QH, Zhang HY, Quan Y. GETdb: A comprehensive database for genetic and evolutionary features of drug targets. Comput Struct Biotechnol J 2024; 23:1429-1438. [PMID: 38616961 PMCID: PMC11015738 DOI: 10.1016/j.csbj.2024.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/25/2024] [Accepted: 04/01/2024] [Indexed: 04/16/2024] Open
Abstract
The development of an innovative drug is complex and time-consuming, and the drug target identification is one of the critical steps in drug discovery process. Effective and accurate identification of drug targets can accelerate the drug development process. According to previous research, evolutionary and genetic information of genes has been found to facilitate the identification of approved drug targets. In addition, allosteric proteins have great potential as targets due to their structural diversity. However, this information that could facilitate target identification has not been collated in existing drug target databases. Here, we construct a comprehensive drug target database named Genetic and Evolutionary features of drug Targets database (GETdb, http://zhanglab.hzau.edu.cn/GETdb/page/index.jsp). This database not only integrates and standardizes data from dozens of commonly used drug and target databases, but also innovatively includes the genetic and evolutionary information of targets. Moreover, this database features an effective allosteric protein prediction model. GETdb contains approximately 4000 targets and over 29,000 drugs, and is a user-friendly database for searching, browsing and downloading data to facilitate the development of novel targets.
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Affiliation(s)
- Qi Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China
| | - Yang He
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China
| | - Ya-Ping Lu
- Sinopharm Genomics Technology Co., Ltd., Wuhan 430030, PR China
- Sinopharm Medical Laboratory (Wuhan) Co., Ltd., Wuhan 430030, PR China
| | - Qi-Hao Wei
- Sinopharm (Wuhan) Precision Medical Technology Co., Ltd., Wuhan 430030, PR China
| | - Hong-Yu Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China
| | - Yuan Quan
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, PR China
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Zhao JH, Wang YW, Yang J, Tong ZJ, Wu JZ, Wang YB, Wang QX, Li QQ, Yu YC, Leng XJ, Chang L, Xue X, Sun SL, Li HM, Ding N, Duan JA, Li NG, Shi ZH. Natural products as potential lead compounds to develop new antiviral drugs over the past decade. Eur J Med Chem 2023; 260:115726. [PMID: 37597436 DOI: 10.1016/j.ejmech.2023.115726] [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: 04/13/2023] [Revised: 05/22/2023] [Accepted: 08/13/2023] [Indexed: 08/21/2023]
Abstract
Virus infection has been one of the main causes of human death since the ancient times. Even though more and more antiviral drugs have been approved in clinic, long-term use can easily lead to the emergence of drug resistance and side effects. Fortunately, there are many kinds of metabolites which were produced by plants, marine organisms and microorganisms in nature with rich structural skeletons, and they are natural treasure house for people to find antiviral active substances. Aiming at many types of viruses that had caused serious harm to human health in recent years, this review summarizes the natural products with antiviral activity that had been reported for the first time in the past ten years, we also sort out the source, chemical structure and safety indicators in order to provide potential lead compounds for the research and development of new antiviral drugs.
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Affiliation(s)
- Jing-Han Zhao
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Yue-Wei Wang
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Jin Yang
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Zhen-Jiang Tong
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Jia-Zhen Wu
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Yi-Bo Wang
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Qing-Xin Wang
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Qing-Qing Li
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Yan-Cheng Yu
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Xue-Jiao Leng
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Liang Chang
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Xin Xue
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Shan-Liang Sun
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - He-Min Li
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China
| | - Ning Ding
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China.
| | - Jin-Ao Duan
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China.
| | - Nian-Guang Li
- National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, Jiangsu, 210023, China.
| | - Zhi-Hao Shi
- Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu, 211198, China.
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Quan Y, Xiong ZK, Zhang KX, Zhang QY, Zhang W, Zhang HY. Evolution-strengthened knowledge graph enables predicting the targetability and druggability of genes. PNAS NEXUS 2023; 2:pgad147. [PMID: 37188275 PMCID: PMC10178923 DOI: 10.1093/pnasnexus/pgad147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 04/21/2023] [Indexed: 05/17/2023]
Abstract
Identifying promising targets is a critical step in modern drug discovery, with causative genes of diseases that are an important source of successful targets. Previous studies have found that the pathogeneses of various diseases are closely related to the evolutionary events of organisms. Accordingly, evolutionary knowledge can facilitate the prediction of causative genes and further accelerate target identification. With the development of modern biotechnology, massive biomedical data have been accumulated, and knowledge graphs (KGs) have emerged as a powerful approach for integrating and utilizing vast amounts of data. In this study, we constructed an evolution-strengthened knowledge graph (ESKG) and validated applications of ESKG in the identification of causative genes. More importantly, we developed an ESKG-based machine learning model named GraphEvo, which can effectively predict the targetability and the druggability of genes. We further investigated the explainability of the ESKG in druggability prediction by dissecting the evolutionary hallmarks of successful targets. Our study highlights the importance of evolutionary knowledge in biomedical research and demonstrates the potential power of ESKG in promising target identification. The data set of ESKG and the code of GraphEvo can be downloaded from https://github.com/Zhankun-Xiong/GraphEvo.
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Affiliation(s)
| | | | - Ke-Xin Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei 430070, P. R. China
| | - Qing-Ye Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei 430070, P. R. China
| | - Wen Zhang
- To whom correspondence should be addressed: ;
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