Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents
Repositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. Computational technologies such as machine learning methods have accelerated the process of drug repositioning in the la...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037022002136 |
| _version_ | 1828087984123019264 |
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| author | Sha Zhu Qifeng Bai Lanqing Li Tingyang Xu |
| author_facet | Sha Zhu Qifeng Bai Lanqing Li Tingyang Xu |
| author_sort | Sha Zhu |
| collection | DOAJ |
| description | Repositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. Computational technologies such as machine learning methods have accelerated the process of drug repositioning in the last few decades years. The repositioning potential of type 2 diabetes mellitus (T2DM) drugs for various diseases such as cancer, neurodegenerative diseases, and cardiovascular diseases have been widely studied. Hence, the related summary about repurposing antidiabetic drugs is of great significance. In this review, we focus on the machine learning methods for the development of new T2DM drugs and give an overview of the repurposing potential of the existing antidiabetic agents. |
| first_indexed | 2024-04-11T05:19:44Z |
| format | Article |
| id | doaj.art-a0ff253cb2fc4394aaef611c067ae487 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-04-11T05:19:44Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-a0ff253cb2fc4394aaef611c067ae4872022-12-24T04:52:48ZengElsevierComputational and Structural Biotechnology Journal2001-03702022-01-012028392847Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agentsSha Zhu0Qifeng Bai1Lanqing Li2Tingyang Xu3Key Lab of Preclinical Study for New Drugs of Gansu Province, Institute of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu 730000, PR ChinaKey Lab of Preclinical Study for New Drugs of Gansu Province, Institute of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu 730000, PR China; Corresponding author.Tencent AI Lab, Shenzhen, PR ChinaTencent AI Lab, Shenzhen, PR ChinaRepositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. Computational technologies such as machine learning methods have accelerated the process of drug repositioning in the last few decades years. The repositioning potential of type 2 diabetes mellitus (T2DM) drugs for various diseases such as cancer, neurodegenerative diseases, and cardiovascular diseases have been widely studied. Hence, the related summary about repurposing antidiabetic drugs is of great significance. In this review, we focus on the machine learning methods for the development of new T2DM drugs and give an overview of the repurposing potential of the existing antidiabetic agents.http://www.sciencedirect.com/science/article/pii/S2001037022002136Drug repositioningDrug repurposingT2DMMachine learningDeep learningAntidiabetic drugs |
| spellingShingle | Sha Zhu Qifeng Bai Lanqing Li Tingyang Xu Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents Computational and Structural Biotechnology Journal Drug repositioning Drug repurposing T2DM Machine learning Deep learning Antidiabetic drugs |
| title | Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents |
| title_full | Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents |
| title_fullStr | Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents |
| title_full_unstemmed | Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents |
| title_short | Drug repositioning in drug discovery of T2DM and repositioning potential of antidiabetic agents |
| title_sort | drug repositioning in drug discovery of t2dm and repositioning potential of antidiabetic agents |
| topic | Drug repositioning Drug repurposing T2DM Machine learning Deep learning Antidiabetic drugs |
| url | http://www.sciencedirect.com/science/article/pii/S2001037022002136 |
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