2023 Fiscal Year Final Research Report
On searching antimicrobial agents among natural products:Fighting against Superbug
| Project/Area Number |
20K12043
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 62010:Life, health and medical informatics-related
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| Research Institution | Nara Institute of Science and Technology |
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Principal Investigator |
Amin Md Altaf Ul 奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (30379531)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | Natural antibiotics / Traditional medicines / Machine learning / Jamu formulas / TCM formulas |
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| Outline of Final Research Achievements |
Antibiotic resistance is a major public health threat and there is an urgent need for new antibiotics. Traditional herbal medicine systems, such as Jamu, Unani, and Traditional Chinese Medicine, have been used for finding new antibiotics by applying machine learning algorithms. In total, we predicted 42 potential plant candidates and 201 candidate metabolites as potential natural antibiotics. We published 4 journal papers (with IF > 4) and two IEEE conference papers using the results of this research. With this KAKENHI money we also conducted some other related researches.
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| Free Research Field |
Systems Biology
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| Academic Significance and Societal Importance of the Research Achievements |
Our research focused on finding natural antibiotic compounds based on traditional medicine formulas by applying various machine learning algorithms. By further investigation if some of our predicted antibiotics can be used in clinical practice it would be of great scientific and social significance.
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