2021 Fiscal Year Research-status Report
On searching antimicrobial agents among natural products:Fighting against Superbug
| Project/Area Number |
20K12043
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| Research Institution | Nara Institute of Science and Technology |
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Principal Investigator |
AMIN MD.ALTAFUL 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 – 2023-03-31
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| Keywords | Antimicrobial / Natural products / Traditional Medicines / Lasso regression / Deep learning / Machine Learning / Graph Clustering |
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| Outline of Annual Research Achievements |
To find new natural product-derived antibiotics, the sizable empirical data generated from thousands of years of anti-infection practice of Traditional Chinese Medicine (TCM) should be fully utilized. By mapping the relevant networks including involving bacteria, antibiotics, TCM syndromes, formulae, natural products ingredients and metabolites, TCM formulae significant in the treatment of lung diseases were screened out and divided into binary groups according to whether their corresponding TCM syndromes reveal potential effects or not. Overall, a natural product ingredient-level TCM formula dataset were constructed, and supervised learning are carried out on whether the formula samples own the potential to fight infections in bacterial pneumonia. Regression and classification algorithms verified the validity of the dataset, and the features of natural product ingredient that are significant for efficacy were extracted from the maching learning models. The candidate natural products as new antibacterical agent were identified and validated by published literature and KNApSAcK Metabolite Activity database. The remains for which we predict novel associations with antimicrobial efficacy might be considered as candidates in the early step of the new antibiotic discovery cycle. In parallel, we developed a method for Antibacterial Activity Prediction of Plant Secondary Metabolites Based on a Combined Approach of Graph Clustering and Deep Neural Network utilizing data from KNApSAcK database and published our work in a journal
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Two PhD students are working with me and supporting to conduct the research well.
One of the PhD student Mr. Ahmad Kamal Nasution is working on finding natural antibiotic compounds based on Indonesian Jamu formulas. He already made a conference presentation and now working on a journal publication.
Another PhD student Mr. Gao Pei is working on finding natural antibiotic compounds based on Traditional Chinese medicine (TCM) formulas. He also published a conference paper and now preparing a journal paper.
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| Strategy for Future Research Activity |
This year we are preparing 2 manuscripts for publication. Both are on finding natural product based antibiotic compounds, one is based on Traditional Chinese Medicine (TCM) formulas and another is based on Indonesian Jamu formulas by applying different machine learning techniques including deep learning. Finally we will compare the results.
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| Causes of Carryover |
Because of Covid-19, we could not attend an international conference last year so we transferred the money to current year. We are planning to attend The 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Societye (EMBC), Glasgow, UK this year. Also the money will be utilized for publication costs of three journal papers we are planning to publish this year,
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[Journal Article] Identification of Targeted Proteins by Jamu Formulas for Different Efficacies Using Machine Learning Approach2021
Author(s)
Wijaya, S. H., Afendi, F. M., Batubara, I., Huang, M., Ono, N., Kanaya, S., & Altaf-Ul-Amin, M
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Journal Title
life
Volume: 11(8)
Pages: 866
DOI
Int'l Joint Research
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[Presentation] An Integrated Multi-Omics Approach for AMR Phenotype Prediction of Gut Microbiota2021
Author(s)
Gao, P., Chen, Z., Wang, D., Huang, M., Ono, N., Altaf-Ul-Amin, M., & Kanaya, S
Organizer
IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Int'l Joint Research
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[Presentation] Prediction of TCM Effective against Bacterial Pneumonia and Identification of Antibacterial Natural Product2021
Author(s)
Gao, P., Chen, Z., Huang, M., Ono, N., Amin, A., & Kanaya, S
Organizer
The 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Societye (EMBC)
Int'l Joint Research
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