2018 Fiscal Year Annual Research Report
A new rotation-translation invariant molecular encoding and its use in Computer-Aided Drug-Discovery
| Project/Area Number |
17F17051
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
山西 芳裕 九州工業大学, 大学院情報工学研究院, 教授 (60437267)
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| Co-Investigator(Kenkyū-buntansha) |
BERENGER FRANCOIS 九州工業大学, 大学院情報工学研究院, 外国人特別研究員
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| Project Period (FY) |
2017-07-26 – 2019-03-31
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| Keywords | LBVS / QSAR / applicability domain |
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| Outline of Annual Research Achievements |
I have been working on computational methods on chemoinformatics research. I have created the "Distance-Based Boolean Applicability Domain". In ligand-based modeling, one must create a model but also an applicability domain for that model. Existing methods are complex, hard to implement or difficult to interpret. They require a threshold or embed an empiric constant. I proposed a trivial to interpret domain. In High Throughput Screening data set modeling experiments, our domain improves the performance and early retrieval of models, while improving the scaffold diversity among top-ranked active molecules. I have published two articles in peer reviewed journals and presented posters at international conferences. I have released open source programs and libraries for chemoinformatics research. I have done some modeling for protein targets of interest to our team.
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| Research Progress Status |
平成30年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
平成30年度が最終年度であるため、記入しない。
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