当前位置: X-MOL 学术Chem. Lett. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Regression Modeling and Virtual Screening of Natural Products Exhibiting Antibacterial Activity. An Application of Electronic-Structure Informatics Descriptors
Chemistry Letters ( IF 1.6 ) Pub Date : 2021-02-13 , DOI: 10.1246/cl.200966
Toshihiro Ideo 1 , Kazuki Yoshida 1 , Manabu Sugimoto 1, 2
Affiliation  

Machine learning using descriptors suggested for “electronic-structure informatics (ESI)” is carried out to establish a regression model for antibacterial activity of 60 natural products. The obtained model is used for the in-house data containing 175 molecules. The screening result is justified through literature survey in which, at least, 13 compounds listed in the top 20 compounds are shown to have the antibacterial activity.

中文翻译:

具有抗菌活性的天然产物的回归建模和虚拟筛选。电子结构信息学描述符的应用

使用建议用于“电子结构信息学(ESI)”的描述符进行机器学习,以建立60种天然产物抗菌活性的回归模型。获得的模型用于包含175个分子的内部数据。通过文献调查证明筛选结果是合理的,在文献调查中,显示出前20种化合物中至少有13种化合物具有抗菌活性。
更新日期:2021-02-15
down
wechat
bug