Classification and QSAR models of leukotriene A4 hydrolase (LTA4H) inhibitors by machine learning methods-Reference-Cited by-同舟云学术

Classification and QSAR models of leukotriene A4 hydrolase (LTA4H) inhibitors by machine learning methods

Published:2021-04-26 Issue:5 Volume:32 Page:411-431
ISSN:1062-936X
Container-title:SAR and QSAR in Environmental Research
language:en
Short-container-title:SAR and QSAR in Environmental Research

Author:

Qin R.¹,Wang H.¹,Yan A.¹

Affiliation:

1. State Key Laboratory of Chemical Resource Engineering Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, Beijing, P. R. China

Publisher

Informa UK Limited

Subject

Drug Discovery,Molecular Medicine,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/1062936X.2021.1910862

Reference58 articles.

1. Azabenzthiazole inhibitors of leukotriene A4 hydrolase

2. Development of predictive quantitative structure–activity relationship model and its application in the discovery of human leukotriene A4 hydrolase inhibitors

3. Binding of Pro-Gly-Pro at the active site of leukotriene A4 hydrolase/aminopeptidase and development of an epoxide hydrolase selective inhibitor

4. PENG: A Neural Gas-Based Approach for Pharmacophore Elucidation. Method Design, Validation, and Virtual Screening for Novel Ligands of LTA4H

5. Recent advances in clinical development of leukotriene B4 pathway drugs

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