標題: An integrated approach with new strategies for QSAR models and lead optimization
作者: Hsu, Hui-Hui
Hsu, Yen-Chao
Chang, Li-Jen
Yang, Jinn-Moon
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
關鍵字: QSAR model;Computational drug design;Molecular docking
公開日期: 1-Jan-2017
摘要: Background: Computational drug design approaches are important for shortening the time and reducing the cost for drug discovery and development. Among these methods, molecular docking and quantitative structure activity relationship (QSAR) play key roles for lead discovery and optimization. Here, we propose an integrated approach with core strategies to identify the protein-ligand hot spots for QSAR models and lead optimization. These core strategies are: 1) to generate both residue-based and atom-based interactions as the features; 2) to identify compound common and specific skeletons; and 3) to infer consensus features for QSAR models. Results: We evaluated our methods and new strategies on building QSAR models of human acetylcholinesterase (huAChE). The leave-one-out cross validation values q(2) and r(2) of our huAChE QSAR model are 0.82 and 0.78, respectively. The experimental results show that the selected features (resides/atoms) are important for enzymatic functions and stabling the protein structure by forming key interactions (e.g., stack forces and hydrogen bonds) between huAChE and its inhibitors. Finally, we applied our methods to arthrobacter globiformis histamine oxidase (AGHO) which is correlated to heart failure and diabetic. Conclusions: Based on our AGHO QSAR model, we identified a new substrate verified by bioassay experiments for AGHO. These results show that our methods and new strategies can yield stable and high accuracy QSAR models. We believe that our methods and strategies are useful for discovering new leads and guiding lead optimization in drug discovery.
URI: http://dx.doi.org/10.1186/s12864-017-3503-2
http://hdl.handle.net/11536/146052
ISSN: 1471-2164
DOI: 10.1186/s12864-017-3503-2
期刊: BMC GENOMICS
Volume: 18
起始頁: 0
結束頁: 0
Appears in Collections:Articles


Files in This Item:

  1. 25ba7c203686f18ea89d43d208959044.pdf