An In Silico Method for Screening Nicotine Derivatives as Cytochrome P450 2A6 Selective Inhibitors Based on Kernel Partial Least Squares

International Journal of Molecular Sciences

Yonghua Wang²  Yan Li¹ 

[1] School of Chemical Engineering, Dalian University of Technology, Dalian 116012, China.;School of Life Science and Technology, Dalian Fisheries University, Dalian 116023, China.

关键词: Kernel partial least squares;    CYP2A6;    nicotine derivatives;    inhibitors;   

DOI  :  10.3390/i8020166

来源: mdpi

【 摘 要 】

Nicotine and a variety of other drugs and toxins are metabolized by cytochrome P450 (CYP) 2A6. The aim of the present study was to build a quantitative structure-activity relationship (QSAR) model to predict the activities of nicotine analogues on CYP2A6. Kernel partial least squares (K-PLS) regression was employed with the electro-topological descriptors to build the computational models. Both the internal and external predictabilities of the models were evaluated with test sets to ensure their validity and reliability. As a comparison to K-PLS, a standard PLS algorithm was also applied on the same training and test sets. Our results show that the K-PLS produced reasonable results that outperformed the PLS model on the datasets. The obtained K-PLS model will be helpful for the design of novel nicotine-like selective CYP2A6 inhibitors.

【 授权许可】

Unknown   
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