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Int. J. Mol. Sci. 2007, 8(2), 166-179; https://doi.org/10.3390/i8020166

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

1
School of Life Science and Technology, Dalian Fisheries University, Dalian 116023, P.R. China.
2
School of Chemical Engineering, Dalian University of Technology, Dalian 116012, P.R. China
*
Author to whom correspondence should be addressed.
Received: 13 December 2006 / Accepted: 19 January 2007 / Published: 28 February 2007
(This article belongs to the Special Issue Interaction of Biological Molecules)
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Abstract

Nicotine and a variety of other drugs and toxins are metabolized by cytochromeP450 (CYP) 2A6. The aim of the present study was to build a quantitative structure-activityrelationship (QSAR) model to predict the activities of nicotine analogues on CYP2A6.Kernel partial least squares (K-PLS) regression was employed with the electro-topologicaldescriptors to build the computational models. Both the internal and external predictabilitiesof the models were evaluated with test sets to ensure their validity and reliability. As acomparison to K-PLS, a standard PLS algorithm was also applied on the same training andtest sets. Our results show that the K-PLS produced reasonable results that outperformed thePLS model on the datasets. The obtained K-PLS model will be helpful for the design ofnovel nicotine-like selective CYP2A6 inhibitors. View Full-Text
Keywords: Kernel partial least squares; CYP2A6; nicotine derivatives; inhibitors Kernel partial least squares; CYP2A6; nicotine derivatives; inhibitors
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Wang, Y.; Li, Y.; Wang, B. An In Silico Method for Screening Nicotine Derivatives as Cytochrome P450 2A6 Selective Inhibitors Based on Kernel Partial Least Squares. Int. J. Mol. Sci. 2007, 8, 166-179.

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