J Chem Inf Model - Metabolism site prediction based on xenobiotic structural formulas and PASS prediction algorithm.

Tópicos

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Resumo

A new ligand-based method for the prediction of sites of metabolism (SOMs) for xenobiotics has been developed on the basis of the LMNA (labeled multilevel neighborhoods of atom) descriptors and the PASS (prediction of activity spectra for substances) algorithm and applied to predict the SOMs of the 1A2, 2C9, 2C19, 2D6, and 3A4 isoforms of cytochrome P450. An average IAP (invariant accuracy of prediction) of SOMs calculated by the leave-one-out cross-validation procedure was 0.89 for the developed method. The external validation was made with evaluation sets containing data on biotransformations for 57 cardiovascular drugs. An average IAP of regioselectivity for evaluation sets was 0.83. It was shown that the proposed method exceeds accuracy of SOM prediction by RS-Predictor for CYP 1A2, 2D6, 2C9, 2C19, and 3A4 and is comparable to or better than SMARTCyp for CYP 2C9 and 2D6.

Resumo Limpo

new ligandbas method predict site metabol som xenobiot develop basi lmna label multilevel neighborhood atom descriptor pass predict activ spectra substanc algorithm appli predict som c c d isoform cytochrom p averag iap invari accuraci predict som calcul leaveoneout crossvalid procedur develop method extern valid made evalu set contain data biotransform cardiovascular drug averag iap regioselect evalu set shown propos method exceed accuraci som predict rspredictor cyp d c c compar better smartcyp cyp c d

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