Probabilistic Predictive Model of the Human Liver Microsomal Metabolism Regioselectivity
Poster Dec 07, 2010
Justas Dapkunas, Andrius Sazonovas, Pranas Japertas
Moreover, in silico predictions of the most likely metabolism sites in a molecule could facilitate the
analysis of spectroscopic data and thus ease the experimental identification of metabolites.
In this work, we present QSAR models for the prediction of metabolism regioselectivity. They provide the probability to be metabolized in human liver microsomes for every atom of the molecule and are based on a novel GALAS (Global, Adjusted Locally According to Similarity) methodology – an approach enabling the evaluation of Model Applicability Domain via the calculation of the prediction Reliability Index (RI).
We developed an automated sample preparation protocol based on a robotic platform PAL RTC (CTC Analytics AG, Zwingen Switzerland), which represent a modified Bligh and Dyer method producing samples for both hydrophilic metabolomics using GC-MS and lipidomics using SFC-MS simultaneously.READ MORE
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