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Probabilistic Predictive Model of the Human Liver Microsomal Metabolism Regioselectivity
EP20446
Poster Title: Probabilistic Predictive Model of the Human Liver Microsomal Metabolism Regioselectivity
Submitted on 19 Dec 2013
Author(s): Justas Dapkunas, Andrius Sazonovas, Pranas Japertas
Affiliations: ACD Labs
Poster Views: 1,435
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Poster Information
Abstract: 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).
Summary: Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task which is performed only in late drug development phases.Therefore, the ability to predict possible sites of human liver microsomal metabolism using in silico techniques would be highly beneficial for any medicinal chemist.Report abuse »
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