SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of Metabolites-Reference-Cited by-同舟云学术

SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of Metabolites

Published:2008-05-19 Issue:5 Volume:3 Page:821-832
ISSN:1860-7179
Container-title:ChemMedChem
language:en
Short-container-title:ChemMedChem

Author:

Ridder Lars,Wagener Markus

Publisher

Wiley

Subject

Organic Chemistry,General Pharmacology, Toxicology and Pharmaceutics,Molecular Medicine,Drug Discovery,Biochemistry,Pharmacology

Reference45 articles.

1. Strategies for dealing with metabolite elucidation in drug discovery and development

2. Integration of Knowledge-Based Metabolic Predictions with Liquid Chromatography Data-Dependent Tandem Mass Spectrometry for Drug Metabolism Studies: Application to Studies on the Biotransformation of Indinavir

3. C. C. Hao, S. Campbell, D. Stranz, N. McSweeney, “Identification of In-Vitro Metabolites of Indinavir using Automated LC/MS/MS Acquisition, In-Silico Prediction, and Structure-Based Data Analysis”, Proceedings of the 52nd ASMS Conference 2004, Nashville (USA).

4. Computational Models for Cytochrome P450: A Predictive Electronic Model for Aromatic Oxidation and Hydrogen Atom Abstraction

5. A Model for Predicting Likely Sites of CYP3A4-mediated Metabolism on Drug-like Molecules

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