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Molecules. 2015 Dec 23;21(1):E1. doi: 10.3390/molecules21010001.

Extended Functional Groups (EFG): An Efficient Set for Chemical Characterization and Structure-Activity Relationship Studies of Chemical Compounds.

Author information

1
Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, Freiberg D-09596, Germany. salmina@mailserver.tu-freiberg.de.
2
Department of Pharmaceutical Chemistry, University of Vienna, Althanstraße 14, Vienna A-1090, Austria. norbert.haider@univie.ac.at.
3
Institute of Structural Biology, Helmholtz Zentrum München-Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, b. 60w, Neuherberg D-85764, Germany. itetko@vcclab.org.
4
BigChem GmbH, Ingolstädter Landstraße 1, b. 60w, Neuherberg D-85764, Germany. itetko@vcclab.org.

Abstract

The article describes a classification system termed "extended functional groups" (EFG), which are an extension of a set previously used by the CheckMol software, that covers in addition heterocyclic compound classes and periodic table groups. The functional groups are defined as SMARTS patterns and are available as part of the ToxAlerts tool (http://ochem.eu/alerts) of the On-line CHEmical database and Modeling (OCHEM) environment platform. The article describes the motivation and the main ideas behind this extension and demonstrates that EFG can be efficiently used to develop and interpret structure-activity relationship models.

KEYWORDS:

chemical functional groups; chemoinformatics analysis; data interpretation; heterocyclic compounds; machine learning

PMID:
26703557
PMCID:
PMC6273096
DOI:
10.3390/molecules21010001
[Indexed for MEDLINE]
Free PMC Article

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