Literature DB >> 17125191

Emerging chemical patterns: a new methodology for molecular classification and compound selection.

Jens Auer1, Jürgen Bajorath.   

Abstract

A concept termed Emerging Chemical Patterns (ECPs) is introduced as a novel approach to molecular classification. The methodology makes it possible to extract key molecular features from very few known active compounds and classify molecules according to different potency levels. The approach was developed in light of the situation often faced during the early stages of lead optimization efforts: too few active reference molecules are available to build computational models for the prediction of potent compounds. The ECP method generates high-resolution signatures of active compounds. Predictive ECP models can be built based on the information provided by sets of only three molecules with potency in the nanomolar and micromolar range. In addition to individual compound predictions, an iterative ECP scheme has been designed. When applied to different sets of active molecules, iterative ECP classification produced compound selection sets with increases in average potency of up to 3 orders of magnitude.

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Year:  2006        PMID: 17125191     DOI: 10.1021/ci600301t

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  3 in total

Review 1.  Automated detection of structural alerts (chemical fragments) in (eco)toxicology.

Authors:  Alban Lepailleur; Guillaume Poezevara; Ronan Bureau
Journal:  Comput Struct Biotechnol J       Date:  2013-04-06       Impact factor: 7.271

2.  Machine learning algorithms for mode-of-action classification in toxicity assessment.

Authors:  Yile Zhang; Yau Shu Wong; Jian Deng; Cristina Anton; Stephan Gabos; Weiping Zhang; Dorothy Yu Huang; Can Jin
Journal:  BioData Min       Date:  2016-05-13       Impact factor: 2.522

3.  Bioalerts: a python library for the derivation of structural alerts from bioactivity and toxicity data sets.

Authors:  Isidro Cortes-Ciriano
Journal:  J Cheminform       Date:  2016-03-04       Impact factor: 5.514

  3 in total

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