Document Detail


Classifying "kinase inhibitor-likeness" by using machine-learning methods.
MedLine Citation:
PMID:  15696507     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
By using an in-house data set of small-molecule structures, encoded by Ghose-Crippen parameters, several machine learning techniques were applied to distinguish between kinase inhibitors and other molecules with no reported activity on any protein kinase. All four approaches pursued--support-vector machines (SVM), artificial neural networks (ANN), k nearest neighbor classification with GA-optimized feature selection (GA/kNN), and recursive partitioning (RP)--proved capable of providing a reasonable discrimination. Nevertheless, substantial differences in performance among the methods were observed. For all techniques tested, the use of a consensus vote of the 13 different models derived improved the quality of the predictions in terms of accuracy, precision, recall, and F1 value. Support-vector machines, followed by the GA/kNN combination, outperformed the other techniques when comparing the average of individual models. By using the respective majority votes, the prediction of neural networks yielded the highest F1 value, followed by SVMs.
Authors:
Hans Briem; Judith Günther
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Chembiochem : a European journal of chemical biology     Volume:  6     ISSN:  1439-4227     ISO Abbreviation:  Chembiochem     Publication Date:  2005 Mar 
Date Detail:
Created Date:  2005-03-09     Completed Date:  2005-06-22     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100937360     Medline TA:  Chembiochem     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  558-66     Citation Subset:  IM    
Affiliation:
Schering AG, Research Center Europe, CDCC/Computational Chemistry, Muellerstrasse 178, 13342 Berlin, Germany. hans.briem@schering.de
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Computational Biology / methods*
Computer Simulation*
Molecular Structure
Neural Networks (Computer)
Protein Kinase Inhibitors / chemistry*,  classification*
Reproducibility of Results
Sensitivity and Specificity
Chemical
Reg. No./Substance:
0/Protein Kinase Inhibitors

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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