Conformation-independent QSAR on c-Src tyrosine kinase inhibitors

Nieves C. Comelli, Erlinda V. Ortiz, Magdalena Kolacz, Alla P. Toropova, Andrey A. Toropov, Pablo R. Duchowicz, Eduardo A. Castro

Research output: Contribution to journalArticle

Abstract

The main idea of this work was to find predictive quantitative structure-activity relationships (QSAR) for a wide set of c-Src tyrosine kinase inhibitors, by means of resorting to a conformation-independent representation of the chemical structure. In this way, our attempt was to avoid the availability of X-ray crystallographic structural information of the target. Therefore, in a set composed of 80 pyrrolo-pyrimidine derivatives, 1179 theoretical descriptors were simultaneously analyzed through linear regression models obtained with the replacement method variable subset selection technique. Alternatively, the flexible (activity dependent) descriptor approach was also applied in this study. The models were validated and tested through the use of an external test set of compounds, the leave-group-out cross validation method, Y-randomization and applicability domain analysis. Our results were compared with previously published ones based on docking analysis and 3D-QSAR. The obtained conformation-independent approach was in good agreement with experimental observations.

Original languageEnglish
Pages (from-to)47-52
Number of pages6
JournalChemometrics and Intelligent Laboratory Systems
Volume134
DOIs
Publication statusPublished - May 15 2014

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Keywords

  • C-Src tyrosine kinase
  • Multivariable linear regression analysis
  • Pyrrolo-pyrimidine derivatives
  • QSAR theory
  • Structural descriptors

ASJC Scopus subject areas

  • Spectroscopy
  • Analytical Chemistry
  • Computer Science Applications
  • Software
  • Process Chemistry and Technology

Cite this

Comelli, N. C., Ortiz, E. V., Kolacz, M., Toropova, A. P., Toropov, A. A., Duchowicz, P. R., & Castro, E. A. (2014). Conformation-independent QSAR on c-Src tyrosine kinase inhibitors. Chemometrics and Intelligent Laboratory Systems, 134, 47-52. https://doi.org/10.1016/j.chemolab.2014.03.003