A computational approach to analyze the mechanism of action of the kinase inhibitor bafetinib.

Abstract

Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. We present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. We apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, we propose potential treatment of lung cancer and IGF1R expressing blast crisis.

• Authors: Thomas R Burkard, Uwe Rix, Florian P Breitwieser, Giulio Superti-Furga, Jacques Colinge
• Journal: PLoS computational biology (PLoS Comput Biol) Vol. 6 Issue 11 Pg. e1001001 (Nov 18 2010) ISSN: 1553-7358 [Electronic] United States
• PMID: 21124949 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• Antineoplastic Agents
• Protein Kinase Inhibitors
• Pyrimidines
• EGFR protein, human
• ErbB Receptors
• bafetinib

Topics

• Antineoplastic Agents (chemistry, pharmacology)
• Apoptosis (drug effects)
• ErbB Receptors (metabolism)
• Humans
• Leukemia, Myelogenous, Chronic, BCR-ABL Positive (drug therapy, enzymology)
• Models, Biological
• Protein Interaction Domains and Motifs
• Protein Interaction Mapping (methods)
• Protein Kinase Inhibitors (chemistry, pharmacology)
• Proteomics (methods)
• Pyrimidines (chemistry, pharmacology)
• Signal Transduction (drug effects)