UpToDate
Official reprint from UpToDate®
www.uptodate.com ©2017 UpToDate, Inc. and/or its affiliates. All Rights Reserved.

Medline ® Abstract for Reference 41

of 'Clinical use of tyrosine kinase inhibitors for chronic myeloid leukemia'

41
TI
Molecular basis explanation for imatinib resistance of BCR-ABL due to T315I and P-loop mutations from molecular dynamics simulations.
AU
Lee TS, Potts SJ, Kantarjian H, Cortes J, Giles F, Albitar M
SO
Cancer. 2008;112(8):1744.
 
BACKGROUND: Computational simulations have become powerful tools for understanding detailed interactions in biologic systems. To the authors' knowledge to date, the mechanism of imatinib resistance in BCR-ABL has not been clarified at the atomic level, and computational studies are required.
METHODS: Molecular dynamics (MD) simulations on the complex of imatinib with the wild-type, T315I mutant, and 10 other P-loop mutants of the tyrosine kinase BCR-ABL were performed to study the mechanism of imatinib resistance.
RESULTS: Simulations suggested that imatinib resistance of T315I results mainly comes from the breakdown of interactions between imatinib and both E286 and M290, contradictory to what was believed previously, in that the missing hydrogen bonding is the main contribution. The current results also demonstrated that the unfavorable electrostatic interaction between P-loop and imatinib is the main reason for resistance for the P-loop mutations. Furthermore, in Y253H, protonation of the histidine at the epsilon position is essential for rendering this mutation resistant to imatinib.
CONCLUSIONS: The current results indicated that large-scale simulations may offer insight and information that other simple modeling methods cannot provide regarding the problem of BCR-ABL imatinib resistance, especially in the case of conformational changes because of remote mutations. Imatinib resistance mechanisms that were not anticipated previously were revealed by analyzing the interactions between imatinib and individual residues based on simulation results. This results demonstrated that MD is a powerful way to verify and predict the clinical response or resistance to imatinib and to other potential drugs.
AD
Consortium for Bioinformatics and Computational Biology and Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55414, USA. leex2750@umn.edu
PMID