期刊
COMMUNICATIONS BIOLOGY
卷 1, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/s42003-018-0075-x
关键词
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资金
- NIH National Cancer Institute Cancer Center Core Grant [P30 CA008748]
- Sloan Kettering Institute, Cycle for Survival
- NIH [R01 GM121505]
- NATIONAL CANCER INSTITUTE [P30CA008748] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM121505] Funding Source: NIH RePORTER
The therapeutic effect of targeted kinase inhibitors can be significantly reduced by intrinsic or acquired resistance mutations that modulate the affinity of the drug for the kinase. In cancer, the majority of missense mutations are rare, making it difficult to predict their impact on inhibitor affinity. We examine the potential for alchemical free-energy calculations to predict how kinase mutations modulate inhibitor affinities to Abl, a major target in chronic myelogenous leukemia (CML). These calculations have useful accuracy in predicting resistance for eight FDA-approved kinase inhibitors across 144 clinically identified point mutations, with a root mean square error in binding free-energy changes of 1.1(0.9)(1.3) kcal mol(-1) (95% confidence interval) and correctly classifying mutations as resistant or susceptible with 88(82)(93)% accuracy. This benchmark establishes the potential for physical modeling to collaboratively support the assessment and anticipation of patient mutations to affect drug potency in clinical applications.
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