Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations Journal Article


Authors: Hauser, K.; Negron, C.; Albanese, S. K.; Ray, S.; Steinbrecher, T.; Abel, R.; Chodera, J. D.; Wang, L.
Article Title: Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations
Abstract: 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.
Keywords: bcr-abl; chronic myeloid-leukemia; c-abl; protonation; domain mutations; molecular-dynamics; accurate; cancer drug-resistance; sh2 domain; binding free-energy
Journal Title: Communications Biology
Volume: 1
ISSN: 2399-3642
Publisher: Springer Nature  
Date Published: 2018-01-01
Start Page: 70
Language: English
ACCESSION: WOS:000461126500070
DOI: 10.1038/s42003-018-0075-x
PROVIDER: wos
PMCID: PMC6110136
PUBMED: 30159405
Notes: Alternate DOI also available, see: 10.1101/239012 -- Source: Wos
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  1. John Damon Chodera
    118 Chodera