ArticleCommunications biology2020
A combined computational and experimental strategy identifies mutations conferring resistance to drugs targeting the BCR-ABL fusion protein.
Article in Communications biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 15 citations in OpenAlex.
- In vitro and in silico modelling of ROS1-positive non-small cell lung cancer reveals fusion-dependent tyrosine kinase inhibitor responses.Molecular oncology · 2026Article
- The advancements in organoids: Potential and challenges in researching the esophagus and esophageal squamous cell carcinoma.Genes & diseases · 2026Review
- Predicting Mutational Effects on CaJournal of the American Chemical Society · 2024Article
- Prediction of Amino Acid Substitutions in ABL1 Protein Leading to Tumor Drug Resistance Based on "Structure-Property" Relationship Classification Models.Life (Basel, Switzerland) · 2023Article
- Structure-guided machine learning prediction of drug resistance mutations in Abelson 1 kinase.Computational and structural biotechnology journal · 2021Article
- Acquired rare recurrentAmerican journal of cancer research · 2020Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug resistance is of increasing concern, especially during the treatments of infectious diseases and cancer. To accelerate the drug discovery process in combating issues of drug resistance, here we developed a computational and experimental strategy to predict drug resistance mutations. Using BCR-ABL as a case study, we successfully recaptured the clinically observed mutations that confer resistance imatinib, nilotinib, dasatinib, bosutinib, and ponatinib. We then experimentally tested the predicted mutants in vitro. We found that although all mutants showed weakened binding strength as expected, the binding constants alone were not a good indicator of drug resistance. Instead, the half-maximal inhibitory concentration (IC
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