ArticleCancer research2016
Balancing Protein Stability and Activity in Cancer: A New Approach for Identifying Driver Mutations Affecting CBL Ubiquitin Ligase Activation.
Article in Cancer research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 35 citations in OpenAlex.
- An interpretable molecular framework for predicting cancer driver missense mutations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Predicting thermostability difference between cellular protein orthologs.Bioinformatics (Oxford, England) · 2023Article
- Cancer driver mutations: predictions and reality.Trends in molecular medicine · 2023Review
- Review
- A critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.Briefings in bioinformatics · 2020Review
- AlloSigMA 2: paving the way to designing allosteric effectors and to exploring allosteric effects of mutations.Nucleic acids research · 2020Article
- MutaBind2: Predicting the Impacts of Single and Multiple Mutations on Protein-Protein Interactions.iScience · 2020Article
- Molecular Biology and Evolution of Cancer: From Discovery to Action.Molecular biology and evolution · 2020Article
- Finding driver mutations in cancer: Elucidating the role of background mutational processes.PLoS computational biology · 2019Article
- Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers.PLoS computational biology · 2019Review
- PremPDI estimates and interprets the effects of missense mutations on protein-DNA interactions.PLoS computational biology · 2018Article
- Mutational signatures and mutable motifs in cancer genomes.Briefings in bioinformatics · 2018Review
- Computational Approaches to Prioritize Cancer Driver Missense Mutations.International journal of molecular sciences · 2018Review
- Exploring background mutational processes to decipher cancer genetic heterogeneity.Nucleic acids research · 2017Article
- Annotating Mutational Effects on Proteins and Protein Interactions: Designing Novel and Revisiting Existing Protocols.Methods in molecular biology (Clifton, N.J.) · 2017Article
- MutaBind estimates and interprets the effects of sequence variants on protein-protein interactions.Nucleic acids research · 2016Article
- Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Oncogenic mutations in the monomeric Casitas B-lineage lymphoma (Cbl) gene have been found in many tumors, but their significance remains largely unknown. Several human c-Cbl (CBL) structures have recently been solved, depicting the protein at different stages of its activation cycle and thus providing mechanistic insight underlying how stability-activity tradeoffs in cancer-related proteins-may influence disease onset and progression. In this study, we computationally modeled the effects of missense cancer mutations on structures representing four stages of the CBL activation cycle to identify driver mutations that affect CBL stability, binding, and activity. We found that recurrent, homozygous, and leukemia-specific mutations had greater destabilizing effects on CBL states than random noncancer mutations. We further tested the ability of these computational models, assessing the changes in CBL stability and its binding to ubiquitin-conjugating enzyme E2, by performing blind CBL-mediated EGFR ubiquitination assays in cells. Experimental CBL ubiquitin ligase activity was in agreement with the predicted changes in CBL stability and, to a lesser extent, with CBL-E2 binding affinity. Two thirds of all experimentally tested mutations affected the ubiquitin ligase activity by either destabilizing CBL or disrupting CBL-E2 binding, whereas about one-third of tested mutations were found to be neutral. Collectively, our findings demonstrate that computational methods incorporating multiple protein conformations and stability and binding affinity evaluations can successfully predict the functional consequences of cancer mutations on protein activity, and provide a proof of concept for mutations in CBL.
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