ArticleeLife2016
The yin-yang of kinase activation and unfolding explains the peculiarity of Val600 in the activation segment of BRAF.
Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 37 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
- Colorectal cancer tumor phenotypes associated withWorld journal of gastrointestinal pathophysiology · 2025Article
- PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context.Nature communications · 2025Article
- A structure-based tool to interpret the significance of kinase mutations in clinical next generation sequencing in cancer.Frontiers in oncology · 2025Article
- DNA Sequencing of CD138 Cell Population Reveals TP53 and RAS-MAPK Mutations in Multiple Myeloma at Diagnosis.Cancers · 2024Article
- Non-Equilibrium Protein Folding and Activation by ATP-Driven Chaperones.Biomolecules · 2022Article
- PTMsnp: A Web Server for the Identification of Driver Mutations That Affect Protein Post-translational Modification.Frontiers in cell and developmental biology · 2020Article
- Article
- Integration of Random Forest Classifiers and Deep Convolutional Neural Networks for Classification and Biomolecular Modeling of Cancer Driver Mutations.Frontiers in molecular biosciences · 2019Article
- Article
- Review
- Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations.PLoS genetics · 2017Article
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- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many driver mutations in cancer are specific in that they occur at significantly higher rates than - presumably - functionally alternative mutations. For example, V600E in the BRAF hydrophobic activation segment (AS) pocket accounts for >95% of all kinase mutations. While many hypotheses tried to explain such significant mutation patterns, conclusive explanations are lacking. Here, we use experimental and in silico structure-energy statistical analyses, to elucidate why the V600E mutation, but no other mutation at this, or any other positions in BRAF's hydrophobic pocket, is predominant. We find that BRAF mutation frequencies depend on the equilibrium between the destabilization of the hydrophobic pocket, the overall folding energy, the activation of the kinase and the number of bases required to change the corresponding amino acid. Using a random forest classifier, we quantitatively dissected the parameters contributing to BRAF AS cancer frequencies. These findings can be applied to genome-wide association studies and prediction models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.