Structure-based prediction of BRAF mutation classes using machine-learning approaches

The BRAF kinase is crucial in oncology because its mutations can activate the MAP kinase pathway, causing cancer but also enabling targeted therapy. BRAF mutations are classified into three classes (I, II, III), aiding treatment decisions.
New BRAF kinase mutations often lack classification. To address this, we developed a machine learning tool to predict the class II and III of BRAF missense variants.
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These results are predictions based on knowledge at the date of the analysis, and are likely to be refined, completed or corrected over time, depending on scientific and technical advances. As not all biological aspects of an alteration can be taken into account, these results must be considered as indicative and, in no case, as a definitive argument for the choice of a therapeutic strategy.

BRAF Mutation Prediction
BRAF mutation request Links to protein databases
BRAF mutation prediction result

Waiting for a BRAF kinase mutation

3D structure
Hydrogen bonds
Ionic interactions
Cation-π interactions
Hydrophobic contacts
π-stacking interactions
Orthologous sequence alignment
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RAF subfamily sequence alignment
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TKL Ser/Thr protein kinase family sequence alignment
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Orthologous sequence alignment (extended)
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