An ensemble learning framework for protein stability prediction with enhanced recognition of stabilizing mutations.

Abstract excerpt

Accurately predicting mutation-induced protein stability changes remains a central challenge in structural bioinformatics. Existing methods exhibit a strong bias toward destabilizing mutations, leading to limited performance for stabilizing mutations and constraining their utility in protein engineering. Here, we address this limitation through two complementary strategies: balanced dataset construction and...

Topics

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• Computational Biology
• Databases, Protein
• Models, Molecular
• Mutation
• Prediction Algorithms