A topological machine learning model integrating persistent Laplacian, physicochemical, and ESM-2 features predicts mutation-induced binding affinity changes for protein-DNA and protein-RNA complexes with reported state-of-the-art accuracy.
Comprehensive review and empirical analysis of hallmarks of dna-, rna-and protein-binding residues in protein chains
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
q-bio.QM 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Topological Machine Learning for Protein-Nucleic Acid Binding Affinity Changes Upon Mutation
A topological machine learning model integrating persistent Laplacian, physicochemical, and ESM-2 features predicts mutation-induced binding affinity changes for protein-DNA and protein-RNA complexes with reported state-of-the-art accuracy.