期刊
NUCLEIC ACIDS RESEARCH
卷 43, 期 11, 页码 5340-5351出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkv446
关键词
-
资金
- French Government [ANR-10-BINF-02--02 BACNET]
We describe a general binding score for predicting the nucleic acid binding probability in proteins. The score is directly derived from physicochemical and evolutionary features and integrates a residue neighboring network approach. Our process achieves stable and high accuracies on both DNA- and RNA-binding proteins and illustrates how the main driving forces for nucleic acid binding are common. Because of the effective integration of the synergetic effects of the network of neighboring residues and the fact that the prediction yields a hierarchical scoring on the protein surface, energy funnels for nucleic acid binding appear on protein surfaces, pointing to the dynamic process occurring in the binding of nucleic acids to proteins.
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