Ab initio modeling led annotation suggests nucleic acid binding function for many DUFs.

Expansions of sequence databases driven by new sequencing technology continue apace. These result in a continuous supply of protein sequences and domains that cannot be straightforwardly annotated by simple homology methods. For these, structure-based function prediction may contribute to an improved annotation. Here, short Domains of Unknown Function (DUFs) are ab initio modeled with and screened for likely nucleic acid binding function. Thirty-two DUFs are thereby predicted to have a nucleic acid binding function. In most cases, additional evidence supporting that function could be obtained from structure comparison, domain architectures, distant evolutionary relationships, genome context or protein-protein interaction data. These predictions contribute to the function annotation of thousands of proteins.

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