Automatic functional annotation of predicted active sites - European ...

equires the identification of chemical functions, which could be found in the context
of residue mentions. MEDLINE abstracts have been processed to identify protein mentions
in combination with species and residues (F1-measure 0.52; the F1-measure is a
statistical measure of a test’s accuracy based on the precision and recall of a test). The
identified protein-species-residue triplets have been validated and benchmarked against
reference data resources. Then, contextual features were extracted through shallow and
deep parsing and the features have been classified into predefined categories (F1-measure
ranges from 0.15 to 0.67). Furthermore, the feature sets have been aligned with annotation
types in UniProtKB to assess the relevance of the annotations for ongoing curation
projects.
Altogether, the annotations have been assessed automatically and manually
against reference data resources.
All MEDLINE has been processed to filter out annotations for residues. A subset of
identified catalytic sites could be cross-validated against the Catalytic Site Atlas (CSA;
44 out of 221). 429 out of 512 protein residues from MSDsite was then annotated with
contextual data. Altogether, MEDLINE does not provide sufficient data to fully annotate
the content from PDB. Conversely, residue annotation is achieved with a different feature
set than provided from GO, and incomplete annotations in the reference datasets can be
filled from public literature.
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