Title
FunFam protein families improve residue level molecular function prediction.
Abstract
The CATH database provides a hierarchical classification of protein domain structures including a sub-classification of superfamilies into functional families (FunFams). We analyzed the similarity of binding site annotations in these FunFams and incorporated FunFams into the prediction of protein binding residues. FunFam members agreed, on average, in 36.9 ± 0.6% of their binding residue annotations. This constituted a 6.7-fold increase over randomly grouped proteins and a 1.2-fold increase (1.1-fold on the same dataset) over proteins with the same enzymatic function (identical Enzyme Commission, EC, number). Mapping de novo binding residue prediction methods (BindPredict-CCS, BindPredict-CC) onto FunFam resulted in consensus predictions for those residues that were aligned and predicted alike (binding/non-binding) within a FunFam. This simple consensus increased the F1-score (for binding) 1.5-fold over the original prediction method. Variation of the threshold for how many proteins in the consensus prediction had to agree provided a convenient control of accuracy/precision and coverage/recall, e.g. reaching a precision as high as 60.8 ± 0.4% for a stringent threshold. The FunFams outperformed even the carefully curated EC numbers in terms of agreement of binding site residues. Additionally, we assume that our proof-of-principle through the prediction of protein binding residues will be relevant for many other solutions profiting from FunFams to infer functional information at the residue level.
Year
DOI
Venue
2019
10.1186/s12859-019-2988-x
BMC Bioinformatics
Keywords
DocType
Volume
Protein function, Protein families, Functional families, Binding residue prediction, Protein binding sites, CATH
Journal
20
Issue
ISSN
Citations 
1
1471-2105
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Linus Scheibenreif110.35
Maria Littmann230.76
Christine Orengo3957.99
Burkhard Rost479588.14