iDBPs: a web server for the identification of DNA binding proteins.
CONCLUSIONS
The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies.


BACKGROUND
http://idbps.tau.ac.il/
Nimrod
Guy
G
Department of Biochemistry, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel.
Schushan
Maya
M
Szilágyi
András
A
Leslie
Christina
C
Ben-Tal
Nir
N
D001665:Binding Sites; D004268:DNA-Binding Proteins / Q000737:chemistry*; D030562:Databases, Protein; D020407:Internet; D020539:Sequence Analysis, Protein; D012984:Software
D004268:DNA-Binding Proteins