Prediction of beta-strand packing interactions using the signature product.
The prediction of beta-sheet topology requires the consideration of long-range interactions between beta-strands that are not necessarily consecutive in sequence. Since these interactions are difficult to simulate using ab initio methods, we propose a supplementary method able to assign beta-sheet topology using only sequence information. We envision using the results of our method to reduce the three-dimensional search space of ab initio methods. Our method is based on the signature molecular descriptor, which has been used previously to predict protein-protein interactions successfully, and to develop quantitative structure-activity relationships for small organic drugs and peptide inhibitors. Here, we show how the signature descriptor can be used in a Support Vector Machine to predict whether or not two beta-strands will pack adjacently within a protein. We then show how these predictions can be used to order beta-strands within beta-sheets. Using the entire PDB database with ten-fold cross-validation, we have achieved 74.0% accuracy in packing prediction and 75.6% accuracy in the prediction of edge strands. For the case of beta-strand ordering, we are able to predict the correct ordering accurately for 51.3% of the beta-sheets. Furthermore, using a simple confidence metric, we can determine those sheets for which accurate predictions can be obtained. For the top 25% highest confidence predictions, we are able to achieve 95.7% accuracy in beta-strand ordering. [Figure: see text].
Brown
W Michael
WM
Computational Biology 9212, Sandia National Laboratories, P.O. Box 5800, MS 310, Albuquerque, NM 87185, USA.
Martin
Shawn
S
Chabarek
Joseph P
JP
Strauss
Charlie
C
Faulon
Jean-Loup
JL
D000595:Amino Acid Sequence; D019295:Computational Biology; D030561:Databases, Nucleic Acid; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*
D010455:Peptides; D011506:Proteins