Functional classification of protein structures by local structure matching in graph representation. (27th April 2018)
- Record Type:
- Journal Article
- Title:
- Functional classification of protein structures by local structure matching in graph representation. (27th April 2018)
- Main Title:
- Functional classification of protein structures by local structure matching in graph representation
- Authors:
- Mills, Caitlyn L.
Garg, Rohan
Lee, Joslynn S.
Tian, Liang
Suciu, Alexandru
Cooperman, Gene D.
Beuning, Penny J.
Ondrechen, Mary Jo - Abstract:
- Abstract: As a result of high‐throughput protein structure initiatives, over 14, 400 protein structures have been solved by Structural Genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP‐Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP‐Func method to our previously reported method, Structurally Aligned Local Sites of Activity (SALSA), using the Ribulose Phosphate Binding Barrel (RPBB), 6‐Hairpin Glycosidase (6‐HG), and Concanavalin A‐like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP‐Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP‐Func methods to predict function. Forty‐one SG proteins in the RPBB superfamily, nine SG proteins in the 6‐HG superfamily, and one SG protein in the CAL/G superfamily wereAbstract: As a result of high‐throughput protein structure initiatives, over 14, 400 protein structures have been solved by Structural Genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP‐Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP‐Func method to our previously reported method, Structurally Aligned Local Sites of Activity (SALSA), using the Ribulose Phosphate Binding Barrel (RPBB), 6‐Hairpin Glycosidase (6‐HG), and Concanavalin A‐like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP‐Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP‐Func methods to predict function. Forty‐one SG proteins in the RPBB superfamily, nine SG proteins in the 6‐HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. … (more)
- Is Part Of:
- Protein science. Volume 27:Number 6(2018)
- Journal:
- Protein science
- Issue:
- Volume 27:Number 6(2018)
- Issue Display:
- Volume 27, Issue 6 (2018)
- Year:
- 2018
- Volume:
- 27
- Issue:
- 6
- Issue Sort Value:
- 2018-0027-0006-0000
- Page Start:
- 1125
- Page End:
- 1135
- Publication Date:
- 2018-04-27
- Subjects:
- protein function annotation -- Graph Representation of Active Sites for Prediction of Function (GRASP‐Func) -- Structurally Aligned Local Sites of Activity (SALSA) -- Ribulose Phosphate Binding Barrel (RPBB) superfamily -- 6‐Hairpin Glycosidase (6‐HG) superfamily -- Concanavalin A‐like Lectins/Glucanase (CAL/G) superfamily
Proteins -- Periodicals
572.6 - Journal URLs:
- http://www.proteinscience.org/ ↗
http://www3.interscience.wiley.com/journal/121502357/ ↗
http://onlinelibrary.wiley.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1002/pro.3416 ↗
- Languages:
- English
- ISSNs:
- 0961-8368
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6936.105500
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 9324.xml