Title
PROFcon: novel prediction of long-range contacts.
Abstract
Despite the continuing advance in the experimental determination of protein structures, the gap between the number of known protein sequences and structures continues to increase. Prediction methods can bridge this sequence-structure gap only partially. Better predictions of non-local contacts between residues could improve comparative modeling, fold recognition and could assist in the experimental structure determination.Here, we introduced PROFcon, a novel contact prediction method that combines information from alignments, from predictions of secondary structure and solvent accessibility, from the region between two residues and from the average properties of the entire protein. In contrast to some other methods, PROFcon predicted short and long proteins at similar levels of accuracy. As expected, PROFcon was clearly less accurate when tested on sparse evolutionary profiles, that is, on families with few homologs. Prediction accuracy was highest for proteins belonging to the SCOP alpha/beta class. PROFcon compared favorably with state-of-the-art prediction methods at the CASP6 meeting. While the performance may still be perceived as low, our method clearly pushed the mark higher. Furthermore, predictions are already accurate enough to seed predictions of global features of protein structure.
Year
DOI
Venue
2005
10.1093/bioinformatics/bti454
Bioinformatics
Keywords
Field
DocType
experimental structure determination,prediction method,known protein sequence,prediction accuracy,better prediction,neural networks. .,novel prediction,long-range contact,evolutionary information,entire protein,inter-residue contacts,secondary structure,protein structure,long protein,protein structure prediction,novel contact prediction method,neural network,protein sequence,comparative modeling,fold recognition
Computer science,Threading (protein sequence),Bioinformatics,Protein secondary structure,Protein structure,Protein contact map
Journal
Volume
Issue
ISSN
21
13
1367-4803
Citations 
PageRank 
References 
61
3.42
16
Authors
2
Name
Order
Citations
PageRank
Marco Punta11709194.79
Burkhard Rost279588.14