PROFcon: novel prediction of long-range contacts.

TitlePROFcon: novel prediction of long-range contacts.
Publication TypeJournal Article
Year of Publication2005
AuthorsPunta, M, Rost, B
Date Published2005 Jul 1
KeywordsAlgorithms, Binding Sites, Computer Simulation, Models, Chemical, Models, Molecular, Neural Networks (Computer), Protein Binding, Protein Conformation, Protein Folding, Proteins, Sequence Alignment, Sequence Analysis, Protein, Software

MOTIVATION: 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.RESULTS: 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.

Alternate JournalBioinformatics
PubMed ID15890748
Grant ListR01-GM64633-01 / GM / NIGMS NIH HHS / United States