Real-value prediction of backbone torsion angles

• Published in: Proteins, structure, function, and bioinformatics Vol. 72; no. 1; pp. 427 - 433
• Main Authors: Xue, Bin, Dor, Ofer, Faraggi, Eshel, Zhou, Yaoqi
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.07.2008
• Subjects: Algorithms; Amino Acid Sequence; Amino Acids - chemistry; artificial neural networks; Databases, Protein; dihedral angle; Proteins - chemistry; Reproducibility of Results; secondary structure; Solvents; Torsion, Mechanical
• ISSN: 0887-3585; 1097-0134
• DOI: 10.1002/prot.21940

The backbone structure of a protein is largely determined by the ϕ and ψ torsion angles. Thus, knowing these angles, even if approximately, will be very useful for protein‐structure prediction. However, in a previous work, a sequence‐based, real‐value prediction of ψ angle could only achieve a mean absolute error of 54° (83°, 35°, 33° for coil, strand, and helix residues, respectively) between predicted and actual angles. Moreover, a real‐value prediction of ϕ angle is not yet available. This article employs a neural‐network based approach to improve ψ prediction by taking advantage of angle periodicity and apply the new method to the prediction to ϕ angles. The 10‐fold‐cross‐validated mean absolute error for the new method is 38° (58°, 33°, 22° for coil, strand, and helix, respectively) for ψ and 25° (35°, 22°, 16° for coil, strand, and helix, respectively) for ϕ. The accuracy of real‐value prediction is comparable to or more accurate than the predictions based on multistate classification of the ϕ−ψ map. More accurate prediction of real‐value angles will likely be useful for improving the accuracy of fold recognition and ab initio protein‐structure prediction. The Real‐SPINE 2.0 server is available on the website http://sparks.informatics.iupui.edu. Proteins 2008. © 2008 Wiley‐Liss, Inc.