A fold-recognition approach to loop modeling.
A novel approach is proposed for modeling loop regions in proteins. In this approach, a prerequisite sequence-structure alignment is examined for regions where the target sequence is not covered by the structural template. These regions, extended with a number of residues from adjacent stem regions, are submitted to fold recognition. The alignments produced by fold recognition are integrated into the initial alignment to create an alignment between the target sequence and several structures, where gaps in the main structural template are covered by local structural templates. This one-to-many (1:N) alignment is used to create a protein model by existing protein-modeling techniques. Several alternative approaches were evaluated using a set of ten proteins. One approach was selected and evaluated using another set of 31 proteins. The most promising result was for gap regions not located at the C-terminus or N-terminus of a protein, where the method produced an average RMSD 12% lower than the loop modeling provided with the program MODELLER. This improvement is shown to be statistically significant.
Levefelt
Christer
C
School of Humanities and Informatics, University of Skövde, Box 408, 54128 Skövde, Sweden.
Lundh
Dan
D
D000595:Amino Acid Sequence; D008958:Models, Molecular; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
D011506:Proteins