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Assessment of the ability to model proteins with leucine‐rich repeats in light of the latest structural information
Author(s) -
Kajava Andrey V.,
Kobe Bostjan
Publication year - 2002
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1110/ps.4010102
Subject(s) - homology modeling , loop modeling , computational biology , protein structure , structural similarity , structural alignment , structural motif , ribonuclease , multiple sequence alignment , computer science , sequence (biology) , leucine rich repeat , biological system , sequence alignment , genetics , biology , peptide sequence , protein structure prediction , artificial intelligence , biochemistry , rna , gene , enzyme , kinase
The three‐dimensional structures of leucine‐rich repeat (LRR)‐containing proteins from five different families were previously predicted based on the crystal structure of the ribonuclease inhibitor, using an approach that combined homology‐based modeling, structure‐based sequence alignment of LRRs, and several rational assumptions. The structural models have been produced based on very limited sequence similarity, which, in general, cannot yield trustworthy predictions. Recently, the protein structures from three of these five families have been determined. In this report we estimate the quality of the modeling approach by comparing the models with the experimentally determined structures. The comparison suggests that the general architecture, curvature, “interior/exterior” orientations of side chains, and backbone conformation of the LRR structures can be predicted correctly. On the other hand, the analysis revealed that, in some cases, it is difficult to predict correctly the twist of the overall super‐helical structure. Taking into consideration the conclusions from these comparisons, we identified a new family of bacterial LRR proteins and present its structural model. The reliability of the LRR protein modeling suggests that it would be informative to apply similar modeling approaches to other classes of solenoid proteins.