Local structure prediction with local structure-based sequence profiles

Abstract :

Prediction of protein structure from its sequence is a big challenge in the post-genomic era. Some experimental and theoretical evidences suggest that the local sequence/structure relationships could enhance the capacities of structure prediction. In this paper, the authors first construct a non-redundant local structure-based sequence profile database (LSBSP1) for nine-residue segments. Then the secondary structure of query sequence is predicted by PSI-PRED, and parsed into overlapping nine-residue sequence segments. Segments matching the profiles in LSBSP1 with a sequence-profile score above 20 and with more than 60% secondary structure consensus are selected. The final predicted structure is the cluster of largest consensus structures from the selected segments. Finally, the authors compare this method with HMMSTR and the overall accuracies are 79% and 74%, respectively.

From :

Yang,A.S. and Wang,L.Y. (2003) Local structure prediction with local structure-based sequence profiles. Bioinformatics, 1967-1274.

http://bioinformatics.oupjournals.org/cgi/content/abstract/19/10/1267

Reference :

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