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Open AccessArticle

Structure Prediction of Partial-Length Protein Sequences

1
Department of Computer Science & Engineering, University of Washington, Box 352350, Seattle, WA 98195-2350, USA
2
Department of Microbiology, University of Washington, Box 357242, Seattle, WA 98195-7242, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2013, 14(7), 14892-14907; https://doi.org/10.3390/ijms140714892
Received: 26 April 2013 / Revised: 1 July 2013 / Accepted: 2 July 2013 / Published: 17 July 2013
(This article belongs to the Collection Protein Folding)
Protein structure information is essential to understand protein function. Computational methods to accurately predict protein structure from the sequence have primarily been evaluated on protein sequences representing full-length native proteins. Here, we demonstrate that top-performing structure prediction methods can accurately predict the partial structures of proteins encoded by sequences that contain approximately 50% or more of the full-length protein sequence. We hypothesize that structure prediction may be useful for predicting functions of proteins whose corresponding genes are mapped expressed sequence tags (ESTs) that encode partial-length amino acid sequences. Additionally, we identify a confidence score representing the quality of a predicted structure as a useful means of predicting the likelihood that an arbitrary polypeptide sequence represents a portion of a foldable protein sequence (“foldability”). This work has ramifications for the prediction of protein structure with limited or noisy sequence information, as well as genome annotation. View Full-Text
Keywords: protein structure prediction; EST; expressed sequence tag; protein folding; protein design protein structure prediction; EST; expressed sequence tag; protein folding; protein design
MDPI and ACS Style

Laurenzi, A.; Hung, L.-H.; Samudrala, R. Structure Prediction of Partial-Length Protein Sequences. Int. J. Mol. Sci. 2013, 14, 14892-14907.

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