Structure Prediction of Partial-Length Protein Sequences

International Journal of Molecular Sciences

Adrian Laurenzi¹  Ling-Hong Hung² 

[1] Department of Computer Science & Engineering, University of Washington, Box 352350, Seattle, WA 98195-2350, USA; E-Mail:;Department of Microbiology, University of Washington, Box 357242, Seattle, WA 98195-7242, USA; E-Mail:

关键词: protein structure prediction;    EST;    expressed sequence tag;    protein folding;    protein design;   

DOI  :  10.3390/ijms140714892

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland