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Protein structure prediction and structural genomics (2001)
| Venue: | Science |
| Citations: | 329 - 14 self |
BibTeX
@ARTICLE{Baker01proteinstructure,
author = {David Baker and Andrej Sali},
title = {Protein structure prediction and structural genomics},
journal = {Science},
year = {2001},
volume = {294},
pages = {93--96}
}
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Abstract
Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of
Keyphrases
structural genomics protein structure prediction protein structure prediction method first class essential feature second class valuable information biological role full understanding initio method fold level high-resolution structure information comparative modeling genome sequencing project large fraction experimental structure determination method detectable similarity known structure computational structure prediction method linear amino acid sequence
