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Cited by 421

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I‐TASSER: Fully automated protein structure prediction in CASP8

Open access
Zhang, Yang·2009·Proteins: Structure, Function, and Bioinformatics

Abstract

The I‐TASSER algorithm for 3D protein structure prediction was tested in CASP8, with the procedure fully automated in both the Server and Human sections. The quality of the server models is close to that of human ones but the human predictions incorporate more diverse templates from other servers which improve the human predictions in some of the distant homology targets. For the first time, the sequence‐based contact predictions from machine learning techniques are found helpful for both template‐based modeling (TBM) and template‐free modeling (FM). In TBM, although the accuracy of the sequence based contact predictions is on average lower than that from template‐based ones, the novel contacts in the sequence‐based predictions, which are complementary to the threading templates in the weakly or unaligned regions, are important to improve the global and local packing in these regions. Moreover, the newly developed atomic structural refinement algorithm was tested in CASP8 and found to improve the hydrogen‐bonding networks and the overall TM‐score, which is mainly due to its ability of removing steric clashes so that the models can be generated from cluster centroids. Nevertheless, one of the major issues of the I‐TASSER pipeline is the model selection where the best models could not be appropriately recognized when the correct templates are detected only by the minority of the threading algorithms. There are also problems related with domain‐splitting and mirror image recognition which mainly influences the performance of I‐TASSER modeling in the FM‐based structure predictions. Proteins 2009. © 2009 Wiley‐Liss, Inc.

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Crossref · 10.1002/prot.22588

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Metadata

Authors
Zhang, Y.
Venue
Proteins: Structure, Function, and Bioinformatics
Publisher
Wiley
Published
2009-01
Volume
77
Issue
S9
Pages
100-113
ISSN
  • 0887-3585 (ISSN-L)
  • 1097-0134
OpenAlex
W2110779321
Cited by
421
References
3
FWCI
15.96
Type
journal article
Language
en
Open access
bronze

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