Comp. Modeling: Prediction

Modeling three-dimensional protein structures for CASP5 using the 3D-SHOTGUN meta-predictors

  1. Iris Sasson,
  2. Daniel Fischer*

Article first published online: 15 OCT 2003

DOI: 10.1002/prot.10544

Issue

Proteins: Structure, Function, and Bioinformatics

Proteins: Structure, Function, and Bioinformatics

Supplement: Fifth Meeting on the Critical Assessment of Techniques for Protein Structure Prediction

Volume 53, Issue Supplement 6, pages 389–394, 2003

Additional Information

How to Cite

Sasson, I. and Fischer, D. (2003), Modeling three-dimensional protein structures for CASP5 using the 3D-SHOTGUN meta-predictors. Proteins, 53: 389–394. doi: 10.1002/prot.10544

Author Information

  1. Bioinformatics, Department of Computer Science, Ben Gurion University, Beer-Sheva, Israel

*Bioinformatics, Department of Computer Science, Ben Gurion University, Beer-Sheva 84015, Israel

Publication History

  1. Issue published online: 15 OCT 2003
  2. Article first published online: 15 OCT 2003
  3. Manuscript Accepted: 6 APR 2003
  4. Manuscript Received: 13 FEB 2003

Funded by

  • United States-Israel Binational Science Foundation, Jerusalem, Israel

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Keywords:

  • homology modeling;
  • protein fold recognition;
  • protein structure prediction;
  • critical assessment of protein structure prediction;
  • 3D-SHOTGUN meta-predictor

Abstract

Full-atom models were generated for all CASP5 targets by using the fully automated 3D-SHOTGUN fold recognition meta-predictors (Fischer D, Proteins 2003;51:434–441). The 3D-SHOTGUN meta-predictors assemble hybrid 3D models by combining structural information of a number of independently generated, fold recognition models. At the time CASP5 took place, the 3D-SHOTGUN servers generated unrefined Cα-only models. Fischer's participation in CASP had three main goals. The first was to test the value of using 3D-SHOTGUN models as input to a refinement procedure. The second goal was to test whether human intervention could result in a better performance than that of the automated servers. The third goal was to evaluate which human procedures, not yet implemented within the 3D-SHOTGUN servers, can be implemented in the future. For CASP5, our group's predictions applied a very simple approach using the multiple parent option of the Modeller program (Sali and Blundell, J Mol Biol 1993;234:779–815). The input to Modeller was different combinations of the unrefined 3D-SHOTGUN models and the sequence-template alignments used by 3D-SHOTGUN's assembly step. Our evaluation of the accuracies of the refined versus the SHOTGUN models shows that the refined models were consistently slightly more accurate than SHOTGUN's. For a few targets, the manual use of the information from the CAFASP servers resulted in better human models. This manual intervention was particularly valuable in the identification of domains, still a difficult feature for automated servers. The CASP5 results indicate that 3D-SHOTGUN's hybrid models can be a valuable starting point for full-atom refinement and that the resulting refined models are, on average, more accurate than those produced by the servers. Thus, we conclude that our three goals were achieved. A preliminary automated version of the refinement procedure, named SHGUM, is now available. Proteins 2003;53:389–394. © 2003 Wiley-Liss, Inc.

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