Modeling Three-Dimensional Protein Structures for CASP5 Using the 3D-SHOTGUN Meta-Predictors

Iris Sasson, Daniel Fischer

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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.

Original languageEnglish
Pages (from-to)389-394
Number of pages6
JournalProteins: Structure, Function and Bioinformatics
Issue numberSUPPL. 6
StatePublished - 12 Nov 2003


  • 3D-SHOTGUN meta-predictor
  • Critical assessment of protein structure prediction
  • Homology modeling
  • Protein fold recognition
  • Protein structure prediction

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology


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