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Ab initio protein structure prediction using a combined hierarchical approach

  • Stanford University
  • Washington University St. Louis

Research output: Contribution to journalArticlepeer-review

88 Scopus citations

Abstract

As part of the third Critical Assessment of Structure Prediction meeting (CASP3), we predict the three-dimensional structures for 13 proteins using a hierarchical approach. First, all possible compact conformations of a protein sequence are enumerated using a highly simplified tetrahedral lattice model. We select a large subset of these conformations using a lattice-based scoring function and build detailed all-atom models incorporating predicted secondary structure. A combined all-atom knowledge-based scoring function is then used to select three smaller subsets from these all-atom models. Finally, a consensus-based distance geometry procedure is used to generate the best conformations from each of the all-atom subsets. With this method, we are able to predict the global topology/shape for all or a large part of the sequence for six out of the thirteen proteins. For two other proteins, the topology/shape for shorter fragments are predicted. This represents a marked improvement in ab initio prediction since CASP was first instigated in 1994.

Original languageEnglish
Pages (from-to)194-198
Number of pages5
JournalProteins: Structure, Function and Genetics
Volume37
Issue numberSUPPL. 3
DOIs
StatePublished - 1999

Keywords

  • Discrete-state models
  • Distance geometry
  • Knowledge-based scoring functions
  • Lattice models

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