Improving protein structure prediction using multiple sequence-based contact predictions

Structure. 2011 Aug 10;19(8):1182-91. doi: 10.1016/j.str.2011.05.004.

Abstract

Although residue-residue contact maps dictate the topology of proteins, sequence-based ab initio contact predictions have been found little use in actual structure prediction due to the low accuracy. We developed a composite set of nine SVM-based contact predictors that are used in I-TASSER simulation in combination with sparse template contact restraints. When testing the strategy on 273 nonhomologous targets, remarkable improvements of I-TASSER models were observed for both easy and hard targets, with p value by Student's t test<0.00001 and 0.001, respectively. In several cases, template modeling score increases by >30%, which essentially converts "nonfoldable" targets into "foldable" ones. In CASP9, I-TASSER employed ab initio contact predictions, and generated models for 26 FM targets with a GDT-score 16% and 44% higher than the second and third best servers from other groups, respectively. These findings demonstrate a new avenue to improve the accuracy of protein structure prediction especially for free-modeling targets.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Amino Acid Sequence
  • Bacterial Proteins / chemistry
  • Caspase 8 / chemistry
  • Caspase 9 / chemistry
  • Computer Simulation*
  • DNA-Binding Proteins / chemistry
  • Models, Molecular
  • Protein Conformation*
  • Support Vector Machine*
  • Transcription Factors / chemistry
  • Viral Proteins / chemistry

Substances

  • Bacterial Proteins
  • DNA-Binding Proteins
  • MotA protein, Enterobacteria phage T4
  • Transcription Factors
  • Viral Proteins
  • Caspase 8
  • Caspase 9