SCORE: predicting the core of protein models

Bioinformatics. 2001 Jun;17(6):541-50. doi: 10.1093/bioinformatics/17.6.541.

Abstract

Motivation: The prediction of the regions of homology models that can be 'restrained by' or 'copied from' the basis structures is a vital step in correct model generation, because these regions are the models most accurate part. However, there is no ideal method for the identification of their limits. In most algorithms their length depends on the number of family members and definitions of secondary structure.

Results: The algorithm SCORE steps away from the conventional definitions of the core to identify from large numbers of basis structures those regions that can be considered structurally related to a target sequence. The use of phi, psi constraints to accurately pinpoint the regions that are conserved across a family and environmentally constrained substitution tables to extend these regions allows SCORE to rapidly (generally in under 1 s, an order of magnitude faster than methods such as MODELLER) identify and build the core of homology models from the alignments of the target sequence to the basis structures. The SCORE algorithm was used to build 114 model cores. In only two cases was the core size less than 50% of the structure and all the cores built had an RMSD of 3.7 A or less to the target structure.

MeSH terms

  • Algorithms*
  • Conserved Sequence
  • Genetic Variation
  • Models, Molecular*
  • Protein Structure, Tertiary / genetics
  • Proteins / analysis*
  • Sequence Alignment

Substances

  • Proteins