Conserved residue clustering and protein structure prediction

Ora Schueler-Furman, David Baker*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


Protein residues that are critical for structure and function are expected to be conserved throughout evolution. Here, we investigate the extent to which these conserved residues are clustered in three-dimensional protein structures. In 92% of the proteins in a data set of 79 proteins, the most conserved positions in multiple sequence alignments are significantly more clustered than randomly selected sets of positions. The comparison to random subsets is not necessarily appropriate, however, because the signal could be the result of differences in the amino acid composition of sets of conserved residues compared to random subsets (hydrophobic residues tend to be close together in the protein core), or differences in sequence separation of the residues in the different sets. In order to overcome these limits, we compare the degree of clustering of the conserved positions on the native structure and on alternative conformations generated by the de novo structure prediction method Rosetta. For 65% of the 79 proteins, the conserved residues are significantly more clustered in the native structure than in the alternative conformations, indicating that the clustering of conserved residues in protein structures goes beyond that expected purely from sequence locality and composition effects. The differences in the spatial distribution of conserved residues can be utilized in de novo protein structure prediction: We find that for 79% of the proteins, selection of the Rosetta generated conformations with the greatest clustering of the conserved residues significantly enriches the fraction of close-to-native structures.

Original languageAmerican English
Pages (from-to)225-235
Number of pages11
JournalProteins: Structure, Function and Genetics
Issue number2
StatePublished - 1 Aug 2003
Externally publishedYes


  • Bioinformatics
  • Clustering
  • Protein residue conservation
  • Protein structure prediction
  • Rosetta


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