An automated classification of the structure of protein loops

Baldomero Oliva, Paul A. Bates, Enrique Querol, Francesc X. Avilés, Michael J.E. Sternberg

Research output: Contribution to journalArticleResearchpeer-review

173 Citations (Scopus)

Abstract

Conformational clusters and consensus sequences for protein loops have been derived by computational analysis of their structures in a non-redundant set of 233 proteins with less than 25% sequence homology (X-ray resolution better than 2.5 Å). Loops have been classified into five types (α-α, β-β links, β-β hairpins, α-β and β-α) according to the secondary structures they embrace. Four variables have been used to describe the loop geometry, three angles and one distance between the secondary structure elements embracing the loop. Ramachandran angles (∅, ψ) are used to define the loop conformations within each brace geometry. All loops from the non-redundant set have been clustered by means of these geometric features. A total of 56 classes (9 α-α, 11 β-β links, 14 β-β hairpins, 13 α-β and 9 β-α) were identified with consensus Ramachandran angles in the loops. These classes were divided into subclasses based on the brace geometry. This clustering procedure captures most of the clusters analysed by predominantly visual inspection methods and finds other clusters that have hitherto not been described. Consensus sequence patterns were identified for the subclasses. An extensive characterisation of loop conformations has therefore been achieved and the computational approach is readily open to the incorporation of information from newly determined structures. These clusters should also enhance model building by comparison studies.
Original languageEnglish
Pages (from-to)814-830
JournalJournal of Molecular Biology
Volume266
DOIs
Publication statusPublished - 7 Mar 1997

Keywords

  • Homology modelling
  • Protein analysis
  • Protein loops
  • Protein prediction
  • Sequence motifs

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