Automated classification of antibody complementarity determining region 3 of the heavy chain (H3) loops into canonical forms and its application to protein structure prediction

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

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Abstract

A computer-based algorithm was used to cluster the loops forming the complementarity determining region (CDR) 3 of the heavy chain (H3) into canonical classes. Previous analyses of the three-dimensional structures of CDR loops (also known as the hypervariable regions) within antibody immunoglobulin variable domains have shown that for five of the six CDRs there are only a few main-chain conformations (known as canonical forms) that show clear relationships between sequence and structure. However, the larger variation in length and conformation of loops within H3 has limited the classification of these loops into canonical forms. The clustering procedure presented here is based on aligning the Ramachandran-coded main-chain conformation of the residues using a dynamic algorithm that allows the insertion of gaps to obtain an optimum alignment. A total of 41 H3 loops out of 62 non-identical loops, extracted from the Brookhaven Protein Data Bank, have been automatically grouped into 22 clusters. Inspection of the clusters for consensus sequences or intra-loop interactions or invariant conformation led to the proposal of 13 canonical forms representing 31 loops. These canonical forms include a consideration of the geometry of both the take-off region adjacent to the bracing β-strands and the remaining loop apex. Subsequently a new set of 15 H3 loops not included in the initial analysis was considered. The clustering procedure was repeated and nine of these 15 loops could be assigned to original clusters, including seven to canonical forms. A sequence profile was generated for each canonical form from the original set of loops and matched against the sequences of the new H3 loops. For five out of the seven new H3 loops that were in a canonical form, the correct form was identified at first rank by this predictive scheme.
Original languageEnglish
Pages (from-to)1193-1210
JournalJournal of Molecular Biology
Volume279
DOIs
Publication statusPublished - 26 Jun 1998

Keywords

  • Analysis
  • Antibody structure
  • Bioinformatics
  • Combining site
  • Protein modelling

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