An iterative structure-assisted approach to sequence alignment and comparative modeling

David F. Burke, Charlotte M. Deane, Hampapathalu A. Nagarajaram, Nuria Campillo, Mercedes Martin-Martinez, Joaquim Mendes, Franck Molina, Jeff Perry, B. V.B. Reddy, Claudio M. Soares, Robert E. Steward, Mark Williams, Maria Armenia Carrondo, Tom L. Blundell, Kenji Mizuguchi

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


Correct alignment of the sequence of a target protein with those of homologues of known three-dimensional structure is a key step in comparative modeling. Usually an iterative approach that takes account of the local and overall structural features is required. We describe such an approach that exploits databases of structural alignments of homologous proteins (HOMSTRAD, and protein superfamilies (CAMPASS,, in which structure-based alignments are analyzed and formatted with the program JOY (http://www- to reveal conserved local structural features. The databases facilitate the recognition of a family or superfamily, they assist in the selection of useful parent structures, they are helpful in alignment of the target sequences with the parent set, and are useful for deriving relationships that can be used in validating models. In the iterative approach, a model is constructed on the basis of the proposed sequence alignment and this is then reexpressed in the JOY format and realigned with the parent set. This is repeated until the model and sequence alignment is optimized. We examine the case for comparison and use of multiple structures of family members, rather than a single parent structure. We use the targets attempted by our group in CASP3 to assess the value of such procedures.

Original languageEnglish
Pages (from-to)55-60
Number of pages6
JournalProteins: Structure, Function and Genetics
Issue numberSUPPL. 3
Publication statusPublished - 1 Jan 1999


  • Alignment annotation
  • Alignment databases
  • Local structural features
  • Loop modeling
  • Model evaluation
  • Protein family
  • Protein structure
  • Side-chain modeling
  • Structure prediction


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