Analysis, clustering and prediction of the conformation of short and medium
size loops connecting regular secondary structures.

Stephen D. Rufino, Luis E. Donate, Luc Canard and Tom L. Blundell.

The Imperial Cancer Research Fund,
Unit of Structural Molecular Biology,
Department of Crystallography,
Birkbeck College, University of London,
Malet Street, London WC1E 7HX, UK.

Loops are regions of non-repetitive conformation connecting regular
secondary structures. They are both the most difficult and error prone
regions of a protein to solve by X-ray crystallography and the hardest
regions to model using knowledge-based procedures. While the core of a
protein can be straight forwardly modelled from the structurally conserved
regions of homologues of known structure, loops must be modelled from a
selected homologue or from a loop chosen from outside the family. Here we
present a loop prediction procedure that attempts to identify the
conformational class of the loop rather than to select a specific loop from
a database of fragments. From the clustering of 2083 loops, of one to eight
residues in length, according to the root mean square deviation of their
spatial fit, a total of 162 loop conformational classes, including 79% of
loops, were identified. Most of the previously described loop conformations
were found among the populated classes. For each class a template was
constructed containing both sequence preferences and the relative
disposition of bounding secondary structures among member loops. During
comparative modelling, the conformation of a loop can be predicted by
identifying a loop class with which its sequence and disposition of bounding
secondary structures are compatible.