Background: Unknown protein structures can be predicted from known str
uctures (the scaffolds) with sequences sufficiently homologous to that
of the target, based on the observation that similar sequences usuall
y adopt the same fold. When structural equivalences between residues i
n the scaffold and target proteins are expressed in terms of conserved
interatomic distances, the resulting 'distance geometry' representati
on provides an elegant mechanism for simultaneous restraint satisfacti
on and bias-free conformation space exploration. Results: We present a
homology modelling algorithm based on distance geometry that relies o
n the gradual projection of simple model chain coordinates into Euclid
ean spaces with decreasing dimensionality. The similarity between the
unknown target structure and the scaffold proteins with known structur
es was described by mapping secondary structure assignments and specif
ic distance restraints between C-alpha atoms onto the model through a
multiple alignment. This information was complemented by additional re
straints derived from stereochemical considerations and other general
aspects of protein structure such as hydrophobic core formation or the
absence of tangled mainchains. Conclusions: The method was capable of
quickly locating the correct fold even from an alignment with modest
average conservation indicating that it could serve as a fast tool for
obtaining correct low-resolution starting conformations for detailed
refinement. (C) Current Biology Ltd