Helical packing patterns in membrane and soluble proteins.

This article presents the results of a detailed analysis of helix-helix interactions in membrane and soluble proteins. A data set of interacting pairs of helices in membrane proteins of known structure was constructed and a structure alignment algorithm was used to identify pairs of helices in soluble proteins that superimpose well with pairs of helices in the membrane-protein data set. Most helix pairs in membrane proteins are found to have a significant number of structural homologs in soluble proteins, although in some cases, primarily involving irregular helices, no close homologs exist. An analysis of geometric relationships between interacting helices in the two sets of proteins identifies some differences in the distributions of helix length, interfacial area, packing angle, and distance between the polypeptide backbones. However, a subset of soluble-protein helix pairs that are close structural homologs to membrane-protein helix pairs exhibits distributions that mirror those observed in membrane proteins. The larger average interface size and smaller distance of closest approach seen for helices in membrane proteins appears due in part to a relative enrichment of alanines and glycines, particularly as components of the AxxxA and GxxxG motifs. It is argued that membrane helices are not on average more tightly packed than helices in soluble proteins; they are simply able to approach each other more closely. This enables them to interact over longer distances, which may in turn facilitate their remaining in contact over much of the width of the lipid bilayer. The close structural similarity seen between some pairs of helices in membrane and soluble proteins suggests that packing patterns observed in soluble proteins may be useful in the modeling of membrane proteins. Moreover, there do not appear to be fundamental differences between the magnitude of the forces that drive helix packing in membrane and soluble proteins, suggesting that strategies to make membrane proteins more soluble by mutating surface residues are likely to encounter success, at least in some cases.

Using multiple structure alignments, fast model building, and energetic analysis in fold recognition and homology modeling.

We participated in the fold recognition and homology sections of CASP5 using primarily in-house software. The central feature of our structure prediction strategy involved the ability to generate good sequence-to-structure alignments and to quickly transform them into models that could be evaluated both with energy-based methods and manually. The in-house tools we used include: a) HMAP (Hybrid Multidimensional Alignment Profile)-a profile-to-profile alignment method that is derived from sequence-enhanced multiple structure alignments in core regions, and sequence motifs in non-structurally conserved regions. b) NEST-a fast model building program that applies an "artificial evolution" algorithm to construct a model from a given template and alignment. c) GRASP2-a new structure and alignment visualization program incorporating multiple structure superposition and domain database scanning modules. These methods were combined with model evaluation based on all atom and simplified physical-chemical energy functions. All of these methods were under development during CASP5 and consequently a great deal of manual analysis was carried out at each stage of the prediction process. This interactive model building procedure has several advantages and suggests important ways in which our and other methods can be improved, examples of which are provided.