A statistical analysis was performed to determine to what extent an amino acid determines the identity of its neighbors and to what extent this is determined by the structural environment. Log-linear analysis was used to discriminate chance occurrence from statistically meaningful correlations. The classification of structures was arbitrary, but was also tested for significance. A list of statistically significant interaction types was selected and then ranked according to apparent importance for applications such as protein design. This showed that, in general, nonlocal, through- space interactions were more important than those between residues near in the protein sequence. The highest ranked nonlocal interactions involved residues in β-sheet structures. Of the local interactions, those between residues i and i + 2 were the most important in both α-helices and β- strands. Some surprisingly strong correlations were discovered within β- sheets between residues and sites sequentially near to their bridging partners. The results have a clear bearing on protein engineering studies, but also have implications for the construction of knowledge-based force fields.
|Number of pages||15|
|Journal||Proteins: Structure, Function and Bioinformatics|
|Publication status||Published - 1 Aug 1998|
- Nonlocal interactions
- Pairwise statistics
- Secondary structure