The Dependence of Amino Acid Pair Correlations

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, throughspace interactions were more important than those between residues near in the protein sequence. The highest ranked nonlocal interactions involved residues in b-sheet structures. Of the local interactions, those between residues i and i 1 2 were the most important in both a-helices and b-strands. Some surprisingly strong correlations were discovered within b-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. Proteins 32:175--189, 1998. r 1998 Wiley-Liss, Inc. Key words: pairwise statistics; secondary structure; nonlocal interaction