Amino acid coupling patterns in thermophilic proteins

Structural analysis is useful in elucidating structural features responsible for enhanced thermal stability of proteins. However, due to the rapid increase of sequenced genomic data, there are far more protein sequences than the corresponding three-dimensional (3D) structures. The usual sequence-based amino acid composition analysis provides useful but simplified clues about the amino acid types related to thermal stability of proteins. In this work, we developed a statistical approach to identify the significant amino acid coupling sequence patterns in thermophilic proteins. The amino acid coupling sequence pattern is defined as any 2 types of amino acids separated by I or more amino acids. Using this approach, we construct the p profiles for the coupling patterns. The p value gives a measure of the relative occurrence of a coupling pattern in thermophiles compared with mesophiles. We found that thermophiles and mesophiles exhibit significant bias in their amino acid coupling patterns. We showed that such bias is mainly due to temperature adaptation instead of species or GC content variations. Though no single outstanding coupling pattern can adequately account for protein thermostability, we can use a group of amino acid coupling patterns having strong statistical significance (p values < 10(-7)) to distinguish between thermophilic and mesophilic proteins. We found a good correlation between the optimal growth temperatures of the genomes and the occurrences of the coupling patterns (the correlation coefficient is 0.89). Furthermore, we can separate the thermophilic proteins from their mesophilic orthologs using the amino acid coupling patterns. These results may be useful in the study of the enhanced stability of proteins from thermophiles - especially when structural information is scarce. (C) 2005 Wiley-Liss, Inc.