Discovering Side-Chain Correlations In [[alpha]]-Helices

Proceedings Of The Second International Conference On Intelligent Systems For Molecular Biology

Volume

Proceedings Of The Second International Conference On Intelligent Systems For Molecular Biology

Contents

Using a new representation for interactions in protein sequences based on correlations between pairs of amino acids, we have examined or-helical segments from known protein structures for important interactions. Traditional techniques tbr representing protein sequences usually make an explicit assumption of conditional independence of residues in the sequences. Protein structure analyses, however, have repeatedly demonstrated the importance of amino acid interactions tbr structural stability. We have developed an automated program for discovering sequence correlations in sets of aligned protein sequences using standard statistical tests and for representing them with Bayesian networks. In this paper, we demonstrate the power of our discovery program and representation by analyzing pairs of residues from c-helices. The sequence correlations we find represent physical and chemical interactions among amino-acid side chains in helical structures. Furthermore, these local interactions are likely to be important for stabilizing and packing s-helices. Lastly, we have also detect correlations in side-chain comformations that indicate important structural interactions but which don’t appear as sequence correlations.