Exceptional aggregation propensity of amino acids in polyglutamine amino-acid-homopolymer

Similar aggregation and {beta}-sheet propensity of amino acids in globular proteins and amyloids, suggests comparable principles of their formation. Here we show that during the process of aggregation into amyloid-like fibers, these rules are not the same in an amino-acid-homopolymer (AAHP) polyglutamine (PolyGln). An aggregation kinetic analysis on nine-point mutants of a forty-six long PolyGln peptide was carried in physiological conditions. At the dynamic equilibrium state of aggregation, critical-concentration derived free-energy differences, signifying aggregation propensity of incorporated amino acids were obtained. None of the obtained propensities correlated with existing conventional aggregation and {beta}-sheet propensities of the amino acids in proteins and amyloids. Further, the differential aggregation behavior of all the peptides only correlated with van der Waals volume of the incorporated amino acid and not with any other physicochemical characteristic of amino acids. The new rules obtained from PolyGln AAHP provide an opportunity to explore physiological relevance of a mutation within AAHP in human proteome. Additionally, this study opens up new avenues for protein model design exploring folding and aggregation behavior of other amino-acid-homopolymer (AAHP) existing in the human proteome. SignificanceMutational analysis within PolyGln sequences adds to the knowledge of unique aggregation propensities of amino acids within PolyGln AAHP. This study highlights the importance of van der Waals volume in dictating stability-instability of an aggregation fold and in turn aggregation kinetics and thermodynamic stability of aggregates. The analysis signifies the role of Gln-Gln interlocking system within PolyGln folding motif and extent of disruption caused by van der Waals volume of an amino acid. The results can be taken as a starting point to evaluate the possible impact of amino acid insertions in PolyGln stretches of other proteins. It also opens opportunities to study the structural and functional relationship of other AAHPS for their unique folding and aggregation behavior. Learning outcome can be utilized as a bottom-up approach to design amyloid biomaterial with different strengths for biomedical applications.