ChemBioChem · 2011 · 13 citations · 44 references
Life SciencesBiochemistryBiophysicsPost-translational ModificationProtein FoldingStructural BiologyMacromolecular AssemblyPeptide ChemistryProtein DynamicsProtein Folding ThermodynamicsProtein PhosphorylationProtein StructureAggregation KineticsAggregation PropensityAmyloid Aggregation KineticsAmyloid Fibril FormationAmyloid FibrilsPeptide AggregationPhosphorylation EffectsProtein Aggregation Kinetics
Despite the importance of post-translational modifications in controlling the solubility and conformational properties of proteins and peptides, precisely how the aggregation propensity of different peptide sequences is modulated by chemical modification remains unclear. Here we have investigated the effect of phosphorylation on the aggregation propensity of a 13-residue synthetic peptide incorporating one or more phosphate groups at seven different sites at various pH values. Fibril formation was shown to be inhibited when a single phosphate group was introduced at all seven locations in the peptide sequence at pH 7.5, when the phosphate group is fully charged. By contrast, when the same peptides were analysed at pH 1.1, when the phosphate is fully protonated, fibrils from all seven peptide sequences form rapidly. At intermediate pH values (pH 3.6) when the phosphate group is mono-anionic, the aggregation propensity of the peptides was found to be highly dependent on the position of the phosphate group in the peptide sequence. Using this information, combined with molecular dynamics (MD) simulations of the peptide sequence, we provide evidence consistent with the peptide forming amyloid fibrils with a class 7 architecture. The results highlight the potential utility of phosphorylation as a method of reversibly controlling the aggregation kinetics of peptide sequences both during and after synthesis. Moreover, by exploiting the ability of the phosphate group to adopt different charge states as a function of pH, and combining experimental insights with atomistic information calculated from MD simulations as pH is varied, we show how the resulting information can be used to predict fibril structures consistent with both datasets, and use these to rationalise their sensitivity of fibrillation kinetics both to the location of the phosphate group and its charge state.
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