Dubay KF, Pawar AP, Chiti F, Zurdo J, Dobson CM, Vendruscolo M.
Prediction of the absolute aggregation rates of amyloidogenic polypeptide chains.
J Mol Biol. 2004 Aug 27;341(5):1317-26.
PubMed.
This paper presents, for the first time, a quantitative method for predicting the rate of aggregation into filaments or other larger structures based on intrinsic (amino acid sequence, charge, hydrophobicity) and extrinsic (pH, ionic content, concentration) factors. The method assumes a simple power-law form for the dependence of aggregation rate on each of these factors, yet arrives at an expression with surprising predictive power. These findings are useful in several ways. On the practical side, it provides a means of determining how changes in the peptide sequence or solution conditions will affect aggregation rates for virtually any polypeptide. Perhaps even more importantly, it provides a framework in which to better understand the interactions among many different factors on aggregation rates. Although the true dependencies are almost certainly more complex than suggested by this simple expression, the same method could be used to obtain parameter values for various algebraic forms that better fit each individual mechanism, as these become better understood. Interactive terms, involving interactions between multiple factors, could also be envisioned. As such, it provides a convenient platform for future research on polypeptide chain aggregation rates.
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MIT
This paper presents, for the first time, a quantitative method for predicting the rate of aggregation into filaments or other larger structures based on intrinsic (amino acid sequence, charge, hydrophobicity) and extrinsic (pH, ionic content, concentration) factors. The method assumes a simple power-law form for the dependence of aggregation rate on each of these factors, yet arrives at an expression with surprising predictive power. These findings are useful in several ways. On the practical side, it provides a means of determining how changes in the peptide sequence or solution conditions will affect aggregation rates for virtually any polypeptide. Perhaps even more importantly, it provides a framework in which to better understand the interactions among many different factors on aggregation rates. Although the true dependencies are almost certainly more complex than suggested by this simple expression, the same method could be used to obtain parameter values for various algebraic forms that better fit each individual mechanism, as these become better understood. Interactive terms, involving interactions between multiple factors, could also be envisioned. As such, it provides a convenient platform for future research on polypeptide chain aggregation rates.
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