221j Insulin Fibrillation Kinetics at Interfaces

Arpan Nayak1, Amit Dutta2, Chuang-Chung Lee3, Gregory J. McRae3, and Georges Belfort4. (1) Howard P Isermann Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 8th st, Troy, NY 12180-3590, (2) Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 8th st, Troy, NY 12180-3590, (3) Chemical Engineering, MIT, Cambridge, MA 02141, (4) Howard P. Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 8th st, Troy, NY 12180-3590

Amyloid fibrillation is the process of native soluble proteins misfolding into insoluble fibrils comprising of cross-?-sheets and has received wide attention due to its substantial physiological relevance and the complexity of the underlying physical and chemical reactions. At present, more than 20 amyloidogenic diseases including Alzheimer's disease, Parkinson's disease, and prion–associated encephalopathies have been found to share fibril formation as the common cause. Human insulin is chosen as a model molecule for our study because (i) it is associated with a clinical syndrome, injection-localized amyloidosis, (ii) it is a member of the class of fibril forming proteins that loses its zinc- coordinated hexameric structure to form monomers that then fibrils, (iii) of its well-characterized in vitro fibrillation kinetics under well-defined solution conditions (2 mg/ml, pH 1.6 and 65ºC), (iv) fibril formation is a problem in commercial isolation and purification of insulin at low pH values of 1-3. Here, we investigate the influence of suspended solid interfaces and dissolved sugars on the kinetics of insulin fibrillation. For apolar solid substrates. insulin nucleation is speeded up while growth of fibers is unaffected. However, in the presence of various sugars, the whole fibrillation process (nucleation and growth) is delayed. We also present a mechanistic mathematical model that simulates the phenomena by incorporating the physical chemistry of nucleation and growth dynamics. Estimated by nonlinear least square algorithms, we find rate constants that account for the ubiquitous sigmoidal responses of amyloidogenic proteins when they misfold.