Protein aggregation: Computational modeling and Monte Carlo algorithm development
Summary, in English
In Papers II and IV we use all-atom Monte Carlo simulations with implicit solvent to characterize two intrinsically disordered proteins known to form fibrillar aggregates: α-synuclein linked with Parkinson’s disease and Aβ linked with Alzheimer’s disease. Paper II investigates the 140-residue α-synuclein in
free monomeric form. In Paper IV, we examine the response of Aβ and α-synuclein to a pulling force, and compare with single-molecule experiments. Both studies suggest that fibril-like folds are easily accessible to these proteins. In Paper V the same model is used to investigate the local unfolding dynamics and
aggregation propensities of the natively folded SOD1 monomer, which has been associated with the disease amyotrophic lateral sclerosis (ALS).
In Paper III we develop a minimal structure-based model for amyloid formation. While most theoretical and computational studies have modeled fibril formation as a 1D growth process, this model allows us to study the interplay between length and width in fibril nucleation.
In Papers I and VI we develop and investigate generalized-ensemble techniques for accelerating simulations of systems with rugged free-energy landscapes. We study the flat-histogram method, and an extension of it which assigns higher weight to regions of low diffusivity. A new scheme for estimating diffusion-optimized weights is developed.
- Computational Biology and Biological Physics
- MultiPark: Multidisciplinary research focused on Parkinson´s disease
Department of Astronomy and Theoretical Physics, Lund University
- Monte Carlo simulations
- protein aggregation
- disordered proteins
- Fysicumarcivet A:2014:Jonsson
- Anders Irbäck
14 February 2014
Lundmarkssalen, Astronomy building
- Flavio Seno (Prof)