Amyloid fibrils are ordered polypeptide aggregates that have been implicated in several neurodegenerative pathologies, such as Alzheimer{\textquoteright}s, Parkinson{\textquoteright}s, Huntington{\textquoteright}s, and prion diseases [1, 2], and, more recently, also in biological functionalities [3, 4, 5]. These findings have paved the way for a wide range of experimental and computational studies aimed at understanding the details of the fibril-formation mechanism. Computer simulations using low-resolution models, which employ a simplified representation of protein geometry and energetics, have provided insights into the basic physical principles underlying protein aggregation in general [6, 7, 8] and ordered amyloid aggregation [9, 10, 11, 12, 13, 14, 15]. For example, Dokholyan and coworkers have used the Discrete Molecular Dynamics method [16, 17] to shed light on the mechanisms of protein oligomerization [18] and the conformational changes that take place in proteins before the aggregation onset [19, 20]. One challenging observation, which is difficult to observe by computer simulations, is the wide range of aggregation scenarios emerging from a variety of biophysical measurements [21, 22]. Atomistic models have been employed to study the conformational space of amyloidogenic polypeptides in the monomeric state [23, 24, 25], the very initial steps of amyloid formation [26, 27, 28, 29, 30, 31, 32], and the structural stability of fibril models [33, 34, 35]. However, all-atom simulations of the kinetics of fibril formation are beyond what can be done with modern computers.
In lieu of a true abstract, this is the beginning of the introduction.}, year = {2012}, journal = {Computational Modeling of Biological Systems: Modeling Macromolecular Assemblies}, pages = {191-214}, publisher = {Springer US}, address = {New York}, isbn = {978-1-4614-2145-0}, doi = {10.1007/978-1-4614-2146-7_8}, language = {eng}, }