The problem of protein folding has always been of prime concern in molecular
biology. Under normal physiological conditions, most proteins acquire well defined
compact three dimensional shapes, known as the native conformations, at which
they are biologically active. When proteins are unfolding or misfolding, they
not only lose their inherent biological activity but they can also aggregate into
insoluble fibrils structures called amyloids which are known to be involved in
many degenerative diseases like Alzheimer’s disease, Parkinson’s disease, type
2 diabetes, cerebral palsy, mad cow disease etc. Thus, determining the folded
structure and clarifying the mechanism of folding of the protein plays an important
role in our understanding of the living organism as well as the human health.
Protein aggregation and amyloid formation have also been studied extensively
in recent years. Studies have led to the hypothesis that amyloid is the general
state of all proteins and is the fundamental state of the system when proteins
can form intermolecular interactions. Thus, the tendency for aggregation and formation amyloid persists for all proteins and is a trend towards competition with
protein folding. However, experiments have also shown that possibility of aggregation and aggregation rates depend on solvent conditions and on the amino acid
sequence of proteins. Some studies have shown that small amino acid sequences
in the protein chain may have a significant effect on the aggregation ability. As
a result, knowledge about the link between amino acid sequence and possibility
of aggregation is essential for understanding amyloid-related diseases as well as
finding a way to treat them.
Although all-atom simulations are now widely used molecular biology, the
application of these methods in the study of protein folding problem is not feasible
due to the limits of computer speed. A suitable approach to the protein folding
problem is to use simple theoretical models. There are quite a number of models
with different ideas and levels of simplicity, but most notably the Go model and
the HP network model and tube model.
