  Folding protein dynamics has been an area of high interest for quite some
time, especially given the increased focus on the field of Biophysics. Because
folding dynamics occur on such short time scales, empirical techniques
developed for more "static" protein events, such as X-ray crystallography,
nuclear magnetic resonance, and green fluorescent protein (GFP) labelling,
aren't as applicable. Instead, computational methods must often be used to
simulate these short lived yet highly dynamic events. One such computational
method that is proven to provide much valuable insight into protein folding
dynamics is Molecular Dynamics Simulation (MD Simulation). This simulation
method is both highly computationally demanding, yet highly accurate in its
modelling of a proteins physical behaviour. Besides MD Simulation, simulations
in general are quite applicable in the context of these protein events. For
example, the simple Gillespie algorithm, a computational technique which can be
executed on almost any personal computer, provides quite the robust view into
protein dynamics given its computational simplicity. This paper will compare
the results of two simulations, an MD simulation of a disordered, six-residue,
carcinogenic protein fragment, and a Gillespie algorithm based simulation of an
ordered folding protein: the mathematically identical nature of the Gillespie
algorithm time series of the asymptotically stochastic hyperbolic tangent
dynamics for the wild type predicting the exact behaviour of the carcinogenic
protein system time series will show the computational power simulations
provide for analyzing both disordered and ordered protein systems.
