A Comparative Study of Disordered and Ordered Protein Folding Dynamics Using Computational Simulation

TL;DR

This paper compares molecular dynamics and Gillespie algorithm simulations to analyze the folding dynamics of disordered and ordered proteins, highlighting the computational insights gained from different simulation methods.

Contribution

It introduces a comparative analysis of MD and Gillespie simulations for disordered and ordered protein folding, demonstrating the effectiveness of computational methods in biophysical studies.

Findings

Gillespie algorithm effectively models ordered protein folding dynamics.

MD simulation provides detailed insights into disordered protein behavior.

Simulation results align with theoretical predictions of protein dynamics.

Abstract

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.