Computer Simulation of Protein Materials at Multiple Length Scales: From Single Proteins to Protein Assemblies

Abstract

Computer simulation of protein materials and their dynamic or mechanical behavior is of high significance, as proteins perform their functions through their structural changes in response to a force (or stimulus). The computer simulation enables the detailed insight into the structure and behavior of proteins at atomistic resolution, which is inaccessible with experimental toolkits such as single-molecule experiments. With the advancement of computing resources, the computer simulation has recently played a vital role as a virtual microscopy in understanding and characterizing the structure and behaviors of protein materials at atomistic resolution. For examples, computer simulations allow for gaining insight into how some protein domains can exhibit the remarkable mechanical properties and functions. In this article, we would like to address the current state-of-arts of computer simulations that have been employed for studying the structure and properties (or behaviors) of proteins at multiple length scales ranging from single proteins to protein assemblies. Specifically, we summarize various computational modeling techniques, ranging from atomistic models to coarse-grained models and continuum models, applicable for modeling protein structures at multiple length scales from single proteins to protein assemblies. This paper discusses how such various computational modeling/simulation techniques can be employed for studying the structure and properties of protein materials at multiple length scales. This paper sheds light on computer simulations, which are able to unveil the hidden, complex mechanisms related to the structure and properties of protein materials at multiple length scales.

Unfolding Pathway of Proteins Predicted by Elastic Network Model

“…Elastic network model (ENM) describes a protein structure as a network of elastic springs connected between neighboring alpha carbon atoms (representing the residues). The potential field of ENM is given by [1,4,6,9] where γ is a force constant for an elastic spring, r ij is a distance between two residues i and j, r c is a cut-off distance, H(x) is a Heaviside step function defined as H(x) = 1 if x > 0; otherwise, H(x) = 0, and superscript 0 indicates an equilibrium state, i.e. native structure.…”

“…Proteins have received significant attention due to their excellent mechanical functions and properties, which are attributed to the force-driven unfolding mechanism [1][2][3]. Specifically, the folding structure of a protein can sustain a mechanical force until the force exerted by a protein reaches a critical value, at which the folding structure is denatured.…”

“…This suggests that for understanding the mechanical functions and properties of proteins, the unfolding mechanisms of proteins have to be analyzed. For such an analysis, for recent decades, atomistic simulations [1,2] have allowed for detailed insight into the force-driven unfolding mechanisms of proteins. Nonetheless, the atomistic simulations are restrictive in analyzing the unfolding mechanics of large proteins due to the computational limitation of atomistic simulations.…”

Literature Review on Fretting Wear and Contact Mechanics of Tribological Coatings

“…In addition to AFM experiment with a theoretical model such as the Prandtl-Tomlinson model, atomistic simulations such as molecular dynamics (MD) simulations have allowed for unveiling the physical origin of frictional properties. Here, the principle of MD simulation is to numerically solve Newton's equation of motion for all atoms of a material system under mechanical process [109][110][111]. In recent decades, MD simulations have played an unprecedented role in gaining insight into nanoscale phenomena including, but not limited to, protein dynamics [109][110][111], nanomaterial behaviors [112,113], and (nanoscale) frictions [114].…”

“…Here, the principle of MD simulation is to numerically solve Newton's equation of motion for all atoms of a material system under mechanical process [109][110][111]. In recent decades, MD simulations have played an unprecedented role in gaining insight into nanoscale phenomena including, but not limited to, protein dynamics [109][110][111], nanomaterial behaviors [112,113], and (nanoscale) frictions [114]. In particular, MD simulations have successfully validated the Prandtl-Tomlinson model by simulating the friction of Pt tip sliding on a gold atomic surface [104].…”