## 1 Introduction  
Most of the known biological functions are only conceivable because of the wide range of operations performed by proteins [1, 2]. The folding and unfolding process is one of these aspects that must be understood to comprehend how these macromolecules operate at the nanometer scale. The protein conformational states are not static and they depend on many factors, such as the surrounding environment and temperature [3]. The study of the three-dimensional protein structure is rather complex, allowing many different approaches to the problem. The application of coarse-grained systems usually enables the analysis of larger proteins composed of several hundred amino acids with relatively low computational effort, typically providing global descriptions [4]. For specific problems, the atomically-detailed models can, to some extent, contribute to further and more accurate information [5]. To this purpose, molecular dynamics (MD) dives deeper into higher accuracy evaluation of the actual phenomena in place. However, its high computational burden often prevents its applicability in studying the large-scale slow motions of the protein, which are known to be correlated with the biological function. In the last decades, it was shown that simplified calculations based on the assumption of a harmonic potential can provide accurate insights into protein dynamics. Normalmode analysis (NMA) was developed for this purpose as a simplified yet powerful tool to extract the functional modes of the protein structure. [PERSON] et al. showed that NMA with internal coordinates is particularly suited for modeling the collective motions, enabling the visualization of biologically relevant modes, and it is complementary to the more time-consuming MD simulations [6]. However, these NMA calculations still relied on a detailed knowledge of the complex semi-empirical potentials that characterize the interactions amongst all the atoms of the system. Afterward, it was shown by [PERSON] that a simplified single-parameter harmonic potential is good enough to reproduce the slow dynamics of the protein correctly while avoiding the expensive and sometimes inaccurate NMA energy minimization of the reference structure [7]. Subsequently, it was recognized that even coarse-grained representations of the protein, only based on the position of the C\({}^{\alpha}\) atoms of the crystal structure, lead to useful predictions of the slow protein dynamics as well as the observed fluctuations [8; 9; 10]. These models are known as the Elastic Network Models (ENMs), and various developments have been carried out in the following years by various research groups [11; 12; 13; 14; 15; 16; 17]. The great amount of work in ENM development was because, despite their inherent simplification, these structural models were found to provide impressive insights on the biological mechanisms and flexibility of the protein [18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28]. It is astonishing that such simplified models, purely based on Structural Mechanics concepts, allow us to understand protein motions and biological activity, which are very complex in nature. The present work encompasses the protein's representation as a simple truss-like domain, similar to macroscale structures in the field of civil engineering, using a finite element (FE) approach. The protein's dynamic properties are extracted by carrying out the modal analysis of the system and considering different initial assumptions. Then, the results of the calculations are compared to experimental data and the outcomes of other numerical studies. Many authors have indicated that underdamped frequencies describing collective modes at GHz and THz frequencies may be relevant to the biochemical function [29; 30; 31; 32; 33; 34; 35]. The hen egg-white lysozyme is the chosen protein for this study due to the extensive bibliography and experimental results related to it. This protein has an essential role in breaking bacterial cell walls and can be found in human milk and tears.