Abstract
Proteins with a high degree of sequence similarity representing different structures provide a key to understand how protein sequence codes for 3D structure. An analysis using the fuzzy oil drop model was carried out on two pairs of proteins with different secondary structures and with high sequence identities. It has been shown that distributions of hydrophobicity for these proteins are approximated well using single 3D Gaussian function. In other words, the similar sequences fold into different 3D structures, however, alternative structures also have symmetric and monocentric hydrophobic cores. It should be noted that a significant change in the helical to beta-structured form in the N-terminal section takes places in the fragment much preceding the location of the mutated regions. It can be concluded that the final structure is the result of a complicated synergy effect in which the whole chain participates simultaneously.
Highlights
The mechanism of the protein folding process is still a puzzle despite intensive research in this direction [1]
Compliance with the model is expressed by the presence of fragments with low hydrophobicity Oi on the protein surface
The most important thing is that regardless of the secondary form, the overarching tendency in all of these proteins is the desire to generate a hydrophobic core. In these proteins the dominant importance of generating nuclear structure has been demonstrated. These two states produce the structure preferred by the aquatic environment, regardless of the secondary form
Summary
The mechanism of the protein folding process is still a puzzle despite intensive research in this direction [1]. Protein folding issues cannot be discussed without taking into account such milestones as Levinthal’s paradox [2,3,4,5,6,7], Anfinsen’s folding research [8,9] or the introduction of the concept of intermediates in the process of protein folding [10]. The concept of hydrophobic interactions unnoticed by quantum chemistry has become one of the decisive factors involved in protein structuring [14,15,16]. The Levinthal paradox in the era of protein simulation and prediction takes the form of the multiple minima problem [17], in which structure prediction techniques assume the evolutionary nature of structure changes and use homology modelling [18]. The ab initio methods, on the other hand, look for simplified forms of the starting structure and a simplified form of force field representation [19]
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