Irena Roterman

Background The presence of water for biological systems, which is critical for protein activity, is treated in protein molecular dynamics simulation tools as a collection of individual water molecules in numbers corresponding to the conditions of a given simulation. The presence of water is important for the folding process as well as the structural changes associated with biological activity. Methods This article presents proposals to treat the water environment as a provider of an external force field directing the folding process to achieve the structure expected by the biological system. The external force field can have different forms, e.g. the form of a field derived from the hydrophobic membrane for membrane proteins, or the form of a chaperonin, if the protein acquires an active structural form assisted by support proteins. Results The study is limited to examples of proteins shaped by the water environment, whose presence as an external force field is expressed by a 3D Gaussian function directing the hydrophobic residues toward central part of protein and hydrophilic ones toward the surface. Conclusions The discussed examples of proteins prove the necessary participation of environment – especially water – in folding process. In consequence the funnel model can be expressed in quantitative form visualising the appropriate energy minimum (global or local) to be determined by specificity of external force field.

Advancement to knowledge is the possibility to simulate the living system in In Silico technique. Therefore, it is of interest to seek an unambiguous interpretation of life as a phenomenon. To overcome the challenges posed by the complexity of biological information, the scope of this study is narrowed down to the cellular level with cells are categorized into two groups: dividing cells – species life, associated with reproduction and non-dividing cells – individual life. This analysis focuses exclusively on individual life, using the erythrocyte as a model for non-dividing cells where the autonomy as a process dedicated to maintaining the stability of the cell's internal environment is treated as the basis. This capacity to sustain internal conditions is recognized as the primary manifestation of life using an automatic response mechanism to environmental changes, governed by negative feedback loops. Furthermore, self-organization, independent recognition of errors and their remediation are identified as key components of autonomous cellular action, the simulation of which is possible using the incorporated simulation tools to model these selected biological processes

The issue of protein folding in vivo remains an unsolved problem despite important progress achieved by artificial intelligence (AlphaFold). Experimental studies have shown that there are several mechanisms involved in this process. The main distinction concerns the involvement of chaperone proteins in this process as opposed to spontaneous folding. Evolutionary analysis shows that tubulin in eukaryotic organisms requires engagement of the ATP-dependent ring-shaped chaperonin TRiC/CCT, while the homologous protein in prokaryotic organisms obtains its functional structure without the support from other proteins. This study—limited to 2 examples: one human tubulin β chain and one structure of homologous bacterial FtsZ protein—presents hypothetical interpretation of these differences based on the external conditions for folding process. The differences of the distribution of hydrophobicity in the compared proteins are taken as the criteria for comparison. The fuzzy oil drop model (FOD-M) assumes the folding of prokaryotic proteins as a spontaneous process aided only by the presence of the water environment that directs the folding toward the generation of a centrally located hydrophobic core with a polar surface. Eukaryotic protein—tubulin—exhibits a distribution of hydrophobicity that lacks this type of order as it is interpreted based on the FOD-M assumptions. The difference seems to be the result of the involvement of different external force fields in the folding process. These 2 proteins are an example that suggest the need to include the active influence of the local environment. The hypothesis for in silico methods of folding process simulation is assumed to use a multiple-object optimization technique that takes into account the optimization of the energy state of protein E as a function dependent on 2 functions: E _INT (internal force field) and E _EXT (external force field).

The fundamental principle for protein structuring is that the 3D structure is determined by the amino acid sequence. An important phenomenon in this regard is the presence of a differentiated secondary structure for chain fragments of identical sequence—referred to as chameleons. In the present work, individual chain fragments were shown to constitute components of a system with specific physicochemical properties of the overall structure, adapting the secondary structure to the superior role assigned to the protein. The proteins (domains) represent the construction with a centrally located hydrophobic core and a polar surface (described by 3D Gauss function) representing a favourable arrangement in contact with water—the standard environment for the activity of most proteins. The fuzzy oil drop model (FOD‐M), which takes into account the presence of a non‐water environment for the active protein, was used to assess this condition. The proteins present in the ChSeq database are the object of analysis. The criterion for qualifying a pair of proteins for the analysis presented herein is the presence of a structuring—a hydrophobicity distribution consistent with a 3D Gaussian distribution representing a micelle‐like system. The analysis shows that an appropriate secondary structure is not an aim by itself, but a means to achieve a hydrophobicity distribution appropriate for the status represented by the structural unit with its defined biological activity. The mathematical model for in silico simulation of protein folding process as environment dependent is also presented.

The structure of protein has encoded the record of biological activity in the form of a specific polarity-hydrophobicity relationship system. Structural changes related to the function change this record according to the process stages, in which the given protein is used. The local exposure of hydrophobicity is a specific record of the possible hydrophobic interaction with another protein, providing an agent stabilising such a system. The local hydrophobicity deficit means the presence of a cavity, ready to interact with a substrate in the case of an enzyme. Other cavity types may be adapted to interact with a ligand comprising a permanent ingredient of a complex, often guaranteeing biological activity. Exposure of hydrophobic residues in the case of membrane-anchored proteins is a typical example, rendering the proteins stable in the membrane environment. The fuzzy oil drop (FOD) model in its modified form (FOD-M) is a model describing such phenomena in the aspect of the polarity/hydrophobicity relationship. Application of this model allows quantitative assessment of the status reflecting the specific nature of individual proteins. Examples of this application are discussed in this publication.

Given the critical importance of preventing protein aggregation in neurodegenerative diseases, aggregation prediction tools are essential. Amyloid predictors would facilitate the understanding and exploitation of the amyloid state of proteins, providing an alternative to costly and slow laboratory tests. In recent years, hexapeptides have become a model for studying amyloid formation. Hexapeptides can also be used to identify aggregation‐prone regions in proteins, particularly those involved in amyloid formation. While numerous computational methods using sophisticated feature sets and architectures have been developed for classifying hexapeptides and predicting amyloidogenic regions in proteins, predictive performance remains limited; for instance, BAP achieves only 84% accuracy. Here, we designed a novel feature selection method for hexapeptides, resulting in an easy to interpret four‐feature representation called the AmyloPick model. A classifier based on this representation outperforms existing state‐of‐the‐art methods. When extended to detect aggregation‐prone regions (APRs) in full proteins, it performs comparably to established tools. A key contribution of this study is the statistical methodology that enables a rigorous performance assessment and direct comparison with other classifiers. This is particularly important because differing methodologies in the literature often hinder the comparability of the proposed methods. Our AmyloPick classifier significantly outperformed the state‐of‐the‐art Budapest Amyloid Predictor (BAP) across all metrics, particularly in adjusted geometric mean (AGM) (0.7808 vs. 0.7649 for BAP) and accuracy (0.8089 vs. 0.7955 for BAP). For APR identification, APR‐AmyloPick was comparable to ANuPP overall but significantly outperformed it in the metric. We have also developed a web server for the AmyloPick classifier.

The activity of serpins uses a specific mechanism or process. This process comprises several steps and is related to significant structural changes that involve significant displacement of chain fragments and whole molecules of protease. An important role is played by a segment of the serpin chain called the Reactive Central Loop (RCL), which interacts with the protease by inhibiting its activity. For the covalent binding of the protease to serpin, the movement of the protease molecule is an effect of splicing the RCL segment into beta-sheet A of serpin. There are structural forms—native, latent, Michaelis complex (non-covalent enzyme-inhibitor complex prior to RCL cleavage), covalent serpin–protease complex, and cleaved—associated with serpin activity. In this work, all these structural forms are discussed using the fuzzy oil drop (FOD-M) model, where the assessment criterion of structuring is based on identifying the type of hydrophobicity distribution. The analysis reveals the specificity of the inhibition mechanism, including the specific action of the RCL. The structural changes involved in this process have been shown to preserve the distribution of hydrophobicity in the form preferred by the aqueous environment in which serpins are active. The disorder (according to FOD-M model) in two complexes (Michaelis and covalent) is hypothetically treated as code for degradation factors. The applied model assesses the function-related structures using the hydrophobicity distribution as the criterion in contrast to many publications based on energetic aspects of serpin activity. Structural changes appear appropriate for water environments—the environment of serpin activity.

The activity of serpins uses a specific mechanism, or process. This process comprises several steps and is related to significant structural changes that involve significant displacement of chain fragments and whole molecules of protease. An important role is played by a segment of the serpin chain called the Reactive Central Loop (RCL), which interacts with the protease by inhibiting its activity. For the covalent binding of the protease to serpin, the movement of the protease molecule is an effect of splicing the RCL segment into beta-sheet A of serpin. There are structural forms—native, latent, Michaelis complex, covalent, and cleaved—associated with serpin activity. In this work, all these structural forms are discussed using the fuzzy oil drop (FOD-M) model, where the assessment criterion of structuring is based on identifying the type of hydrophobicity distribution. The analysis reveals the specificity of the inhibition mechanism, including the specific action of the RCL. The structural changes involved in this process have been shown to preserve the distribution of hydrophobicity in the form preferred by the aqueous environment in which serpins are active. The disorder (according to FOD-M model) in two complexes (Michaelis and covalent) is treated as code for degradation factors.

The contribution of the environment to protein folding seems obvious. The aqueous environment directs protein folding towards generating a centric hydrophobic core with a polar shell. The cell membrane environment—in which numerous proteins are anchored—to stabilise the arrangement, expects the exposure of hydrophobic residues and the concentration of polar residues in the central part—a channel for the transport of numerous molecules. The influence of these environments seems evident due to the persistent residence of proteins in their surroundings providing an external force field for structure stabilisation. Structural forms are also obtained with the participation of supporting proteins—such as proteins from the heat shock protein group—which accompany the folding process and temporarily provide an appropriate external force field in which the protein, having obtained the correct structure for its activity, is released from interaction with the supporting protein. This paper discusses an example of the contribution of Hsp104 to casein folding and the effect of disaggregase preventing inappropriate aggregation. For this purpose, a model called the fuzzy oil drop (FOD-M) was used, which takes hydrophobic interactions into account in the assessment of protein structure status. Their distribution in the protein body highlights the contribution and influence of the external force field—originating from Hsp104 and the disaggregase in this case.

The predisposition of amino acids towards accepting the appropriate secondary structure form is ambiguous. The identified sequences (6–12 aa in length – ChSeq data base) of the chameleon type (the same sequence accepting different secondary structures) constitute a puzzle that makes it difficult to indicate the initial conformation in a chain with a given amino acid sequence. The analysis of proteins presented in this paper uses the hydrophobicity distribution in protein body as the criterion for comaparable analysis of the status of helica/Beta-structural chameleon fragments in pairs of proteins. The sub-base is the object of analysis containg the proteins representing the organisation of hydrophobicity in one protein of the pair as ordered according to micelle-like organisation (hydrophobic core with polar surface) and the second one in pair with disordered hydrophobicity organisation. The status of chameleon sections appears to represent local organisation of hydrophobicity highly accordant in both proteins in chameleon pair independently on the status of the structural unit they belong to. The fuzzy oil drop model (FOD) in its modified form (FOD-M) is applied for analysis. This work aims to verify the hypothesis assuming the subordination of the form of secondary structure to the superior goal of obtaining a hydrophobicity distribution suitable for the given biological activity of the protein, ensuring biological functionality. Secondary structure is not an aim by itself. It is shown, that the main goal is to reach the structure representing specific activity. Secondary structure is a means to achieve this goal.