In Silico Modeling of the Influence of Environment on Amyloid Folding Using FOD-M Model

Model of the external force field for the protein folding process-the role of prefoldin

Introduction: The protein folding process is very sensitive to environmental conditions. Many possibilities in the form of numerous pathways for this process can-if an incorrect one is chosen-lead to the creation of forms described as misfolded. The aqueous environment is the natural one for the protein folding process. Nonetheless, other factors such as the cell membrane and the presence of specific molecules (chaperones) affect this process, ensuring the correct expected structural form to guarantee biological activity. All these factors can be considered components of the external force field for this process. Methods: The fuzzy oil drop-modified (FOD-M) model makes possible the quantitative evaluation of the modification of the external field, treating the aqueous environment as a reference. The FOD-M model (tested on membrane proteins) includes the component modifying the water environment, allowing the assessment of the external force field generated by prefoldin. Results: In this work, prefoldin was treated as the provider of a specific external force field for actin and tubulin. The discussed model can be applied to any folding process simulation, taking into account the changed external conditions. Hence, it can help simulate the in silico protein folding process under defined external conditions determined by the respective external force field. In this work, the structures of prefoldin and protein folded with the participation of prefoldin were analyzed. Discussion: Thus, the role of prefoldin can be treated as a provider of an external field comparable to other environmental factors affecting the protein folding process.

Ab initio protein structure prediction: the necessary presence of external force field as it is delivered by Hsp40 chaperone

BACKGROUND

The aqueous environment directs the protein folding process towards the generation of micelle-type structures, which results in the exposure of hydrophilic residues on the surface (polarity) and the concentration of hydrophobic residues in the center (hydrophobic core). Obtaining a structure without a hydrophobic core requires a different type of external force field than those generated by a water. The examples are membrane proteins, where the distribution of hydrophobicity is opposite to that of water-soluble proteins. Apart from these two extreme examples, the process of protein folding can be directed by chaperones, resulting in a structure devoid of a hydrophobic core.

RESULTS

The current work presents such example: DnaJ Hsp40 in complex with alkaline phosphatase PhoA-U (PDB ID-6PSI)-the client molecule. The availability of WT form of the folding protein-alkaline phosphatase (PDB ID-1EW8) enables a comparative analysis of the structures: at the stage of interaction with the chaperone and the final, folded structure of this biologically active protein. The fuzzy oil drop model in its modified FOD-M version was used in this analysis, taking into account the influence of an external force field, in this case coming from a chaperone.

CONCLUSIONS

The FOD-M model identifies the external force field introduced by chaperon influencing the folding proces. The identified specific external force field can be applied in Ab Initio protein structure prediction as the environmental conditioning the folding proces.

New insights on the catalytic center of proteins from peptidylprolyl isomerase group based on the FOD-M model

Generating the structure of the hydrophobic core is based on the orientation of hydrophobic residues towards the central part of the protein molecule with the simultaneous exposure of polar residues. Such a course of the protein folding process takes place with the active participation of the polar water environment. While the self-assembly process leading to the formation of micelles concerns freely moving bi-polar molecules, bipolar amino acids in polypeptide chain have limited mobility due to the covalent bonds. Therefore, proteins form a more or less perfect micelle-like structure. The criterion is the hydrophobicity distribution, which to a greater or lesser extent reproduces the distribution expressed by the 3D Gaussian function on the protein body. The vast majority of proteins must ensure solubility, so a certain part of it-as it is expected-should reproduce the structuring of micelles. The biological activity of proteins is encoded in the part that does not reproduce the micelle-like system. The location and quantitative assessment of the contribution of orderliness to disorder is of critical importance for the determination of biological activity. The form of maladjustment to the 3D Gauss function may be varied-hence the obtained high diversity of specific interactions with strictly defined molecules: ligands or substrates. The correctness of this interpretation was verified on the basis of the group of enzymes Peptidylprolyl isomerase-E.C.5.2.1.8. In proteins representing this class of enzymes, zones responsible for solubility-micelle-like hydrophobicity system-the location and specificity of the incompatible part in which the specific activity of the enzyme is located and coded were identified. The present study showed that the enzymes of the discussed group show two different schemes of the structure of catalytic center (taking into account the status as defined by the fuzzy oil drop model).

Structural Specificity of Polymorphic Forms of α-Synuclein Amyloid

The structural transformation producing amyloids is a phenomenon that sheds new light on the protein folding problem. The analysis of the polymorphic structures of the α-synuclein amyloid available in the PDB database allows analysis of the amyloid-oriented structural transformation itself, but also the protein folding process as such. The polymorphic amyloid structures of α-synuclein analyzed employing the hydrophobicity distribution (fuzzy oil drop model) reveal a differentiation with a dominant distribution consistent with the micelle-like system (hydrophobic core with polar shell). This type of ordering of the hydrophobicity distribution covers the entire spectrum from the example with all three structural units (single chain, proto-fibril, super-fibril) exhibiting micelle-like form, through gradually emerging examples of local disorder, to structures with an extremely different structuring pattern. The water environment directing protein structures towards the generation of ribbon micelle-like structures (concentration of hydrophobic residues in the center of the molecule forming a hydrophobic core with the exposure of polar residues on the surface) also plays a role in the amyloid forms of α-synuclein. The polymorphic forms of α-synuclein reveal local structural differentiation with a common tendency to accept the micelle-like structuralization in certain common fragments of the polypeptide chain of this protein.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

New insights into disordered proteins and regions according to the FOD-M model

A collection of intrinsically disordered proteins (IDPs) having regions with the status of intrinsically disordered (IDR) according to the Disprot database was analyzed from the point of view of the structure of hydrophobic core in the structural unit (chain / domain). The analysis includes all the Homo Sapiens as well as Mus Musculus proteins present in the DisProt database for which the structure is available. In the analysis, the fuzzy oil drop modified model (FOD-M) was used, taking into account the external force field, modified by the presence of other factors apart from polar water, influencing protein structuring. The paper presents an alternative to secondary-structure-based classification of intrinsically disordered regions (IDR). The basis of our classification is the ordering of hydrophobic core as calculated by the FOD-M model resulting in FOD-ordered or FOD-unordered IDRs.

The Possible Mechanism of Amyloid Transformation Based on the Geometrical Parameters of Early-Stage Intermediate in Silico Model for Protein Folding

The specificity of the available experimentally determined structures of amyloid forms is expressed primarily by the two- and not three-dimensional forms of a single polypeptide chain. Such a flat structure is possible due to the β structure, which occurs predominantly. The stabilization of the fibril in this structure is achieved due to the presence of the numerous hydrogen bonds between the adjacent chains. Together with the different forms of twists created by the single R- or L-handed α-helices, they form the hydrogen bond network. The specificity of the arrangement of these hydrogen bonds lies in their joint orientation in a system perpendicular to the plane formed by the chain and parallel to the fibril axis. The present work proposes the possible mechanism for obtaining such a structure based on the geometric characterization of the polypeptide chain constituting the basis of our early intermediate model for protein folding introduced formerly. This model, being the conformational subspace of Ramachandran plot (the ellipse path), was developed on the basis of the backbone conformation, with the side-chain interactions excluded. Our proposal is also based on the results from molecular dynamics available in the literature leading to the unfolding of α-helical sections, resulting in the β-structural forms. Both techniques used provide a similar suggestion in a search for a mechanism of conformational changes leading to a formation of the amyloid form. The potential mechanism of amyloid transformation is presented here using the fragment of the transthyretin as well as amyloid Aβ.

Lightweight ProteinUnet2 network for protein secondary structure prediction: a step towards proper evaluation

Background

The prediction of protein secondary structures is a crucial and significant step for ab initio tertiary structure prediction which delivers the information about proteins activity and functions. As the experimental methods are expensive and sometimes impossible, many SS predictors, mainly based on different machine learning methods have been proposed for many years. Currently, most of the top methods use evolutionary-based input features produced by PSSM and HHblits software, although quite recently the embeddings—the new description of protein sequences generated by language models (LM) have appeared that could be leveraged as input features. Apart from input features calculation, the top models usually need extensive computational resources for training and prediction and are barely possible to run on a regular PC. SS prediction as the imbalanced classification problem should not be judged by the commonly used Q3/Q8 metrics. Moreover, as the benchmark datasets are not random samples, the classical statistical null hypothesis testing based on the Neyman–Pearson approach is not appropriate.

Results

We present a lightweight deep network ProteinUnet2 for SS prediction which is based on U-Net convolutional architecture and evolutionary-based input features (from PSSM and HHblits) as well as SPOT-Contact features. Through an extensive evaluation study, we report the performance of ProteinUnet2 in comparison with top SS prediction methods based on evolutionary information (SAINT and SPOT-1D). We also propose a new statistical methodology for prediction performance assessment based on the significance from Fisher–Pitman permutation tests accompanied by practical significance measured by Cohen’s effect size.

Conclusions

Our results suggest that ProteinUnet2 architecture has much shorter training and inference times while maintaining results similar to SAINT and SPOT-1D predictors. Taking into account the relatively long times of calculating evolutionary-based features (from PSSM in particular), it would be worth conducting the predictive ability tests on embeddings as input features in the future. We strongly believe that our proposed here statistical methodology for the evaluation of SS prediction results will be adopted and used (and even expanded) by the research community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04623-z.

On the need to introduce environmental characteristics in ab initio protein structure prediction using a coarse-grained UNRES force field

During the protein folding process in computer simulations involving the use of a United RESidue (UNRES) force field, an additional module was introduced to represent directly the presence of a polar solvent in water form. This module implements the fuzzy oil drop model (FOD) where the 3D Gauss function expresses the presence of a polar environment which directs the polypeptide chain folding process towards the generation of a centric hydrophobic core. Sample test polypeptide chains of 8 proteins with chain lengths ranging from 37 to 75 aa were simulated in silico using the UNRES (U) package with an implicit solvent model and a built-in module expressing the FOD model (UNRES-FOD-UNRES (U + F) interleaved simulation). The protein structure obtained by both *** simulation schemes, i.e., accordingly***U and U + F, for all the analyzed protein models shows the presence of a hydrophobic core including where it is absent in the native structure. The proposed FOD-M model (M-modified) explaining the source of this phenomenon reveals the need to modify the external field expressing the role of a folding environment. The modification takes into account the influence of other than polar factors present in the folding environment.

Dependence of Protein Structure on Environment: FOD Model Applied to Membrane Proteins

The natural environment of proteins is the polar aquatic environment and the hydrophobic (amphipathic) environment of the membrane. The fuzzy oil drop model (FOD) used to characterize water-soluble proteins, as well as its modified version FOD-M, enables a mathematical description of the presence and influence of diverse environments on protein structure. The present work characterized the structures of membrane proteins, including those that act as channels, and a water-soluble protein for contrast. The purpose of the analysis was to verify the possibility that an external force field can be used in the simulation of the protein-folding process, taking into account the diverse nature of the environment that guarantees a structure showing biological activity.

On the Dependence of Prion and Amyloid Structure on the Folding Environment

Currently available analyses of amyloid proteins reveal the necessity of the existence of radical structural changes in amyloid transformation processes. The analysis carried out in this paper based on the model called fuzzy oil drop (FOD) and its modified form (FOD-M) allows quantifying the role of the environment, particularly including the aquatic environment. The starting point and basis for the present presentation is the statement about the presence of two fundamentally different methods of organizing polypeptides into ordered conformations—globular proteins and amyloids. The present study shows the source of the differences between these two paths resulting from the specificity of the external force field coming from the environment, including the aquatic and hydrophobic one. The water environment expressed in the fuzzy oil drop model using the 3D Gauss function directs the folding process towards the construction of a micelle-like system with a hydrophobic core in the central part and the exposure of polarity on the surface. The hydrophobicity distribution of membrane proteins has the opposite characteristic: Exposure of hydrophobicity at the surface of the membrane protein with an often polar center (as in the case of ion channels) is expected. The structure of most proteins is influenced by a more or less modified force field generated by water through the appropriate presence of a non-polar (membrane-like) environment. The determination of the proportion of a factor different from polar water enables the assessment of the protein status by indicating factors favoring the structure it represents.