Modeling protein folding in vivo

Plumbagin accelerates serum albumin's amyloid aggregation kinetics and generates fibril polymorphism by inducing non-native β-sheet structures

The ligand-induced conformational switch of proteins has great significance in understanding the biophysics and biochemistry of their self-assembly. In this work, we have investigated the ability of plumbagin (PL), a hydroxynaphthoquinone compound found in the root of the medicinal plant Plumbago zeylanica, to modulate aggregation precursor state, aggregation kinetics and generate distinct fibril of human serum albumin (HSA). PL was found to moderately bind (binding constant Ka ∼ 10-4 M-1)) to domain-II of HSA in the stoichiometric ratio of 1:1. We found that PL-HSA complex aggregation was accelerated as compared to that of HSA aggregation and it may be through an independent pathway. We also detected that fibril produced in the presence of PL is wider in diameter, contains a higher amount of β-sheet (∼18%) and disordered (∼46%) structures, and is less stable. We concluded that the acceleration of aggregation reaction and generation of fibril polymorphism was mainly because of the higher extent of unfolding and high content of non-native β-sheet structure in the aggregation precursor state of PL-HSA complex. This study offers opportunities to explore the ability of ligand binding to modulate aggregation reactions and generate polymorphic protein fibrils.

A Study of a Protein-Folding Machine: Transient Rotation of the Polypeptide Backbone Facilitates Rapid Folding of Protein Domains in All-Atom Molecular Dynamics Simulations

Molecular dynamics simulations of protein folding typically consider the polypeptide chain at equilibrium and in isolation from the cellular components. We argue that in order to understand protein folding as it occurs in vivo, it should be modeled as an active, energy-dependent process, in which the cellular protein-folding machine directly manipulates the polypeptide. We conducted all-atom molecular dynamics simulations of four protein domains, whose folding from the extended state was augmented by the application of rotational force to the C-terminal amino acid, while the movement of the N-terminal amino acid was restrained. We have shown earlier that such a simple manipulation of peptide backbone facilitated the formation of native structures in diverse α-helical peptides. In this study, the simulation protocol was modified, to apply the backbone rotation and movement restriction only for a short time at the start of simulation. This transient application of a mechanical force to the peptide is sufficient to accelerate, by at least an order of magnitude, the folding of four protein domains from different structural classes to their native or native-like conformations. Our in silico experiments show that a compact stable fold may be attained more readily when the motions of the polypeptide are biased by external forces and constraints.

Folding and Evolution of a Repeat Protein on the Ribosome

Life on earth is the result of the work of proteins, the cellular nanomachines that fold into elaborated 3D structures to perform their functions. The ribosome synthesizes all the proteins of the biosphere, and many of them begin to fold during translation in a process known as cotranslational folding. In this work we discuss current advances of this field and provide computational and experimental data that highlight the role of ribosome in the evolution of protein structures. First, we used the sequence of the Ankyrin domain from the Drosophila Notch receptor to launch a deep sequence-based search. With this strategy, we found a conserved 33-residue motif shared by different protein folds. Then, to see how the vectorial addition of the motif would generate a full structure we measured the folding on the ribosome of the Ankyrin repeat protein. Not only the on-ribosome folding data is in full agreement with classical in vitro biophysical measurements but also it provides experimental evidence on how folded proteins could have evolved by duplication and fusion of smaller fragments in the RNA world. Overall, we discuss how the ribosomal exit tunnel could be conceptualized as an active site that is under evolutionary pressure to influence protein folding.

Regulation by Different Types of Chaperones of Amyloid Transformation of Proteins Involved in the Development of Neurodegenerative Diseases

The review highlights various aspects of the influence of chaperones on amyloid proteins associated with the development of neurodegenerative diseases and includes studies conducted in our laboratory. Different sections of the article are devoted to the role of chaperones in the pathological transformation of alpha-synuclein and the prion protein. Information about the interaction of the chaperonins GroE and TRiC as well as polymer-based artificial chaperones with amyloidogenic proteins is summarized. Particular attention is paid to the effect of blocking chaperones by misfolded and amyloidogenic proteins. It was noted that the accumulation of functionally inactive chaperones blocked by misfolded proteins might cause the formation of amyloid aggregates and prevent the disassembly of fibrillar structures. Moreover, the blocking of chaperones by various forms of amyloid proteins might lead to pathological changes in the vital activity of cells due to the impaired folding of newly synthesized proteins and their subsequent processing. The final section of the article discusses both the little data on the role of gut microbiota in the propagation of synucleinopathies and prion diseases and the possible involvement of the bacterial chaperone GroE in these processes.

Is Protein Folding a Thermodynamically Unfavorable, Active, Energy-Dependent Process?

The prevailing current view of protein folding is the thermodynamic hypothesis, under which the native folded conformation of a protein corresponds to the global minimum of Gibbs free energy G. We question this concept and show that the empirical evidence behind the thermodynamic hypothesis of folding is far from strong. Furthermore, physical theory-based approaches to the prediction of protein folds and their folding pathways so far have invariably failed except for some very small proteins, despite decades of intensive theory development and the enormous increase of computer power. The recent spectacular successes in protein structure prediction owe to evolutionary modeling of amino acid sequence substitutions enhanced by deep learning methods, but even these breakthroughs provide no information on the protein folding mechanisms and pathways. We discuss an alternative view of protein folding, under which the native state of most proteins does not occupy the global free energy minimum, but rather, a local minimum on a fluctuating free energy landscape. We further argue that ΔG of folding is likely to be positive for the majority of proteins, which therefore fold into their native conformations only through interactions with the energy-dependent molecular machinery of living cells, in particular, the translation system and chaperones. Accordingly, protein folding should be modeled as it occurs in vivo, that is, as a non-equilibrium, active, energy-dependent process.

Artificial Intelligence Deconstructs Drug Targeting In Vivo by Leveraging a Transformer Platform

Lead optimization in structure-based drug design ultimately requires that the therapeutic agent be evaluated in the cellular context. However, the in vivo control of the target structure remains unyielding to computational modeling. This situation may change as transformer technologies enable a deconstruction of in vivo cooperativity steering drug-induced protein folding.

Artificial Intelligence Set to Reverse Engineer Drug Targeting in the Cell

Therapeutic drugs are required to target proteins in the cell, not in vitro. Yet, drug-induced protein folding in vivo is off limits to computational modeling efforts. This situation may change as artificial intelligence empowers molecular dynamics and enables the deconstruction of in vivo cooperativity for structural adaptation.

Conformational Strain Indicated by Ramachandran Angles for the Protein Backbone Is Only Weakly Related to the Flexibility

Studies on energy associated with free dipeptides have shown that conformers with unfavorable (ϕ,ψ) torsion angles have higher energy compared to conformers with favorable (ϕ,ψ) angles. It is expected that higher energy confers higher dynamics and flexibility to that part of the protein. Here, we explore a potential relationship between conformational strain in a residue due to unfavorable (ϕ,ψ) angles and its flexibility and dynamics in the context of protein structures. We compared flexibility of strained and relaxed residues, which are recognized based on outlier/allowed and favorable (ϕ,ψ) angles respectively, using normal-mode analysis (NMA). We also performed in-depth analysis on flexibility and dynamics at catalytic residues in protein kinases, which exhibit different strain status in different kinase structures using NMA and molecular dynamics simulations. We underline that strain of a residue, as defined by backbone torsion angles, is almost unrelated to the flexibility and dynamics associated with it. Even the overall trend observed among all high-resolution structures in which relaxed residues tend to have slightly higher flexibility than strained residues is counterintuitive. Consequently, we propose that identifying strained residues based on (ϕ,ψ) values is not an effective way to recognize energetic strain in protein structures.

Statistical Evidence for a Helical Nascent Chain

We investigate the hypothesis that protein folding is a kinetic, non-equilibrium process, in which the structure of the nascent chain is crucial. We compare actual amino acid frequencies in loops, α-helices and β-sheets with the frequencies that would arise in the absence of any amino acid bias for those secondary structures. The novel analysis suggests that while specific amino acids exist to drive the formation of loops and sheets, none stand out as drivers for α-helices. This favours the idea that the α-helix is the initial structure of most proteins before the folding process begins.

Effects of Ionic Liquids on Metalloproteins

In the past decade, innovative protein therapies and bio-similar industries have grown rapidly. Additionally, ionic liquids (ILs) have been an area of great interest and rapid development in industrial processes over a similar timeline. Therefore, there is a pressing need to understand the structure and function of proteins in novel environments with ILs. Understanding the short-term and long-term stability of protein molecules in IL formulations will be key to using ILs for protein technologies. Similarly, ILs have been investigated as part of therapeutic delivery systems and implicated in numerous studies in which ILs impact the activity and/or stability of protein molecules. Notably, many of the proteins used in industrial applications are involved in redox chemistry, and thus often contain metal ions or metal-associated cofactors. In this review article, we focus on the current understanding of protein structure-function relationship in the presence of ILs, specifically focusing on the effect of ILs on metal containing proteins.

Energy-dependent protein folding: modeling how a protein folding machine may work

Background: Proteins fold robustly and reproducibly in vivo, but many cannot fold in vitro in isolation from cellular components. Despite the remarkable progress that has been achieved by the artificial intelligence approaches in predicting the protein native conformations, the pathways that lead to such conformations, either in vitro or in vivo, remain largely unknown. The slow progress in recapitulating protein folding pathways in silico may be an indication of the fundamental deficiencies in our understanding of folding as it occurs in nature. Here we consider the possibility that protein folding in living cells may not be driven solely by the decrease in Gibbs free energy and propose that protein folding in vivo should be modeled as an active energy-dependent process. The mechanism of action of such a protein folding machine might include direct manipulation of the peptide backbone. Methods: To show the feasibility of a protein folding machine, we conducted molecular dynamics simulations that were augmented by the application of mechanical force to rotate the C-terminal amino acid while simultaneously limiting the N-terminal amino acid movements. Results: Remarkably, the addition of this simple manipulation of peptide backbones to the standard molecular dynamics simulation indeed facilitated the formation of native structures in five diverse alpha-helical peptides. Steric clashes that arise in the peptides due to the forced directional rotation resulted in the behavior of the peptide backbone no longer resembling a freely jointed chain. Conclusions: These simulations show the feasibility of a protein folding machine operating under the conditions when the movements of the polypeptide backbone are restricted by applying external forces and constraints. Further investigation is needed to see whether such an effect may play a role during co-translational protein folding in vivo and how it can be utilized to facilitate folding of proteins in artificial environments.

The road less traveled in protein folding: evidence for multiple pathways

Free Energy Landscape theory of Protein Folding, introduced over 20 years ago, implies that a protein has many paths to the folded conformation with the lowest free energy. Despite the knowledge in principle, it has been remarkably hard to detect such pathways. The lack of such observations is primarily due to the fact that no one experimental technique can detect many parts of the protein simultaneously with the time resolution necessary to see such differences in paths. However, recent technical developments and employment of multiple experimental probes and folding prompts have illuminated multiple folding pathways in a number of proteins that had all previously been described with a single path.

An ancient evolutionary connection between Ribonuclease A and EndoU families

The ribonuclease A family of proteins is well studied from the biochemical and biophysical points of view, but its evolutionary origins are obscure, as no sequences homologous to this family have been reported outside of vertebrates. Recently, the spatial structure of the ribonuclease domain from a bacterial polymorphic toxin was shown to be closely similar to the structure of vertebrate ribonuclease A. The absence of sequence similarity between the two structures prompted a speculation of convergent evolution of bacterial and vertebrate ribonuclease A-like enzymes. We show that bacterial and homologous archaeal polymorphic toxin ribonucleases with a known or predicted ribonuclease A-like fold are distant homologs of the ribonucleases from the EndoU family, found in all domains of cellular life and in viruses. We also detected a homolog of vertebrate ribonucleases A in the transcriptome assembly of the sea urchin Mesocentrotus franciscanus These observations argue for the common ancestry of prokaryotic ribonuclease A-like and ubiquitous EndoU-like ribonucleases, and suggest a better-grounded scenario for the origin of animal ribonucleases A, which could have emerged in the deuterostome lineage, either by an extensive modification of a copy of an EndoU gene, or, more likely, by a horizontal acquisition of a prokaryotic immunity-mediating ribonuclease gene.

A hybrid, bottom-up, structurally accurate, Go¯-like coarse-grained protein model

Coarse-grained (CG) protein models in the structural biology literature have improved over the years from being simple tools to understand general folding and aggregation driving forces to capturing detailed structures achieved by actual folding sequences. Here, we ask whether such models can be developed systematically from recent advances in bottom-up coarse-graining methods without relying on bioinformatic data (e.g., protein data bank statistics). We use relative entropy coarse-graining to develop a hybrid CG but Go¯-like CG peptide model, hypothesizing that the landscape of proteinlike folds is encoded by the backbone interactions, while the sidechain interactions define which of these structures globally minimizes the free energy in a unique native fold. To construct a model capable of capturing varied secondary structures, we use a new extended ensemble relative entropy method to coarse-grain based on multiple reference atomistic simulations of short polypeptides with varied α and β character. Subsequently, we assess the CG model as a putative protein backbone forcefield by combining it with sidechain interactions based on native contacts but not incorporating native distances explicitly, unlike standard Go¯ models. We test the model's ability to fold a range of proteins and find that it achieves high accuracy (∼2 Å root mean square deviation resolution for both short sequences and large globular proteins), suggesting the strong role that backbone conformational preferences play in defining the fold landscape. This model can be systematically extended to non-natural amino acids and nonprotein polymers and sets the stage for extensions to non-Go¯ models with sequence-specific sidechain interactions.

Topological descriptions of protein folding

How knotted proteins fold has remained controversial since the identification of deeply knotted proteins nearly two decades ago. Both computational and experimental approaches have been used to investigate protein knot formation. Motivated by the computer simulations of Bölinger et al. [Bölinger D, et al. (2010) PLoS Comput Biol 6:e1000731] for the folding of the [Formula: see text]-knotted α-haloacid dehalogenase (DehI) protein, we introduce a topological description of knot folding that could describe pathways for the formation of all currently known protein knot types and predicts knot types that might be identified in the future. We analyze fingerprint data from crystal structures of protein knots as evidence that particular protein knots may fold according to specific pathways from our theory. Our results confirm Taylor's twisted hairpin theory of knot folding for the [Formula: see text]-knotted proteins and the [Formula: see text]-knotted ketol-acid reductoisomerases and present alternative folding mechanisms for the [Formula: see text]-knotted phytochromes and the [Formula: see text]- and [Formula: see text]-knotted proteins.