Native Protein Structure Research Articles

Salt-Induced Dissolution of Protein Aggregates.

Protein aggregation is mediated by a complex interplay of noncovalent interactions and is associated with a broad range of aspects from debilitating human diseases to the food industry and therapeutic biotechnology. Deciphering the intricate roles of noncovalent interactions is of paramount importance for the design of effective inhibitory and disaggregation strategies, which remains a formidable challenge. By using a combination of spectroscopic and microscopic tools, here we show that the surfactant-mediated protein aggregation can be modulated by an intriguing interplay of hydrophobic and electrostatic effects. Additionally, our results illuminate the unique role of salt as a potent disaggregation inducer that alters the protein-surfactant electrostatic interactions and triggers the dissolution of preformed protein aggregates resulting in restoring the native protein structure. This unusual salt-induced dissolution and refolding offers a unique approach to regulating the balance between protein self-assembly and disassembly and will offer a potent strategy to design electrostatically targeted inhibitors.

In-silico Profiling of Deleterious Non Synonymous SNPs of Homogentisate 1, 2 Dioxygenase (HGD) Gene for Early Diagnosis of “Alkaptonuria”

In-silico characterization and molecular modelling of a single amino acid substitution in HGD (Homogentisate 1,2dioxygenase) gene are mainly caused by the deficiency of enzyme Homogentisate 1,2dioxygenase (HGD). An enzyme HGD involved in the catabolism of amino acids such as tyrosine and phenylalanine. The objective of this study was to analyse non-synonymous SNPs from highly deleterious missense mutations which affect the protein function of HGD gene. Based on 3D structure different computational algorithms were performed to identify deleterious SNPs and assess the influence of mutation by using molecular dynamics simulations and molecular docking. Bioinformatics analysis like SIFT, PolyPhen 2.0, I mutant 3.0, PANTHER, SNPs and GO were performed to predict non deleterious ns-SNPs from missense mutations. Energy minimization was done by using GROMACS followed by RMSD calculations and free-energy values under SWISS-PDB viewer and PyMoL respectively. Later, Trajectory analysis was performed using computational tools like SRIDE, CONSURF, SPPIDER, PSIPRED, FLEXPRED for predicting the probably damaged ns-SNPs. Moreover, molecular docking was performed and identified highly deleterious probably damaging mutation. By operating 10 bioinformatics analysis, we obtained 5 mutations R53W, L61P, G121R, G361R and L430H which have an adverse effect on HGD gene. The results of the ConSurf analysis showed that all of these ns-SNPs are in the highly conserved positions and influence the structure of native proteins. L61P mutation had more effect on protein structure. Later, for future studies these mutations assists to develop an effective drug for the associated disease Alkaptonuria.

Hallucinating symmetric protein assemblies.

Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of seven designs are very similar to the computational models (median root mean square deviation: 0.6 angstroms), as are three cryo-electron microscopy structures of giant 10-nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning and pave the way for the design of increasingly complex components for nanomachines and biomaterials.

PIF - A Java library for finding atomic interactions and extracting geometric features supporting the analysis of protein structures.

Proteins play an essential role in the functioning of living organisms. The enormity of the atomic interactions in proteins is essential in controlling their spatial structures and dynamics. It can also provide scientists with valuable information that help to determine the native structures of proteins. This paper presents the PIF (Protein Interaction Finder) library for the Java language, enabling the identification of selected atomic interactions (hydrogen and disulfide bonds, ionic, hydrophobic, aromatic-aromatic, sulfur-aromatic, and amino-aromatic interactions) based on the three-dimensional structure of proteins. The interaction calculation rules applied in PIF rely on documented theoretical foundations gathered from experimental studies of interactions in native protein structures. The library has a universal purpose, supporting drug discovery and development processes and protein structure modeling. Finding the atomic interactions can also deliver numerical features for various Artificial Intelligence (AI) models built for protein analysis. The conducted research comparing the results obtained with the use of the PIF library and competing tools has shown that our solution can effectively determine the interactions occurring in protein structures for entire collections of proteins. Moreover, as a solution that provides a programming interface, the PIF library can be used in any Java project, making it a universal tool.

De novo protein design of photochemical reaction centers

Natural photosynthetic protein complexes capture sunlight to power the energetic catalysis that supports life on Earth. Yet these natural protein structures carry an evolutionary legacy of complexity and fragility that encumbers protein reengineering efforts and obfuscates the underlying design rules for light-driven charge separation. De novo development of a simplified photosynthetic reaction center protein can clarify practical engineering principles needed to build new enzymes for efficient solar-to-fuel energy conversion. Here, we report the rational design, X-ray crystal structure, and electron transfer activity of a multi-cofactor protein that incorporates essential elements of photosynthetic reaction centers. This highly stable, modular artificial protein framework can be reconstituted in vitro with interchangeable redox centers for nanometer-scale photochemical charge separation. Transient absorption spectroscopy demonstrates Photosystem II-like tyrosine and metal cluster oxidation, and we measure charge separation lifetimes exceeding 100 ms, ideal for light-activated catalysis. This de novo-designed reaction center builds upon engineering guidelines established for charge separation in earlier synthetic photochemical triads and modified natural proteins, and it shows how synthetic biology may lead to a new generation of genetically encoded, light-powered catalysts for solar fuel production.

Modeling protein structure as a stable static equilibrium.

We present evidence that the protein structure can be modeled as a stable static equilibrium, determined mainly by compressive supports in the nonpolar interior. That is, protein structures derive their structural strength through the same mechanical principles as do conventional structures like bridges and buildings. This is based on the observation that the experimentally elucidated structural determinants, the interior nonpolar side chains, are engaged in strong compressions in static terms. At the same time, major substructures in proteins, helices and h-bonded strands, because of their geometry, inherently leave gaps in the space they occupy. Under the compressive force, nonpolar side chains from one substructure can protrude into the gaps of another neighboring substructure and block its motion. As a result, interlocking of substructures can form, which builds up the nonpolar core assembly. The native structure then is the one with the structurally most stable core assembly. While intuitively appealing, this is a radical departure from the prevailing thinking that protein native structure is determined by global energy minimum, which is founded on thermodynamic hypothesis. Furthermore, to develop an effective model for analyzing protein structure with conventional tools, a proper mechanical representation must be established. By proving that the stability of the equilibrium in compressive interactions is conditioned on a form of mechanical energy minimum, we show that our notion of native structure can be equally consistent with the thermodynamic hypothesis. By mathematically treating the blocking action, an interaction, as a bar, a physical object, we succeed in representing and analyzing the core assembly as truss, a conventional structure. In this paper we define and expound step-by-step increasingly integrated interlocking patterns. We then analyze the core assemblies of a large set of diverse protein database structures. A native structure can be distinguished from decoys by comparing the composition and strength of their core assemblies. We show the results for two sets of native structures vs decoys.

Binding of silver ions to alpha-lactalbumin

The process and product of silver ions binding to alpha-lactalbumin (α-LA) were studied and discussed in this paper. The aim of the work was to explain the mechanism of reaction using interdisciplinary research. The kinetic study shows that binding equilibrium of silver to α-LA is achieved after 2 min. Process was fitted to pseudo-zero, zero and Weber-Morris models and can be distinguished by two distinct steps: firstly, graduate decline in silver concentration in solution and second step of silver concentration equilibration. The determined thermodynamic parameters showed that the reaction can occur spontaneously. Complementing the experiments, molecular dynamic simulations and DFT calculations have shown that aspartic and glutamic residues have the most significant contribution in the silver binding process. Spectroscopic (ATR-FT-IR and Raman) methods were used to compare structure of native protein and after binding of silver and they confirmed that the binding occurs with participation of acidic residues of protein. Morphology and information about surface of particles were determined using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) (with energy dispersive X-ray spectroscopy - EDX). Such experiments have shown that silver forms nearly homogeneous metallic structure onto protein. Silver has shown to be released from complexes in synthetic intestine physiological fluids in the highest quantity in stomach with comparison to mimicked intestine system. Cytotoxicity study showed better biocompatibility and bioavailability of composite than control.

In silico mutational analysis to identify the role and pathogenicity of BCL-w missense variants

BackgroundIntrinsic pathway of apoptosis is generally mediated by BCL-2 (B cell lymphoma 2) family of proteins; they either induce or inhibit the apoptosis. Overexpression of BCL-2 in cancer cell may lead to delay in apoptosis. BCL-w is the pro-survival member of the BCL-2 family. BCL2L2 gene is present on chromosome number 14 in humans, and it encodes BCL-w protein; BCL-w protein is 193 amino acids residues in length. Interactions among the BCL-2 proteins are very specific. The fate of cell is determined by the ratio of pro-apoptotic proteins to pro-survival proteins. BCL-w promotes cell survival. Studies suggested that overexpression of BCL-w protein is associated with many cancers including DLBCL, BL, colorectal cancers, gastric cancers, and many more. The cause of overexpression is translocations or gene amplification which will subsequently result in cancerous activity. ProcessFor in-silico analysis, BCL2L2 gene was retrieved from UniProt (UniProt ID: Q92843). 54 missense variants have been collected in BCL-w proteins from COSMIC database. Different tools were used to detect the deleteriousness of the variants. ResultIn silico mutational study reveals how the non-synonymous mutations directly affect the protein’s native structure and its function. Variant mutational analysis with PolyPhen-2 revealed that out of 55 variants, 28 of the missense mutations was probably damaging with a score ranging from 0.9 to 1, while 24 variants were benign with a score ranging from 0 to 0.4. ConclusionsThis in silico work aims to determine how missense mutations in BCL-w protein affect the activity of the protein, the stability of the protein, and to determine the pathogenicity of the variants. Prediction of pathogenicity of variants will reveal if the missense mutation has a damaging effect on the native structure of protein or not. Prediction of protein stability will reveal whether the mutation has a stabilizing or destabilizing effect on the protein.

Constrained Layer Assignment for the Protein Burial Folding Code Accounting for Chain Connectivity.

The connection between protein sequences and tertiary structures has intrigued investigators for decades. A plausible hypothesis for the coding scheme postulates that atomic burial information obtainable from the sequence could be sufficient for structural determination when combined to sequence-independent constraints. Accordingly, folding simulations using native burial information expressed by atomic central distances, discretized into a small number L of equiprobable burial layers, have indeed been successful in reaching and distinguishing the native structure of several globular proteins. Attempted predictions of layers from sequence, however, turned out to be insufficiently accurate for most proteins. Here we explore the possibility that a nonuniform assignment of layers, which is intended to account for constraints imposed by chain connectivity, might provide a more efficient burial encoding of tertiary structures. We consider the condition that adjacent Cα-atoms along the sequence cannot occupy nonadjacent layers, in which case the information required to specify sequences of burials would be smaller. It is shown that appropriate folding behavior can still be observed in this explicitly more constrained scenario with a structure-dependent assignment intended to produce the thinnest possible layers still compatible with the imposed burial constraint. This thinnest assignment turns out to be sufficiently restrictive for the observed examples and provides appropriately thinner layers or, equivalently, a larger number of layers, for examples previously observed to indeed require more restrictive constraints when compared to counterparts of similar size, as well as the appropriate increase in number of layers for larger proteins. Implications for the general understanding of the protein folding code are discussed.

In Silico and In Vitro Analysis of MAP3773c Protein from Mycobacterium avium subsp. Paratuberculosis.

Simple SummaryParatuberculosis is a disease that is caused by Mycobacterium avium subsp. paratuberculosis, a bacterium that survives inside a cell to cause disease. This bacterium therefore needs the nutrients of the cell to survive. Zinc and iron are very important elements in its nutrition and are necessary to carry out many of its survival functions, so the cell develops mechanisms to eliminate these pathogenic bacteria to continue living. One of these mechanisms is the elimination of iron as a strategy to kill the bacteria. In this research, we took on the task of studying one of the proteins of the bacterium called MAP3773c, along with its structure, some of its properties and its particular characteristics. In relation to the affinity for zinc and iron to bind to it, we are interested in discovering and making it known to the scientific community whether MAP3773c is related to the pathology of the disease.Paratuberculosis is a disease caused by Mycobacterium avium subsp. paratuberculosis (MAP). It is of great interest to better understand the proteins involved in the pathogenicity of this organism in order to be able to identify potential therapeutic targets and design new vaccines. The protein of interest–MAP3773c–was investigated, and molecular modeling in silico, docking, cloning, expression, purification, and partial characterization of the recombinant protein were achieved. In the in silico study, it was shown that MAP3773c of MAP has 34% sequence similarity with Mycobacterium tuberculosis (MTB) FurB, which is a zinc uptake regulator (Zur) protein. The docking data showed that MAP3773c exhibits two metal-binding sites. The presence of structural Zn2+ in the purified protein was confirmed by SDS-PAGE PAR staining. The purification showed one band that corresponded to a monomer, which was confirmed by liquid chromatography–mass spectrometry (LC-MS). The presence of a monomer was verified by analyzing the native protein structure through BN-SDS-PAGE (Native Blue (BN) Two-Dimensional Electrophoresis) and BN–Western blotting. The MAP3773c protein contains structural zinc. In conclusion, our results show that MAP3773c displays the features of a Fur-type protein with two metal-binding sites, one of them coordinating structural Zn2+.

Basement Membrane of Tissue Engineered Extracellular Matrix Scaffolds Modulates Rapid Human Endothelial Cell Recellularization and Promote Quiescent Behavior After Monolayer Formation.

Off-the-shelf small diameter vascular grafts are an attractive alternative to eliminate the shortcomings of autologous tissues for vascular grafting. Bovine saphenous vein (SV) extracellular matrix (ECM) scaffolds are potentially ideal small diameter vascular grafts, due to their inherent architecture and signaling molecules capable of driving repopulating cell behavior and regeneration. However, harnessing this potential is predicated on the ability of the scaffold generation technique to maintain the delicate structure, composition, and associated functions of native vascular ECM. Previous de-cellularization methods have been uniformly demonstrated to disrupt the delicate basement membrane components of native vascular ECM. The antigen removal (AR) tissue processing method utilizes the protein chemistry principle of differential solubility to achieve a step-wise removal of antigens with similar physiochemical properties. Briefly, the cellular components of SV are permeabilized and the actomyosin crossbridges are relaxed, followed by lipophilic antigen removal, sarcomeric disassembly, hydrophilic antigen removal, nuclease digestion, and washout. Here, we demonstrate that bovine SV ECM scaffolds generated using the novel AR approach results in the retention of native basement membrane protein structure, composition (e.g., Collagen IV and laminin), and associated cell modulatory function. Presence of basement membrane proteins in AR vascular ECM scaffolds increases the rate of endothelial cell monolayer formation by enhancing cell migration and proliferation. Following monolayer formation, basement membrane proteins promote appropriate formation of adherence junction and apicobasal polarization, increasing the secretion of nitric oxide, and driving repopulating endothelial cells toward a quiescent phenotype. We conclude that the presence of an intact native vascular basement membrane in the AR SV ECM scaffolds modulates human endothelial cell quiescent monolayer formation which is essential for vessel homeostasis.

Protein conformational changes at the oil/water-interface induced by premix membrane emulsification

We present combined experimental and modelling evidence that β-lactoglobulin proteins employed as stabilizers of oil/water emulsions undergo minor but significant conformational changes during premix membrane emulsification processes. Circular Dichroism spectroscopy and Molecular Dynamics simulations reveal that the native protein structure is preserved as a metastable state after adsorption at stress-free oil/water interfaces. However, the shear stress applied to the oil droplets during their fragmentation in narrow membrane pores causes a transition into a more stable, partially unfolded interfacial state. The protein’s β-sheet content is reduced by up to 8% in a way that is largely independent of the pressure applied during emulsification, and is driven by an increase of contacts between the oil and hydrophobic residues at the expense of structural order within the protein core.

Identification of CD73 as the Antigen of an Antigen-Unknown Monoclonal Antibody Established by Exosome Immunization, and Its Antibody–Drug Conjugate Exerts an Antitumor Effect on Glioblastoma Cell Lines

Development of antibodies against the native structure of membrane proteins with multiple transmembrane domains is challenging because it is difficult to prepare antigens with native structures. Previously, we successfully developed a monoclonal antibody against multi-pass membrane protein TMEM180 by exosome immunization in rats. This approach yielded antibodies that recognized cancer-specific antigens on the exosome. In this study, we performed immunoprecipitation using magnetic beads to identify the antigen of one of the rat antibody clones, 0614, as CD73. We then converted antibody 0614 to human chimeric antibody 0614-5. Glioblastoma (GB) was the cancer type with the highest expression of CD73 in the tumor relative to healthy tissue. An antibody–drug conjugate (ADC) of 0614-5 exerted an antitumor effect on GB cell lines according to expression of CD73. The 0614-5-ADC has potential to be used to treat cancers with high CD73 expression. In addition, our strategy could be used to determine the antigen of any antibody produced by exosome immunization, which may allow the antibody to advance to new antibody therapies.

Self-Supervised Pre-training for Protein Embeddings Using Tertiary Structures

The protein tertiary structure largely determines its interaction with other molecules. Despite its importance in various structure-related tasks, fully-supervised data are often time-consuming and costly to obtain. Existing pre-training models mostly focus on amino-acid sequences or multiple sequence alignments, while the structural information is not yet exploited. In this paper, we propose a self-supervised pre-training model for learning structure embeddings from protein tertiary structures. Native protein structures are perturbed with random noise, and the pre-training model aims at estimating gradients over perturbed 3D structures. Specifically, we adopt SE(3)-invariant features as model inputs and reconstruct gradients over 3D coordinates with SE(3)-equivariance preserved. Such paradigm avoids the usage of sophisticated SE(3)-equivariant models, and dramatically improves the computational efficiency of pre-training models. We demonstrate the effectiveness of our pre-training model on two downstream tasks, protein structure quality assessment (QA) and protein-protein interaction (PPI) site prediction. Hierarchical structure embeddings are extracted to enhance corresponding prediction models. Extensive experiments indicate that such structure embeddings consistently improve the prediction accuracy for both downstream tasks.

Peroxidation of tetronic 1107 reduces protein chaperone effect

To enhance the stability of protein therapeutics, pharmaceutical companies have long used various copolymer surfactants as excipients. They act to stabilize proteins by adhering to the hydrophobic surface of the protein preventing denaturation and aggregation. However, some commonly used excipients possess polyoxyalkylene chains that are susceptible to oxidative degradation while in aqueous solution. We postulate that oxidation reactions involving the hydrophobic domains reduce the surfactant’s ability to stabilize the native protein structure. We investigated the effect of UV (λ = 254 nm) radiated poloxamine T1107 (T1107) on its ability to disaggregate DTT denatured hen egg-white lysozyme (HEWL). Peroxidation of UV irradiated T1107 was analyzed using FTIR spectroscopy, the Fe+2 to Fe+3 ion reduction assay method, and 1H NMR. Our results indicate that increased UV irradiation led to structural changes in T1107, specifically the addition of a carbonyl on the formate group. The structural change decreased T1107’s ability to disaggregate HEWL thus supporting our hypothesis. These results indicate that peroxide content is an important parameter to control in polyoxyalkylene-based excipients.

Non-Equilibrium Protein Folding and Activation by ATP-Driven Chaperones.

Recent experimental studies suggest that ATP-driven molecular chaperones can stabilize protein substrates in their native structures out of thermal equilibrium. The mechanism of such non-equilibrium protein folding is an open question. Based on available structural and biochemical evidence, I propose here a unifying principle that underlies the conversion of chemical energy from ATP hydrolysis to the conformational free energy associated with protein folding and activation. I demonstrate that non-equilibrium folding requires the chaperones to break at least one of four symmetry conditions. The Hsp70 and Hsp90 chaperones each break a different subset of these symmetries and thus they use different mechanisms for non-equilibrium protein folding. I derive an upper bound on the non-equilibrium elevation of the native concentration, which implies that non-equilibrium folding only occurs in slow-folding proteins that adopt an unstable intermediate conformation in binding to ATP-driven chaperones. Contrary to the long-held view of Anfinsen’s hypothesis that proteins fold to their conformational free energy minima, my results predict that some proteins may fold into thermodynamically unstable native structures with the assistance of ATP-driven chaperones, and that the native structures of some chaperone-dependent proteins may be shaped by their chaperone-mediated folding pathways.

Sample Processing Considerations for Protein Stability Studies of Low Concentration Biofluid Samples using Differential Scanning Calorimetry.

The analysis of biofluid samples with low protein content (e.g., urine or saliva) can be challenging for downstream analysis methods with limited sensitivity. To circumvent this problem, sample processing methods are employed to increase the protein concentration in analyzed samples. However, for some techniques, like differential scanning calorimetry (DSC) that characterizes thermally-induced unfolding of biomolecules, sample processing must not affect native protein structure and stability. We evaluated centrifugal concentration and stirred cell ultrafiltration, two common methods of sample concentration characterized by a low risk of protein denaturation, with the goal of establishing a protocol for DSC analysis of low concentration biospecimens. Our studies indicate that both methods can affect protein stability assessed by DSC and, even after optimization of several parameters, the obtained DSC profile (thermogram) suggested that sample processing affects the structure or intermolecular interactions of component proteins contributing to altered thermal stability detectable by DSC. We also found a relationship between changes in thermograms and low protein concentration, indicating that diluting biospecimens to concentrations below 0.1 mg/mL can perturb the intermolecular environment and affect the structure of proteins present in the solution. Dilution of samples below 0.1 mg/mL, as well as concentration of samples with low protein content, resulted in affected thermogram shapes suggesting changes in protein stability. This should be taken into account when concentrating dilute samples or employing techniques that lower the protein concentration (e.g., fractionation), when downstream applications include techniques, such as DSC, that require the preservation of native protein forms.

Effects of ultrasound on the structural and emulsifying properties and interfacial properties of oxidized soybean protein aggregates

Oxidative attack leads to the oxidative aggregation and structural and functional feature weakening of soybean protein. We aimed to investigate the impact of ultrasonic treatment (UT) with different intensities on the structure, emulsifying features and interfacial features of oxidized soybean protein aggregates (OSPI). The results showed that oxidative treatment could disrupt the native soy protein (SPI) structure by promoting the formation of oxidized aggregates with β1-sheet structures through hydrophobic interactions. These changes led to a decrease in the solubility, emulsification ability and interfacial activity of soybean protein. After low-power ultrasound (100 W, 200 W) treatment, the relative contents of β1-sheets, β2-sheets, random coils, and disulfide bonds of the OSPI increased while the surface hydrophobicity, absolute ζ-potential value and free sulfhydryl content decreased. Moreover, protein aggregates with larger particle sizes and poor solubility were formed. The emulsions prepared using the OSPI showed bridging flocculation and decreased protein adsorption and interfacial tension. After applying medium-power ultrasound (300 W, 400 W, and 500 W) treatments, the OSPI solubility increased and particle size decreased. The α-helix and β-turn contents, surface hydrophobicity and absolute ζ-potential value increased, the structure unfolded, and the disulfide bond content decreased. These changes improved the emulsification activity and emulsion state of the OSPI and increased the protein adsorption capacity and interfacial tension of the emulsion. However, after a high-power ultrasound (600 W) treatment, the OSPI showed a tendency to reaggregate, which had a certain negative effect on the emulsification activity and interfacial activity. The results showed that UT at an appropriate power could depolymerize OSPI and improve the emulsification and interfacial activity of soybean protein.

Using steered molecular dynamic tension for assessing quality of computational protein structure models.

The native structures of proteins, except for notable exceptions of intrinsically disordered proteins, in general take their most stable conformation in the physiological condition to maintain their structural framework so that their biological function can be properly carried out. Experimentally, the stability of a protein can be measured by several means, among which the pulling experiment using the atomic force microscope (AFM) stands as a unique method. AFM directly measures the resistance from unfolding, which can be quantified from the observed force-extension profile. It has been shown that key features observed in an AFM pulling experiment can be well reproduced by computational molecular dynamics simulations. Here, we applied computational pulling for estimating the accuracy of computational protein structure models under the hypothesis that the structural stability would positively correlated with the accuracy, i.e. the closeness to the native, of a model. We used in total 4929 structure models for 24 target proteins from the Critical Assessment of Techniques of Structure Prediction (CASP) and investigated if the magnitude of the break force, that is, the force required to rearrange the model's structure, from the force profile was sufficient information for selecting near-native models. We found that near-native models can be successfully selected by examining their break forces suggesting that high break force indeed indicates high stability of models. On the other hand, there were also near-native models that had relatively low peak forces. The mechanisms of the stability exhibited by the break forces were explored and discussed.

Synthetic Sulfated Polymers Control Amyloid Aggregation of Ovine Prion Protein and Decrease Its Toxicity.

Amyloid aggregation, including aggregation and propagation of prion protein, is a key factor in numerous human diseases, so-called amyloidosis, with a very poor ability for treatment or prevention. The present work describes the effect of sulfated or sulfonated polymers (sodium dextran sulfate, polystyrene sulfonate, polyanethole sulfonate, and polyvinyl sulfate) on different stages of amyloidogenic conversion and aggregation of the prion protein, which is associated with prionopathies in humans and animals. All tested polymers turned out to induce amyloid conversion of the ovine prion protein. As suggested from molecular dynamics simulations, this effect probably arises from destabilization of the native prion protein structure by the polymers. Short polymers enhanced its further aggregation, whereas addition of high-molecular poly(styrene sulfonate) inhibited amyloid fibrils formation. According to the seeding experiments, the protein–polymer complexes formed after incubation with poly(styrene sulfonate) exhibited significantly lower amyloidogenic capacity compared with the control fibrils of the free prion protein. The cytotoxicity of soluble oligomers was completely inhibited by treatment with poly(styrene sulfonate). To summarize, sulfonated polymers are a promising platform for the formulation of a new class of anti-prion and anti-amyloidosis therapeutics.