PASTA 2.0: an improved server for protein aggregation prediction

Production, characterisation, and biological properties of Tenebrio molitor-derived oligopeptides

Three protein hydrolysates from Tenebrio molitor were obtained by enzymatic hydrolysis employing two food-grade proteases (i.e. Alcalase and Flavourzyme), and a complete characterisation of their composition was done. The digestion-derived products were obtained using the INFOGEST protocol. In vitro antioxidant activity and anti-inflammatory activities were evaluated. Tenebrio molitor flour and the protein hydrolysates showed a high ability to scavenge the DPPH radical (EC50 values from 0.30 to 0.87 mg/mL). The hydrolysate obtained with a combination of the two food-grade proteases could decrease the gene expression of pro-inflammatory genes after being digested. Furthermore, the peptidome was fully determined for the first time for T. molitor hydrolysates and digests, and 40 peptides were selected based on their bioactivity to be evaluated by in silico tools, including prediction tools and molecular docking. These results provide new perspectives on the use of edible insects as sustainable and not nutritionally disadvantageous food for human consumption.

Elucidating the Molecular Basis of 14-3-3 Interaction with α-Synuclein: Insights from Molecular Dynamics Simulations and the Design of a Novel Protein-Protein Interaction Inhibitor

Parkinson's disease is a widespread age-related neurodegenerative disorder characterized by the loss of dopaminergic neurons in the midbrain along with the appearance of protein aggregates, termed as "Lewy bodies" in the surviving neuronal cells. The components of Lewy bodies include proteins such as α-synuclein, 14-3-3, Parkin, and LRRK2, along with other cellular organelles, which, in their native state, perform a plethora of vital biological functions within the human biome. Formation of these aggregates renders these components inactive, thereby interfering with homeostasis. In this regard, the current study attempts to investigate the complexation behavior of all human-based 14-3-3 isoforms with α-synuclein via a combination of classical and enhanced sampling techniques and thereby determine the causality of these protein-protein interactions. The study indicated that upon complexation, the aggregation propensity of both 14-3-3 and α-synuclein increases, and this increment is propelled by the interfacial residues on either protein. Furthermore, mutagenesis studies revealed that Lys214 of 14-3-3 (henceforth termed K214A) is crucial for the formation of this binary complex. Principal component analysis combined with clustering studies unveiled the stability of these complexes in terms of their conformational distribution across the entire MD trajectory. For K214A, these clustered states were sparsely located, thereby making the transitions between them slightly difficult. Dynamic cross-correlation maps (DCCM) revealed the role of residues in the range 80-130 of 14-3-3 having a potential allosteric role in driving this complexation process. Finally, a novel peptide-based supramolecular inhibitor was designed, which exhibited higher proficiency in limiting the 14-3-3/α-synuclein interaction compared to the previous inhibitor model. It was also revealed that the presence of this inhibitor induces structural rigidity in α-synuclein, making changes in its conformations extremely difficult, as observed through Umbrella Sampling studies. Based on available information, the current study provides an insight into the molecular-level understanding of protein-protein interactions underlying Parkinson's disease and adds on to the methods of devising novel therapeutic approaches to treat the same.

Large-scale investigation of species-specific orphan genes in the human gut microbiome elucidates their evolutionary origins

Species-specific genes, also known as orphans, are ubiquitous across life's domains. In prokaryotes, species-specific orphan genes (SSOGs) are mostly thought to originate in external elements such as viruses followed by horizontal gene transfer, whereas the scenario of native origination, through rapid divergence or de novo, is mostly dismissed. However, quantitative evidence supporting either scenario is lacking. Here, we systematically analyzed genomes from 4644 human gut microbiome species and identified more than 600,000 unique SSOGs, representing an average of 2.6% of a given species' pangenome. These sequences are mostly rare within each species yet show signs of purifying selection. Overall, SSOGs use optimal codons less frequently, and their proteins are more disordered than those of conserved genes (i.e., non-SSOGs). Importantly, across species, the GC content of SSOGs closely matches that of conserved ones. In contrast, the ∼5% of SSOGs that share similarity to known viral sequences have distinct characteristics, including lower GC content. Thus, SSOGs with similarity to viruses differ from the remaining SSOGs, contrasting an external origination scenario for most of them. By examining the orthologous genomic region in closely related species, we show that a small subset of SSOGs likely evolved natively de novo and find that these genes also differ in their properties from the remaining SSOGs. Our results challenge the notion that external elements are the dominant source of prokaryotic genetic novelty and will enable future studies into the biological role and relevance of species-specific genes in the human gut.

Exploring pathological link between antimicrobial and amyloid peptides

Amyloid peptides (AMYs) and antimicrobial peptides (AMPs) are considered as the two distinct families of peptides, characterized by their unique sequences, structures, biological functions, and specific pathological targets. However, accumulating evidence has revealed intriguing pathological connections between these peptide families in the context of microbial infection and neurodegenerative diseases. Some AMYs and AMPs share certain structural and functional characteristics, including the ability to self-assemble, the presence of β-sheet-rich structures, and membrane-disrupting mechanisms. These shared features enable AMYs to possess antimicrobial activity and AMPs to acquire amyloidogenic properties. Despite limited studies on AMYs-AMPs systems, the cross-seeding phenomenon between AMYs and AMPs has emerged as a crucial factor in the bidirectional communication between the pathogenesis of neurodegenerative diseases and host defense against microbial infections. In this review, we examine recent developments in the potential interplay between AMYs and AMPs, as well as their pathological implications for both infectious and neurodegenerative diseases. By discussing the current progress and challenges in this emerging field, this account aims to inspire further research and investments to enhance our understanding of the intricate molecular crosstalk between AMYs and AMPs. This knowledge holds great promise for the development of innovative therapies to combat both microbial infections and neurodegenerative disorders.

Hereditary Amyloidosis: Insights Into a Fibrinogen A Variant Protein

Amyloidosis are a group of diseases in which soluble proteins aggregate and deposit in fibrillar conformation extracellularly in tissues. The effectiveness of therapeutic strategies depends on the specific protein involved, being crucial to accurately determine its nature. Moreover, following the diagnosis, the search for the mutation within relatives allows the clinical advice. Here we report the precise diagnosis and explored the possible reasons of the structural pathogenicity for a renal amyloidosis related to a fibrinogen Aα-chain variant. Whole-exome sequencing and GATK calling pipeline were leveraged to characterize the protein variant present in a patient with kidney failure. Bioinformatics strategies were applied to suggest potential explanations of the variants aggregation. Our pipeline allowed the identification of a single-point variant of fibrinogen Aα-chain, which opened the possibility of curative transplantation. In silico structural analysis suggested that the pathogenicity of the variant may be attributed to a heightened susceptibility to yield a peptide prone to deposit as an oligomer with a β-sheet structure. Exploiting the comprehensive coverage of whole-genome sequencing, we managed to fill a vacant stage in the diagnosis of hereditary amyloidosis and to stimulate the advancement in biomedicine.

Photocontrolled Reversible Amyloid Fibril Formation of Parathyroid Hormone-Derived Peptides

Peptide fibrillization is crucial in biological processes such as amyloid-related diseases and hormone storage, involving complex transitions between folded, unfolded, and aggregated states. We here employ light to induce reversible transitions between aggregated and nonaggregated states of a peptide, linked to the parathyroid hormone (PTH). The artificial light-switch 3-{[(4-aminomethyl)phenyl]diazenyl}benzoic acid (AMPB) is embedded into a segment of PTH, the peptide PTH25-37, to control aggregation, revealing position-dependent effects. Through in silico design, synthesis, and experimental validation of 11 novel PTH25-37-derived peptides, we predict and confirm the amyloid-forming capabilities of the AMPB-containing peptides. Quantum-chemical studies shed light on the photoswitching mechanism. Solid-state NMR studies suggest that β-strands are aligned parallel in fibrils of PTH25-37, while in one of the AMPB-containing peptides, β-strands are antiparallel. Simulations further highlight the significance of π-π interactions in the latter. This multifaceted approach enabled the identification of a peptide that can undergo repeated phototriggered transitions between fibrillated and defibrillated states, as demonstrated by different spectroscopic techniques. With this strategy, we unlock the potential to manipulate PTH to reversibly switch between active and inactive aggregated states, representing the first observation of a photostimulus-responsive hormone.

Cu(II) Specifically Disassembles Insulin Amyloid Nanostructures via Direct Interaction with Cross-β Fibrils

In this work, we demonstrate direct evidence of the antiamyloid potential of Cu(II) ions against amyloid formation of insulin. The Cu(II) ions were found to efficiently disassemble the preformed amyloid nanostructures into soluble species and suppress monomer fibrillation under aggregation-prone conditions. The direct interaction of Cu(II) ions with the cross-β structure of amyloid fibrils causes substantial disruption of both the interchain and intrachain interactions, predominantly the H-bonds and hydrophobic contacts. Further, the Cu(II) ions show a strong affinity for the aggregation-prone conformers of the protein and inhibit their spontaneous self-assembly. These results reveal the possible molecular mechanism for the antiamyloidogenic potential of Cu(II) which could be important for the development of metal-ion specific therapeutic strategies against amyloid linked complications.

Authentic hSAA related with AA amyloidosis: New method of purification, folding and amyloid polymorphism

The secondary amyloidosis of humans is caused by the formation of hSAA fibrils in different organs and tissues. Until now hSAA was thought to have low amyloidogenicity in vitro and the majority of SAA aggregation experiments were done using murine protein or hSAA non-pathogenic isoforms. In this work a novel purification method for recombinant hSAA was introduced, enabling to obtain monomeric protein capable of amyloid aggregation under physiological conditions. The stability and amyloid aggregation of hSAA have been examined using a wide range of biophysical methods. It was shown that the unfolding of monomeric protein occurs through the formation of molten globule-like intermediate state. Polymorphism of hSAA amyloids was discovered to depend on the solution pH. At pH 8.5, rapid protein aggregation occurs, which leads to the formation of twisted short fibrils. Even a slight decrease of the pH to 7.8 results in delayed aggregation with the formation of long straight amyloids composed of laterally associated protofilaments. Limited proteolysis experiments have shown that full-length hSAA is involved in the formation of intermolecular interactions in both amyloid polymorphs. The results obtained, and the experimental approach used in this study can serve as a basis for further research on the mechanism of authentic hSAA amyloid formation.

Type I Hsp40s/DnaJs aggregates exhibit features reminiscent of amyloidogenic structures

A rise in temperature triggers a structural change in the human Type I 40 kDa heat shock protein (Hsp40/DnaJ), known as DNAJA1. This change leads to a less compact structure, characterized by an increased presence of solvent-exposed hydrophobic patches and β-sheet-rich regions. This transformation is validated by circular dichroism, thioflavin T binding, and Bis-ANS assays. The formation of this β-sheet-rich conformation, which is amplified in the absence of zinc, leads to protein aggregation. This aggregation is induced not only by high temperatures but also by low ionic strength and high protein concentration. The aggregated conformation exhibits characteristics of an amyloidogenic structure, including a distinctive X-ray diffraction pattern, seeding competence (which stimulates the formation of amyloid-like aggregates), cytotoxicity, resistance to SDS, and fibril formation. Interestingly, the yeast Type I Ydj1 also tends to adopt a similar β-sheet-rich structure under comparable conditions, whereas Type II Hsp40s, whether human or from yeast, do not. Moreover, Ydj1 aggregates were found to be cytotoxic. Studies using DNAJA1- and Ydj1-deleted mutants suggest that the zinc-finger region plays a crucial role in amyloid formation. Our discovery of amyloid aggregation in a C-terminal deletion mutant of DNAJA1, which resembles a spliced homolog expressed in the testis, implies that Type I Hsp40 co-chaperones may generate amyloidogenic species in vivo.

Engineered droplet-forming peptide as photocontrollable phase modulator for fused in sarcoma protein

The assembly and disassembly of biomolecular condensates are crucial for the subcellular compartmentalization of biomolecules in the control of cellular reactions. Recently, a correlation has been discovered between the phase transition of condensates and their maturation (aggregation) process in diseases. Therefore, modulating the phase of condensates to unravel the roles of condensation has become a matter of interest. Here, we create a peptide-based phase modulator, JSF1, which forms droplets in the dark and transforms into amyloid-like fibrils upon photoinitiation, as evidenced by their distinctive nanomechanical and dynamic properties. JSF1 is found to effectively enhance the condensation of purified fused in sarcoma (FUS) protein and, upon light exposure, induce its fibrilization. We also use JSF1 to modulate the biophysical states of FUS condensates in live cells and elucidate the relationship between FUS phase transition and FUS proteinopathy, thereby shedding light on the effect of protein phase transition on cellular function and malfunction.

AggreProt: a web server for predicting and engineering aggregation prone regions in proteins

Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.

The Potent PHL4 Transcription Factor Effector Domain Contains Significant Disorder

The phosphate-starvation response transcription-factor protein family is essential to plant response to low-levels of phosphate. Proteins in this transcription factor (TF) family act by altering various gene expression levels, such as increasing levels of the acid phosphatase proteins which catalyze the conversion of inorganic phosphates to bio-available compounds. There are few structural characterizations of proteins in this TF family, none of which address the potent TF activation domains. The phosphate-starvation response-like protein-4 (PHL4) protein from this family has garnered interest due to the unusually high TF activation activity of the N-terminal domain. Here, we demonstrate using solution nuclear magnetic resonance (NMR) measurements that the PHL4 N-terminal activating TF effector domain is mainly an intrinsically disordered domain of over 200 residues, and that the C-terminal region of PHL4 is also disordered. Additionally, we present evidence from size-exclusion chromatography, diffusion NMR measurements, and a cross-linking assay suggesting full-length PHL4 forms a tetrameric assembly. Together, the data indicate the N- and C-terminal disordered domains in PHL4 flank a central folded region that likely forms the ordered oligomer of PHL4. This work provides a foundation for future studies detailing how the conformations and molecular motions of PHL4 change as it acts as a potent activator of gene expression in phosphate metabolism. Such a detailed mechanistic understanding of TF function will benefit genetic engineering efforts that take advantage of this activity to boost transcriptional activation of genes across different organisms.

Apolipoprotein C-III amyloidosis in white lions (Panthera leo)

Apolipoprotein C-III (ApoC-III) amyloidosis in humans is a hereditary amyloidosis caused by a D25V mutation in the APOC3 gene. This condition has only been reported in a French family and not in animals. We analyzed a 19-year-old white lion (Panthera leo) that died in a Japanese safari park and found renal amyloidosis characterized by severe deposition confined to the renal corticomedullary border zone. Mass spectrometry-based proteomic analysis identified ApoC-III as a major component of renal amyloid deposits. Amyloid deposits were also positive for ApoC-III by immunohistochemistry. Based on these results, this case was diagnosed as ApoC-III amyloidosis for the first time in nonhuman animals. Five additional white lions were also tested for amyloid deposition retrospectively. ApoC-III amyloid deposition was detected in 3 white lions aged 19 to 21 years but not in 2 cases aged 0.5 and 10 years. Genetic analysis of white and regular-colored lions revealed that the APOC3 sequences of the lions were identical, regardless of amyloid deposition. These results suggest that ApoC-III amyloidosis in lions, unlike in humans, may not be a hereditary condition but an age-related condition. Interestingly, lion ApoC-III has a Val30 substitution compared with other species of Panthera that have Met30. Structural predictions suggest that the conformation of ApoC-III with Met30 and ApoC-III with Val30 are almost identical, but this substitution may alter the ability to bind to lipids. As with the D25V mutation in human ApoC-III, the Val30 substitution in lions may increase the proportion of free ApoC-III, leading to amyloid formation.

Stability of Protein Pharmaceuticals: Recent Advances

There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'

Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors

Background

Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

Results

The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past 25 years, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 186 VIPs, resulting in a total of 403 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

Conclusions

VIPdb version 2 summarizes 403 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications.

Availability

VIPdb version 2 is available at https://genomeinterpretation.org/vipdb.

Novel Antioxidant Self-Assembled Peptides Extracted from Azumapecten farreri Meat: In Vitro- and In Silico-Assisted Identification

Previous studies have found that the self-assembled supramolecules of Azumapecten farreri meat peptides have antioxidant effects. Therefore, this study aims to isolate and identify novel antioxidant peptides with self-assembly characteristics and analyze their structure-activity relationship through molecular docking and molecular dynamics simulation. The in vitro results show that as the purification steps increased, the antioxidant activity of peptides became stronger. Additionally, the purification step did not affect its pH-responsive self-assembly. Using LC-MS/MS, 298 peptide sequences were identified from the purified fraction PF1, and 12 safe and antioxidant-active peptides were acquired through in silico screening. The molecular docking results show that they had good binding interactions with key antioxidant-related protein ligands (KEAP1 (Kelch-like ECH-associated protein 1) and MPO (myeloperoxidase)). The peptide QPPALNDSYLYGPQ, with the lowest docking energy, was selected for a 100 ns molecular dynamics simulation. The results show that the peptide QPPALNDSYLYGPQ exhibited excellent stability when docked with KEAP1 and MPO, thus exerting antioxidant effects by regulating the KEAP1-NRF2 pathway and inhibiting MPO activity. This study further validates the antioxidant and self-assembling properties of the self-assembled supramolecules of Azumapecten farreri meat peptide and shows its potential for developing new, effective, and stable antioxidants.

Cryo-EM and Solid State NMR Together Provide a More Comprehensive Structural Investigation of Protein Fibrils

The Tropomyosin 1 isoform I/C C-terminal domain (Tm1-LC) fibril structure is studied jointly with cryogenic electron microscopy (cryo-EM) and solid state nuclear magnetic resonance (NMR). This study demonstrates the complementary nature of these two structural biology techniques. Chemical shift assignments from solid state NMR are used to determine the secondary structure at the level of individual amino acids, which is faithfully seen in cryo-EM reconstructions. Additionally, solid state NMR demonstrates that the region not observed in the reconstructed cryo-EM density is primarily in a highly mobile random coil conformation rather than adopting multiple rigid conformations. Overall, this study illustrates the benefit of investigations combining cryo-EM and solid state NMR to investigate protein fibril structure.

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

The effects of histidine substitution of aromatic residues on the amyloidogenic properties of the fragment 264-277 of nucleophosmin 1

Histidine (His) plays a key role in mediating protein interactions and its unique side chain determines pH responsive self-assembling processes and thus in the formation of nanostructures. In this study, To identify novel self-assembling bioinspired sequences, we analyzed a series of peptide sequences obtained through the point mutation of aromatic residues of 264-277 fragment of nucleophosmin 1 (NPM1) with single and double histidines. Through several orthogonal biophysical techniques and under different pH and ionic strength conditions we evaluated the effects of these substitutions in the amyloidogenic features of derived peptides. The results clearly indicate that both the type of aromatic mutated residue and its position can have different effect on amyloid-like behaviors. They corroborate the crucial role exerted by Tyr271 in the self-assembling process of CTD of NPM1 in AML mutated form and add novel insights in the accurate investigation of how side chain orientations can determine successful design of innovative bioinspired materials.

ENAM Mutations Can Cause Hypomaturation Amelogenesis Imperfecta

Amelogenesis imperfecta (AI) is a diverse group of inherited diseases featured by various presentations of enamel malformations that are caused by disturbances at different stages of enamel formation. While hypoplastic AI suggests a thickness defect of enamel resulting from aberrations during the secretory stage of amelogenesis, hypomaturation AI indicates a deficiency of enamel mineralization and hardness established at the maturation stage. Mutations in ENAM, which encodes the largest enamel matrix protein, enamelin, have been demonstrated to cause generalized or local hypoplastic AI. Here, we characterized 2 AI families with disparate hypoplastic and hypomaturation enamel defects and identified 2 distinct indel mutations at the same location of ENAM, c588+1del and c.588+1dup. Minigene splicing assays demonstrated that they caused frameshifts and truncation of ENAM proteins, p.Asn197Ilefs*81 and p.Asn197Glufs*25, respectively. In situ hybridization of Enam on mouse mandibular incisors confirmed its restricted expression in secretory stage ameloblasts and suggested an indirect pathogenic mechanism underlying hypomaturation AI. In silico analyses indicated that these 2 truncated ENAMs might form amyloid structures and cause protein aggregation with themselves and with wild-type protein through the added aberrant region at their C-termini. Consistently, protein secretion assays demonstrated that the truncated proteins cannot be properly secreted and impede secretion of wild-type ENAM. Moreover, compared to the wild-type, overexpression of the mutant proteins significantly increased endoplasmic reticulum stress and upregulated the expression of unfolded protein response (UPR)-related genes and TNFRSF10B, a UPR-controlled proapoptotic gene. Caspase, terminal deoxynucleotidyl transferase UTP nick-end labeling (TUNEL), and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assays further revealed that both truncated proteins, especially p.Asn197Ilefs*81, induced cell apoptosis and decreased cell survival, suggesting that the 2 ENAM mutations cause AI through ameloblast cell pathology and death rather than through a simple loss of function. This study demonstrates that an ENAM mutation can lead to generalized hypomaturation enamel defects and suggests proteinopathy as a potential pathogenesis for ENAM-associated AI.

Nuclear aggregates of NONO/SFPQ and A-to-I-edited RNA in Parkinson's disease and dementia with Lewy bodies

Neurodegenerative diseases are commonly classified as proteinopathies that are defined by the aggregation of a specific protein. Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are classified as synucleinopathies since α-synuclein (α-syn)-containing inclusions histopathologically define these diseases. Unbiased biochemical analysis of PD and DLB patient material unexpectedly revealed novel pathological inclusions in the nucleus comprising adenosine-to-inosine (A-to-I)-edited mRNAs and NONO and SFPQ proteins. These inclusions showed no colocalization with Lewy bodies and accumulated at levels comparable to α-syn. NONO and SFPQ aggregates reduced the expression of the editing inhibitor ADAR3, increasing A-to-I editing mainly within human-specific, Alu-repeat regions of axon, synaptic, and mitochondrial transcripts. Inosine-containing transcripts aberrantly accumulated in the nucleus, bound tighter to recombinant purified SFPQ in vitro, and potentiated SFPQ aggregation in human dopamine neurons, resulting in a self-propagating pathological state. Our data offer new insight into the inclusion composition and pathophysiology of PD and DLB.

Structural effects of charge destabilization and amino acid substitutions in amyloid fragments of CsgA

The most studied functional amyloid is the CsgA, major curli subunit protein, which is produced by numerous strains of Enterobacteriaceae. Although CsgA sequences are highly conserved, they exhibit species diversity, which reflects the specific evolutionary and functional adaptability of the major curli subunit. Herein, we performed bioinformatics analyses to uncover the differences in the amyloidogenic properties of the R4 fragments in Escherichia coli and Salmonella enterica and proposed four mutants for more detailed studies: M1, M2, M3, and M4. The mutated sequences were characterized by various experimental techniques, such as circular dichroism, ATR-FTIR, FT-Raman, thioflavin T, transmission electron microscopy and confocal microscopy. Additionally, molecular dynamics simulations were performed to determine the role of buffer ions in the aggregation process. Our results demonstrated that the aggregation kinetics, fibril morphology, and overall structure of the peptide were significantly affected by the positions of charged amino acids within the repeat sequences of CsgA. Notably, substituting glycine with lysine resulted in the formation of distinctive spherically packed globular aggregates. The differences in morphology observed are attributed to the influence of phosphate ions, which disrupt the local electrostatic interaction network of the polypeptide chains. This study provides knowledge on the preferential formation of amyloid fibrils based on charge states within the polypeptide chain.

CORDAX web server: an online platform for the prediction and 3D visualization of aggregation motifs in protein sequences

MOTIVATION

Proteins, the molecular workhorses of biological systems, execute a multitude of critical functions dictated by their precise three-dimensional structures. In a complex and dynamic cellular environment, proteins can undergo misfolding, leading to the formation of aggregates that take up various forms, including amorphous and ordered aggregation in the shape of amyloid fibrils. This phenomenon is closely linked to a spectrum of widespread debilitating pathologies, such as Alzheimer's disease, Parkinson's disease, type-II diabetes, and several other proteinopathies, but also hampers the engineering of soluble agents, as in the case of antibody development. As such, the accurate prediction of aggregation propensity within protein sequences has become pivotal due to profound implications in understanding disease mechanisms, as well as in improving biotechnological and therapeutic applications.

RESULTS

We previously developed Cordax, a structure-based predictor that utilizes logistic regression to detect aggregation motifs in protein sequences based on their structural complementarity to the amyloid cross-beta architecture. Here, we present a dedicated web server interface for Cordax. This online platform combines several features including detailed scoring of sequence aggregation propensity, as well as 3D visualization with several customization options for topology models of the structural cores formed by predicted aggregation motifs. In addition, information is provided on experimentally determined aggregation-prone regions that exhibit sequence similarity to predicted motifs, scores, and links to other predictor outputs, as well as simultaneous predictions of relevant sequence propensities, such as solubility, hydrophobicity, and secondary structure propensity.

AVAILABILITY AND IMPLEMENTATION

The Cordax webserver is freely accessible at https://cordax.switchlab.org/.

Formation of Calprotectin Inhibits Amyloid Aggregation of S100A8 and S100A9 Proteins

Calcium-binding S100A8 and S100A9 proteins play a significant role in various disorders due to their pro-inflammatory functions. Substantially, they are also relevant in neurodegenerative disorders via the delivery of signals for the immune response. However, at the same time, they can aggregate and accelerate the progression of diseases. Natively, S100A8 and S100A9 exist as homo- and heterodimers, but upon aggregation, they form amyloid-like oligomers, fibrils, or amorphous aggregates. In this study, we aimed to elucidate the aggregation propensities of S100A8, S100A9, and their heterodimer calprotectin by investigating aggregation kinetics, secondary structures, and morphologies of the aggregates. For the first time, we followed the in vitro aggregation of S100A8, which formed spherical aggregates, unlike the fibrillar structures of S100A9 under the same conditions. The aggregates were sensitive to amyloid-specific ThT and ThS dyes and had a secondary structure composed of β-sheets. Similarly to S100A9, S100A8 protein was stabilized by calcium ions, resulting in aggregation inhibition. Finally, the formation of S100A8 and S100A9 heterodimers stabilized the proteins in the absence of calcium ions and prevented their aggregation.

Molecular Dynamics Insights into the Aggregation Behavior of N-Terminal β-Lactoglobulin Peptides

β-lactoglobulin (BLG) forms amyloid-like aggregates at high temperatures, low pH, and low ionic strengths. At a pH below 2, BLG undergoes hydrolysis into peptides, with N-terminal peptides 1-33 and 1-52 being prone to fibrillization, forming amyloid-like fibrils. Due to their good mechanical properties, BLG amyloids demonstrate great potential for diverse applications, including biosensors, nanocomposites, and catalysts. Consequently, further studies are essential to comprehensively understand the factors governing the formation of BLG amyloid-like morphologies. In this study, all-atom molecular dynamics simulations were employed to explore the aggregation of N-terminal 1-33 and 1-52 BLG peptides under conditions of pH 2 and at 10 mM NaCl concentration. The simulations revealed that the peptides spontaneously assembled into aggregates of varying sizes. The aggregation process was enabled by the low charge of peptides and the presence of hydrophobic residues within them. As the peptides associated into aggregates, there was a concurrent increase in β-sheet structures and the establishment of hydrogen bonds, enhancing the stability of the aggregates. Notably, on average, 1-33 peptides formed larger aggregates compared to their 1-52 counterparts, while the latter exhibited a slightly higher content of β-sheets and higher cluster orderliness. The applied approach facilitated insights into the early stages of amyloid-like aggregation and molecular-level insight into the formation of β-sheets, which serve as nucleation points for further fibril growth.

Interaction and simulation studies suggest the possible molecular targets of intrinsically disordered amyloidogenic antimicrobial peptides in Acinetobacter baumannii

Acinetobacter baumannii is one of the causing agents of nosocomial infections. A wide range of antibiotics fails to work against these pathogens. Hence, there is an urgent requirement to develop other therapeutics to solve this problem. Antimicrobial peptides (AMPs) are a diverse group of naturally occurring peptides that have the ability to kill diverse groups of microorganisms. The major challenge of using AMPs as therapeutics is their unstable nature and the fact that most of their molecular targets are still unknown. In this study, we have selected intrinsically disordered and amyloidogenic AMPs, showing activity against A. baumannii, that is, Bactenecin, Cath BF, Citropin 1.1, DP7, NA-CATH, Tachyplesin, and WAM-1. To identify the probable target of these AMPs in A. baumannii, calculation of docking score, binding energy, dissociation constant, and molecular dynamics analysis was performed with selected seventeen possible molecular targets. The result showed that the most probable molecular targets of most of the intrinsically disordered amyloidogenic AMPs were UDP-N-acetylenol-pyruvoyl-glucosamine reductase (MurB), followed by 33-36 kDa outer membrane protein (Omp 33-36), UDP-N-acetylmuramoyl-l-alanyl-d-glutamate-2,6-diaminopimelate ligase (MurE), and porin Subfamily Protein (PorinSubF). Further, molecular dynamics analysis concluded that the target of antimicrobial peptide Bactenecin is MurB of A. baumannii, and identified other molecular targets of selected AMPs. Additionally, the oligomerization capacity of the selected AMPs was also investigated, and it was shown that the selected AMPs form oligomeric states, and interact with their molecular targets in that state. Experimental validation using purified AMPs and molecular targets needs to be done to confirm the interaction.Communicated by Ramaswamy H. Sarma.

Structural determinants of odorant-binding proteins affecting their ability to form amyloid fibrils

The formation of amyloid fibrils is associated with many severe pathologies as well as the execution of essential physiological functions by proteins. Despite the diversity, all amyloids share a similar morphology and consist of stacked β-strands, suggesting high amyloidogenicity of native proteins enriched with β-structure. Such proteins include those with a β-barrel-like structure with β-strands arranged into a cylindrical β-sheet. However, the mechanisms responsible for destabilization of the native state and triggering fibrillogenesis have not thoroughly explored yet. Here we analyze the structural determinants of fibrillogenesis in proteins with β-barrel structures on the example of odorant-binding protein (OBP), whose amyloidogenicity was recently demonstrated in vitro. We reveal a crucial role in the fibrillogenesis of OBPs for the "open" conformation of the molecule. This conformation is achieved by disrupting the interaction between the β-barrel and the C-terminus of protein monomers or dimers, which exposes "sticky" amyloidogenic sites for interaction. The data suggest that the "open" conformation of OBPs can be induced by destabilizing the native β-barrel structure through the disruption of: 1) intramolecular disulfide cross-linking and non-covalent contacts between the C-terminal fragment and β-barrel in the protein's monomeric form, or 2) intermolecular contacts involved in domain swapping in the protein's dimeric form.

Natural compound plumbagin based inhibition of hIAPP revealed by Markov state models based on MD data along with experimental validations

Human islet amyloid polypeptide (amylin or hIAPP) is a 37 residue hormone co-secreted with insulin from β cells of the pancreas. In patients suffering from type-2 diabetes, amylin self-assembles into amyloid fibrils, ultimately leading to the death of the pancreatic cells. However, a research gap exists in preventing and treating such amyloidosis. Plumbagin, a natural compound, has previously been demonstrated to have inhibitory potential against insulin amyloidosis. Our investigation unveils collapsible regions within hIAPP that, upon collapse, facilitates hydrophobic and pi-pi interactions, ultimately leading to aggregation. Intriguingly plumbagin exhibits the ability to bind these specific collapsible regions, thereby impeding the aforementioned interactions that would otherwise drive hIAPP aggregation. We have used atomistic molecular dynamics approach to determine secondary structural changes. MSM shows metastable states forming native like hIAPP structure in presence of PGN. Our in silico results concur with in vitro results. The ThT assay revealed a striking 50% decrease in fluorescence intensity at a 1:1 ratio of hIAPP to Plumbagin. This finding suggests a significant inhibition of amyloid fibril formation by plumbagin, as ThT fluorescence directly correlates with the presence of these fibrils. Further TEM images revealed disappearance of hIAPP fibrils in plumbagin pre-treated hIAPP samples. Also, we have shown that plumbagin disrupts the intermolecular hydrogen bonding in hIAPP fibrils leading to an increase in the average beta strand spacing, thereby causing disaggregation of pre-formed fibrils demonstrating overall disruption of the aggregation machinery of hIAPP. Our work is the first to report a detailed atomistic simulation of 22 μs for hIAPP. Overall, our studies put plumbagin as a potential candidate for both preventive and therapeutic candidate for hIAPP amyloidosis.

Influenza A virus propagation requires the activation of the unfolded protein response and the accumulation of insoluble protein aggregates

Influenza A virus (IAV) employs multiple strategies to manipulate cellular mechanisms and support proper virion formation and propagation. In this study, we performed a detailed analysis of the interplay between IAV and the host cells' proteostasis throughout the entire infectious cycle. We reveal that IAV infection activates the inositol requiring enzyme 1 (IRE1) branch of the unfolded protein response, and that this activation is important for an efficient infection. We further observed the accumulation of virus-induced insoluble protein aggregates, containing both viral and host proteins, associated with a dysregulation of the host cell RNA metabolism. Our data indicate that this accumulation is important for IAV propagation and favors the final steps of the infection cycle, more specifically the virion assembly. These findings reveal additional mechanisms by which IAV disrupts host proteostasis and uncovers new cellular targets that can be explored for the development of host-directed antiviral strategies.

Essential factors, advanced strategies, challenges, and approaches involved for efficient expression of recombinant proteins in Escherichia coli

Producing recombinant proteins is a major accomplishment of biotechnology in the past century. Heterologous hosts, either eukaryotic or prokaryotic, are used for the production of these proteins. The utilization of microbial host systems continues to dominate as the most efficient and affordable method for biotherapeutics and food industry productions. Hence, it is crucial to analyze the limitations and advantages of microbial hosts to enhance the efficient production of recombinant proteins on a large scale. E. coli is widely used as a host for the production of recombinant proteins. Researchers have identified certain obstacles with this host, and given the growing demand for recombinant protein production, there is an immediate requirement to enhance this host. The following review discusses the elements contributing to the manifestation of recombinant protein. Subsequently, it sheds light on innovative approaches aimed at improving the expression of recombinant protein. Lastly, it delves into the obstacles and optimization methods associated with translation, mentioning both cis-optimization and trans-optimization, producing soluble recombinant protein, and engineering the metal ion transportation. In this context, a comprehensive description of the distinct features will be provided, and this knowledge could potentially enhance the expression of recombinant proteins in E. coli.

A sequence-based model for identifying proteins undergoing liquid-liquid phase separation/forming fibril aggregates via machine learning

Liquid-liquid phase separation (LLPS) and the solid aggregate (also referred to as amyloid aggregates) formation of proteins, have gained significant attention in recent years due to their associations with various physiological and pathological processes in living organisms. The systematic investigation of the differences and connections between proteins undergoing LLPS and those forming amyloid fibrils at the sequence level has not yet been explored. In this research, we aim to address this gap by comparing the two types of proteins across 36 features using collected data available currently. The statistical comparison results indicate that, 24 of the selected 36 features exhibit significant difference between the two protein groups. A LLPS-Fibrils binary classification model built on these 24 features using random forest reveals that the fraction of intrinsically disordered residues (FIDR ) is identified as the most crucial feature. While, in the further three-class LLPS-Fibrils-Background classification model built on the same screened features, the composition of cysteine and that of leucine show more significant contributions than others. Through feature ablation analysis, we finally constructed a model FLFB (Feature-based LLPS-Fibrils-Background protein predictor) using six refined features, with an average area under the receiver operating characteristics of 0.83. This work indicates using sequence features and a machine learning model, proteins undergoing LLPS or forming amyloid fibrils can be identified.

Computational Screening for mAb Colloidal Stability with Coarse-Grained, Molecular-Scale Simulations

Monoclonal antibodies (mAbs) are an important modality of protein therapeutics with broad applications for numerous diseases. However, colloidal instabilities occurring at high protein concentrations can limit the ability to develop stable, high-concentration liquid dosage forms that are required for patient-centric, device-mediated products. Therefore, it is advantageous to identify colloidally stable mAbs early in the discovery process to ensure that they are selected for development. Experimental screening for colloidal stability can be time- and resource-consuming and is most feasible at the later stages of drug development due to material requirements. Alternatively, computational approaches have emerging potential to provide efficient screening and focus developmental efforts on mAbs with the greatest developability potential, while providing mechanistic relationships for colloidal instability. In this work, coarse-grained, molecular-scale models were fine-tuned to screen for colloidal stability at amino-acid resolution. This model parameterization provides a framework to screen for mAb self-interactions and extrapolate to bulk solution behavior. This approach was applied to a wide array of mAbs under multiple buffer conditions, demonstrating the utility of the presented computational approach to augment early candidate screening and later formulation strategies for protein therapeutics.

Structural studies of catalytic peptides using molecular dynamics simulations

Many self-assembling peptides can form amyloid like structures with different sizes and morphologies. Driven by non-covalent interactions, their aggregation can occur through distinct pathways. Additionally, they can bind metal ions to create enzyme like active sites that allow them to catalyze diverse reactions. Due to the non-crystalline nature of amyloids, it is quite challenging to elucidate their structures using experimental spectroscopic techniques. In this aspect, molecular dynamics (MD) simulations provide a useful tool to derive structures of these macromolecules in solution. They can be further validated by comparing with experimentally measured structural parameters. However, these simulations require a multi-step process starting from the selection of the initial structure to the analysis of MD trajectories. There are multiple force fields, parametrization protocols, equilibration processes, software and analysis tools available for this process. Therefore, it is complicated for non-experts to select the most relevant tools and perform these simulations effectively. In this chapter, a systematic methodology that covers all major aspects of modeling of catalytic peptides is provided in a user-friendly manner. It will be helpful for researchers in this critical area of research.

Four classic "de novo" genes all have plausible homologs and likely evolved from retro-duplicated or pseudogenic sequences

Despite being previously regarded as extremely unlikely, the idea that entirely novel protein-coding genes can emerge from non-coding sequences has gradually become accepted over the past two decades. Examples of "de novo origination", resulting in lineage-specific "orphan" genes, lacking coding orthologs, are now produced every year. However, many are likely cases of duplicates that are difficult to recognize. Here, I re-examine the claims and show that four very well-known examples of genes alleged to have emerged completely "from scratch"- FLJ33706 in humans, Goddard in fruit flies, BSC4 in baker's yeast and AFGP2 in codfish-may have plausible evolutionary ancestors in pre-existing genes. The first two are likely highly diverged retrogenes coding for regulatory proteins that have been misidentified as orphans. The antifreeze glycoprotein, moreover, may not have evolved from repetitive non-genic sequences but, as in several other related cases, from an apolipoprotein that could have become pseudogenized before later being reactivated. These findings detract from various claims made about de novo gene birth and show there has been a tendency not to invest the necessary effort in searching for homologs outside of a very limited syntenic or phylostratigraphic methodology. A robust approach is used for improving detection that draws upon similarities, not just in terms of statistical sequence analysis, but also relating to biochemistry and function, to obviate notable failures to identify homologs.

The blobulator: a webtool for identification and visual exploration of hydrophobic modularity in protein sequences

Motivation

Clusters of hydrophobic residues are known to promote structured protein stability and drive protein aggregation. Recent work has shown that identifying contiguous hydrophobic residue clusters (termed "blobs") has proven useful in both intrinsically disordered protein (IDP) simulation and human genome studies. However, a graphical interface was unavailable.

Results

Here, we present the blobulator: an interactive and intuitive web interface to detect intrinsic modularity in any protein sequence based on hydrophobicity. We demonstrate three use cases of the blobulator and show how identifying blobs with biologically relevant parameters provides useful information about a globular protein, two orthologous membrane proteins, and an IDP. Other potential applications are discussed, including: predicting protein segments with critical roles in tertiary interactions, providing a definition of local order and disorder with clear edges, and aiding in predicting protein features from sequence.

Availability

The blobulator GUI can be found at www.blobulator.branniganlab.org, and the source code with pip installable command line tool can be found on GitHub at www.GitHub.com/BranniganLab/blobulator.

Cryo-EM observation of the amyloid key structure of polymorphic TDP-43 amyloid fibrils

The transactive response DNA-binding protein-43 (TDP-43) is a multi-facet protein involved in phase separation, RNA-binding, and alternative splicing. In the context of neurodegenerative diseases, abnormal aggregation of TDP-43 has been linked to amyotrophic lateral sclerosis and frontotemporal lobar degeneration through the aggregation of its C-terminal domain. Here, we report a cryo-electron microscopy (cryo-EM)-based structural characterization of TDP-43 fibrils obtained from the full-length protein. We find that the fibrils are polymorphic and contain three different amyloid structures. The structures differ in the number and relative orientation of the protofilaments, although they share a similar fold containing an amyloid key motif. The observed fibril structures differ from previously described conformations of TDP-43 fibrils and help to better understand the structural landscape of the amyloid fibril structures derived from this protein.

AmyloComp: A Bioinformatic Tool for Prediction of Amyloid Co-aggregation

Typically, amyloid fibrils consist of multiple copies of the same protein. In these fibrils, each polypeptide chain adopts the same β-arc-containing conformation and these chains are stacked in a parallel and in-register manner. In the last few years, however, a considerable body of data has been accumulated about co-aggregation of different amyloid-forming proteins. Among known examples of the co-aggregation are heteroaggregates of different yeast prions and human proteins Rip1 and Rip3. Since the co-aggregation is linked to such important phenomena as infectivity of amyloids and molecular mechanisms of functional amyloids, we analyzed its structural aspects in more details. An axial stacking of different proteins within the same amyloid fibril is one of the most common type of co-aggregation. By using an approach based on structural similarity of the growing tips of amyloids, we developed a computational method to predict amyloidogenic β-arch structures that are able to interact with each other by the axial stacking. Furthermore, we compiled a dataset consisting of 26 experimentally known pairs of proteins capable or incapable to co-aggregate. We utilized this dataset to test and refine our algorithm. The developed method opens a way for a number of applications, including the identification of microbial proteins capable triggering amyloidosis in humans. AmyloComp is available on the website: https://bioinfo.crbm.cnrs.fr/index.php?route=tools&tool=30.

Formation of amyloid fibrils by the regulatory 14-3-3ζ protein

The 14-3-3 proteins are a highly conserved adaptor protein family with multi-layer functions, abundantly expressed in the brain. The 14-3-3 proteins modulate phosphorylation, regulate enzymatic activity and can act as chaperones. Most importantly, they play an important role in various neurodegenerative disorders due to their vast interaction partners. Particularly, the 14-3-3ζ isoform is known to co-localize in aggregation tangles in both Alzheimer's and Parkinson's diseases as a result of protein-protein interactions. These abnormal clumps consist of amyloid fibrils, insoluble aggregates, mainly formed by the amyloid-β, tau and α-synuclein proteins. However, the molecular basis of if and how 14-3-3ζ can aggregate into amyloid fibrils is unknown. In this study, we describe the formation of amyloid fibrils by 14-3-3ζ using a comprehensive approach that combines bioinformatic tools, amyloid-specific dye binding, secondary structure analysis and atomic force microscopy. The results presented herein characterize the amyloidogenic properties of 14-3-3ζ and imply that the well-folded protein undergoes aggregation to β-sheet-rich amyloid fibrils.

PACT - Prediction of amyloid cross-interaction by threading

Amyloid proteins are often associated with the onset of diseases, including Alzheimer's, Parkinson's and many others. However, there is a wide class of functional amyloids that are involved in physiological functions, e.g., formation of microbial biofilms or storage of hormones. Recent studies showed that an amyloid fibril could affect the aggregation of another protein, even from a different species. This may result in amplification or attenuation of the aggregation process. Insight into amyloid cross-interactions may be crucial for better understanding of amyloid diseases and the potential influence of microbial amyloids on human proteins. However, due to the demanding nature of the needed experiments, knowledge of such interactions is still limited. Here, we present PACT (Prediction of Amyloid Cross-interaction by Threading) - the computational method for the prediction of amyloid cross-interactions. The method is based on modeling of a heterogeneous fibril formed by two amyloidogenic peptides. The resulting structure is assessed by the structural statistical potential that approximates its plausibility and energetic stability. PACT was developed and first evaluated mostly on data collected in the AmyloGraph database of interacting amyloids and achieved high values of Area Under ROC (AUC=0.88) and F1 (0.82). Then, we applied our method to study the interactions of CsgA - a bacterial biofilm protein that was not used in our in-reference datasets, which is expressed in several bacterial species that inhabit the human intestines - with two human proteins. The study included alpha-synuclein, a human protein that is involved in Parkinson's disease, and human islet amyloid polypeptide (hIAPP), which is involved in type 2 diabetes. In both cases, PACT predicted the appearance of cross-interactions. Importantly, the method indicated specific regions of the proteins, which were shown to play a central role in both interactions. We experimentally confirmed the novel results of the indicated CsgA fragments interacting with hIAPP based on the kinetic characteristics obtained with the ThT assay. PACT opens the possibility of high-throughput studies of amyloid interactions. Importantly, it can work with fairly long protein fragments, and as a purely physicochemical approach, it relies very little on scarce training data. The tool is available as a web server at https://pact.e-science.pl/pact/ . The local version can be downloaded from https://github.com/KubaWojciechowski/PACT .

Stabilization challenges and aggregation in protein-based therapeutics in the pharmaceutical industry

Protein-based therapeutics have revolutionized the pharmaceutical industry and become vital components in the development of future therapeutics. They offer several advantages over traditional small molecule drugs, including high affinity, potency and specificity, while demonstrating low toxicity and minimal adverse effects. However, the development and manufacturing processes of protein-based therapeutics presents challenges related to protein folding, purification, stability and immunogenicity that should be addressed. These proteins, like other biological molecules, are prone to chemical and physical instabilities. The stability of protein-based drugs throughout the entire manufacturing, storage and delivery process is essential. The occurrence of structural instability resulting from misfolding, unfolding, and modifications, as well as aggregation, poses a significant risk to the efficacy of these drugs, overshadowing their promising attributes. Gaining insight into structural alterations caused by aggregation and their impact on immunogenicity is vital for the advancement and refinement of protein therapeutics. Hence, in this review, we have discussed some features of protein aggregation during production, formulation and storage as well as stabilization strategies in protein engineering and computational methods to prevent aggregation.

Biophysical evolution of the receptor-binding domains of SARS-CoVs

With hundreds of coronaviruses (CoVs) identified in bats that can infect humans, it is essential to understand how CoVs that affected the human population have evolved. Seven known CoVs have infected humans, of which three CoVs caused severe disease with high mortalities: severe acute respiratory syndrome (SARS)-CoV emerged in 2002, Middle East respiratory syndrome-CoV in 2012, and SARS-CoV-2 in 2019. SARS-CoV and SARS-CoV-2 belong to the same family, follow the same receptor pathway, and use their receptor-binding domain (RBD) of spike protein to bind to the angiotensin-converting enzyme 2 (ACE2) receptor on the human epithelial cell surface. The sequence of the two RBDs is divergent, especially in the receptor-binding motif that directly interacts with ACE2. We probed the biophysical differences between the two RBDs in terms of their structure, stability, aggregation, and function. Since RBD is being explored as an antigen in protein subunit vaccines against CoVs, determining these biophysical properties will also aid in developing stable protein subunit vaccines. Our results show that, despite RBDs having a similar three-dimensional structure, they differ in their thermodynamic stability. RBD of SARS-CoV-2 is significantly less stable than that of SARS-CoV. Correspondingly, SARS-CoV-2 RBD shows a higher aggregation propensity. Regarding binding to ACE2, less stable SARS-CoV-2 RBD binds with a higher affinity than more stable SARS-CoV RBD. In addition, SARS-CoV-2 RBD is more homogenous in terms of its binding stoichiometry toward ACE2 compared to SARS-CoV RBD. These results indicate that SARS-CoV-2 RBD differs from SARS-CoV RBD in terms of its stability, aggregation, and function, possibly originating from the diverse receptor-binding motifs. Higher aggregation propensity and decreased stability of SARS-CoV-2 RBD warrant further optimization of protein subunit vaccines that use RBD as an antigen by inserting stabilizing mutations or formulation screening.

Butyrylcholinesterase signal sequence self-aggregates and enhances amyloid fibril formation in vitro

Alzheimer's disease (AD) pathogenesis has been attributed to extracellular aggregates of amyloid β (Aβ) plaques and neurofibrillary tangles in the human brain. It has been reported that butyrylcholinesterase (BChE) also accumulates in the brain Aβ plaques in AD. We have previously found that the BChE substitution in 5'UTR caused an in-frame N-terminal extension of 41 amino acids of the BChE signal peptide. The resultant variant with a 69 amino acid signal peptide, designated N-BChE, could play a role in AD development. Here, we report that the signal sequence of the BChE, if produced in an extended 69 aa version, can self-aggregate and could form seeds that enhance amyloid fibril formation in vitro in a dose-dependent manner and create larger co-aggregates. Similar phenomena could have been observed in the human brain if such an extended form of the signal sequence had been, in some circumstances, translated.

Optimized peptide nanofibrils as efficient transduction enhancers for in vitro and ex vivo gene transfer

Chimeric antigen receptor (CAR)-T cell therapy is a groundbreaking immunotherapy for cancer. However, the intricate and costly manufacturing process remains a hurdle. Improving the transduction rate is a potential avenue to cut down costs and boost therapeutic efficiency. Peptide nanofibrils (PNFs) serve as one such class of transduction enhancers. PNFs bind to negatively charged virions, facilitating their active engagement by cellular protrusions, which enhances virion attachment to cells, leading to increased cellular entry and gene transfer rates. While first-generation PNFs had issues with aggregate formation and potential immunogenicity, our study utilized in silico screening to identify short, endogenous, and non-immunogenic peptides capable of enhancing transduction. This led to the discovery of an 8-mer peptide, RM-8, which forms PNFs that effectively boost T cell transduction rates by various retroviral vectors. A subsequent structure-activity relationship (SAR) analysis refined RM-8, resulting in the D4 derivative. D4 peptide is stable and assembles into smaller PNFs, avoiding large aggregate formation, and demonstrates superior transduction rates in primary T and NK cells. In essence, D4 PNFs present an economical and straightforward nanotechnological tool, ideal for refining ex vivo gene transfer in CAR-T cell production and potentially other advanced therapeutic applications.

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm

Various diseases, including Huntington's disease, Alzheimer's disease, and Parkinson's disease, have been reported to be linked to amyloid. Therefore, it is crucial to distinguish amyloid from non-amyloid proteins or peptides. While experimental approaches are typically preferred, they are costly and time-consuming. In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector machine for identifying amyloidgenic peptides. Experimental results demonstrate that our proposed method significantly improves the identification of amyloidgenic peptides compared to existing predictors. This suggests that our method may serve as a powerful tool in identifying amyloidgenic peptides. To facilitate academic use, the dataset and codes used in the current study are accessible at https://figshare.com/articles/online_resource/iAMY-RECMFF/22816916.

ATP-independent substrate recruitment to proteasomal degradation in mycobacteria

Mycobacteria and other actinobacteria possess proteasomal degradation pathways in addition to the common bacterial compartmentalizing protease systems. Proteasomal degradation plays a crucial role in the survival of these bacteria in adverse environments. The mycobacterial proteasome interacts with several ring-shaped activators, including the bacterial proteasome activator (Bpa), which enables energy-independent degradation of heat shock repressor HspR. However, the mechanism of substrate selection and processing by the Bpa-proteasome complex remains unclear. In this study, we present evidence that disorder in substrates is required but not sufficient for recruitment to Bpa-mediated proteasomal degradation. We demonstrate that Bpa binds to the folded N-terminal helix-turn-helix domain of HspR, whereas the unstructured C-terminal tail of the substrate acts as a sequence-specific threading handle to promote efficient proteasomal degradation. In addition, we establish that the heat shock chaperone DnaK, which interacts with and co-regulates HspR, stabilizes HspR against Bpa-mediated proteasomal degradation. By phenotypical characterization of Mycobacterium smegmatis parent and bpa deletion mutant strains, we show that Bpa-dependent proteasomal degradation supports the survival of the bacterium under stress conditions by degrading HspR that regulates vital chaperones.

Prediction of protein aggregation propensity employing SqFt-based logistic regression model

Here we present a novel machine-learning approach to predict protein aggregation propensity (PAP) which is a key factor in the formation of amyloid fibrils based on logistic regression (LR). Amyloid fibrils are associated with various neurodegenerative diseases (ND) such as Alzheimer's disease (AD) and Parkinson's disease (PD), which are caused by oxidative stress and impaired protein homeostasis. Accordingly, the paper uses a dataset of hexapeptides with known aggregation tendencies and eight physiochemical features to train and test the LR model. Also, it evaluates the performance of the LR model using F-measure and Matthews correlation coefficient (MCC) as metrics and compares it with other existing methods. Moreover, it investigates the effect of combining sequence and feature information in the prediction. In conclusion, the LR model with sequence and feature information achieves high F-measure (0.841) and MCC (0.6692), outperforming other methods and demonstrating its efficiency and reliability for PAP prediction. In addition, the overall performance of the concluded method was higher than the other known servers, for instance, Aggrescan, Metamyl, Foldamyloid, and PASTA 2.0. The LR model can be accessed at: https://github.com/KatherineEshari/Protein-aggregation-prediction.

Nanoscopic Elucidation of Spontaneous Self-Assembly of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Open Reading Frame 6 (ORF6) Protein

Open reading frame 6 (ORF6), the accessory protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that suppresses host type-I interferon signaling, possesses amyloidogenic sequences. ORF6 amyloidogenic peptides self-assemble to produce cytotoxic amyloid fibrils. Currently, the molecular properties of the ORF6 remain elusive. Here, we investigate the structural dynamics of the full-length ORF6 protein in a near-physiological environment using high-speed atomic force microscopy. ORF6 oligomers were ellipsoidal and readily assembled into ORF6 protofilaments in either a circular or a linear pattern. The formation of ORF6 protofilaments was enhanced at higher temperatures or on a lipid substrate. ORF6 filaments were sensitive to aliphatic alcohols, urea, and SDS, indicating that the filaments were predominantly maintained by hydrophobic interactions. In summary, ORF6 self-assembly could be necessary to sequester host factors and causes collateral damage to cells via amyloid aggregates. Nanoscopic imaging unveiled the innate molecular behavior of ORF6 and provides insight into drug repurposing to treat amyloid-related coronavirus disease 2019 complications.

AggBERT: Best in Class Prediction of Hexapeptide Amyloidogenesis with a Semi-Supervised ProtBERT Model

The prediction of peptide amyloidogenesis is a challenging problem in the field of protein folding. Large language models, such as the ProtBERT model, have recently emerged as powerful tools in analyzing protein sequences for applications, such as predicting protein structure and function. In this article, we describe the use of a semisupervised and fine-tuned ProtBERT model to predict peptide amyloidogenesis from sequences alone. Our approach, which we call AggBERT, achieved state-of-the-art performance, demonstrating the potential for large language models to improve the accuracy and speed of amyloid fibril prediction over simple heuristics or structure-based approaches. This work highlights the transformative potential of machine learning and large language models in the fields of chemical biology and biomedicine.