AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides

Building Up Functional Coiled-Coil-Based Supramolecular Assemblies for Biomedical and Biotechnological Applications

The self-assembling nature of coiled-coils has brought this common structural motif into the spotlight of protein design since it offers a customizable framework for engineering innovative protein nanoparticles with tailored functionalities. We recently harnessed the self-assembling capabilities of ZapB, a bacterial coiled-coil protein, to build up fluorescent protein nanoparticles possessing remarkable affinity for antibodies. Here, we describe a complete workflow detailing the design, production, and characterization of such coiled-coil-based protein nanostructures. Additionally, we detail their functionalization with specific antibodies and illustrate their utility in stimulating the activation and proliferation of human T cells, underscoring the potential of these protein-only nanoparticles in immunotherapeutic interventions.

iAmyP: A Multi-view Learning for Amyloidogenic Hexapeptides Identification Based on Sequence Least Squares Programming

The development of peptide drug is hindered by the risk of amyloidogenic aggregation; if peptides tend to aggregate in this manner, they may be unsuitable for drug design. Computational methods aimed at predicting amyloidogenic sequences often face challenges in extracting high-quality features, and their predictive performance can be enchanced. To surmount these challenges, iAmyP was introduced as a specialized computational tool designed for predicting amyloidogenic hexapeptides. Utilizing multi-view learning, iAmyP incorporated sequence, structural, and evolutionary features, performing feature selection and feature fusion through recursive feature elimination and attention mechanisms. This amalgamation of features and subsequent feature selection and fusion lead to optimal performance facilitated by an optimization algorithm based on sequence least squares programming. Notably, iAmyP exhibited robust generalization for peptides with lengths of 7-10 amino acids. The role of hydrophobic amino acids in the aggregation process is critical, and a thorough analysis have significantly enhanced our insight into their significance in amyloidogenic hexapeptides. This tool represented an advancement in the development of peptide therapeutics by providing an understanding of amyloidogenic aggregation, establishing itself as a valuable framework for assessing amyloidogenic sequences. The data and code can be freely accessed at https://github.com/xialab-ahu/iAmyP .

The Hsc70 system maintains the synaptic SNARE protein SNAP-25 in an assembly-competent state and delays its aggregation

The complex mechanism of synaptic vesicle fusion with the plasma membrane for neurotransmitter release is initiated by the formation of the SNARE complex at the presynaptic terminal of the neuron. The SNARE complex is composed of four helices contributed by three proteins: one from syntaxin (localized at the plasma membrane), one from synaptobrevin (localized at the synaptic vesicle), and two from the intrinsically disordered and aggregation-prone SNAP-25, which is localized to the plasma membrane by virtue of palmitoylation of cysteine residues. The fusion process is tightly regulated and requires the constitutively expressed Hsp70 chaperone (Hsc70) and its J-protein co-chaperone CSPα. We hypothesize that Hsc70 and CSPα cooperate to chaperone SNAP-25, disfavoring its aggregation and keeping it in a folding state competent for SNARE complex formation. To test this hypothesis, we employed a bottom-up approach and studied the interaction between Hsc70 and CSPα with SNAP-25 in vitro. We showed that the aggregation of SNAP-25 is delayed in the presence of Hsc70 and CSPα. Using a peptide array that spans the sequence of SNAP-25, we identified three potential Hsc70-interacting sequences and designed peptides containing these sequences to test binding in solution. We characterized the interaction of SNAP-25-derived peptides with Hsc70 and CSPα using a combination of biochemical and biophysical techniques, including native-PAGE, binding affinity by fluorescence anisotropy, ATPase-activity of Hsc70, and NMR. We have identified an Hsc70 binding site within SNAP-25 that is likely to represent the site used in the cell to facilitate SNARE complex formation.

Ab-amy 2.0: Predicting light chain amyloidogenic risk of therapeutic antibodies based on antibody language model

Therapeutic antibodies have emerged as a promising treatment option for a wide range of diseases. However, the light chain of antibodies can potentially induce amyloidosis, a condition characterized by protein misfolding and aggregation, posing a significant safety concern. Therefore, it is crucial to assess the amyloidogenic risk of therapeutic antibodies during the early stages of drug development. In this study, we introduce AB-Amy 2.0, a new computational model with enhanced performance for assessing the light chain amyloidogenic risk of therapeutic antibodies. By employing pretrained protein language models (PLMs) embeddings, AB-Amy 2.0 achieves higher accuracy in amyloidogenic risk prediction compared with traditional features offering a crucial tool for early-stage identification of antibodies with low aggregation propensity. The AB-Amy 2.0 was trained on antiBERTy embeddings and utilizes the SVM algorithm, resulting in superior performance metrics. On an independent test dataset, the model achieved high sensitivity, specificity, ACC, MCC and AUC of 93.47%, 89.23%, 91.92%, 0.8261 and 0.9739, respectively. These results highlight the effectiveness and robustness of AB-Amy 2.0 in predicting light chain amyloidogenic risk accurately. To facilitate user-friendly access, we have developed an online web server (http://i.uestc.edu.cn/AB-Amy2) and a command line tool (https://github.com/zzyywww/ABAmy2). These resources enable the broader application of this advanced model and promise to enhance the development of safer therapeutic antibodies.

Cryo-EM structure of a lysozyme-derived amyloid fibril from hereditary amyloidosis

Systemic ALys amyloidosis is a debilitating protein misfolding disease that arises from the formation of amyloid fibrils from C-type lysozyme. We here present a 2.8 Å cryo-electron microscopy structure of an amyloid fibril, which was isolated from the abdominal fat tissue of a patient who expressed the D87G variant of human lysozyme. We find that the fibril possesses a stable core that is formed by all 130 residues of the fibril precursor protein. There are four disulfide bonds in each fibril protein that connect the same residues as in the globularly folded protein. As the conformation of lysozyme in the fibril is otherwise fundamentally different from native lysozyme, our data provide a structural rationale for the need of protein unfolding in the development of systemic ALys amyloidosis.

Predictive Model Building for Aggregation Kinetics Based on Molecular Dynamics Simulations of an Antibody Fragment

Computational methods including machine learning and molecular dynamics simulations have strong potential to characterize, understand, and ultimately predict the properties of proteins relevant to their stability and function as therapeutics. Such methods would streamline the development pathway by minimizing the current experimental testing required for many protein variants and formulations. The molecular understanding of thermostability and aggregation propensity has advanced significantly along with predictive algorithms based on the sequence-level or structural-level information on a protein. However, these approaches focus largely on a comparison of protein sequence variations to correlate the properties of proteins to their stability, solubility, and aggregation propensity. For therapeutic protein development, it is of equal importance to take into account the impact of the formulation conditions to elucidate and predict the stability of the antibody drugs. At the macroscopic level, changing temperature, pH, ionic strength, and the addition of excipients can significantly alter the kinetics of protein aggregation. The mechanisms controlling aggregation kinetics have been traced back to a combination of molecular features, including conformational stability, partial unfolding to aggregation-prone states, and the colloidal stability governed by surface charges and hydrophobicity. However, very little has been done to evaluate these features in the context of protein dynamics in different formulations. In this work, we have combined a range of molecular features calculated from the Fab A33 protein sequence and molecular dynamics simulations. Using the power of advanced, yet interpretable, statistical tools, it has been possible to uncover greater insights into the mechanisms behind protein stability, validating previous findings, and also develop models that can predict the aggregation kinetics within a range of 49 different solution conditions.

Molecular Dynamics Simulations Reveal How Competing Protein-Surface Interactions for Glycine, Citrate, and Water Modulate Stability in Antibody Fragment Formulations

The design of stable formulations remains a major challenge for protein therapeutics, particularly the need to minimize aggregation. Experimental formulation screens are typically based on thermal transition midpoints (Tm), and forced degradation studies at elevated temperatures. Both approaches give limited predictions of long-term storage stability, particularly at low temperatures. Better understanding of the mechanisms of action for formulation of excipients and buffers could lead to improved strategies for formulation design. Here, we identified a complex impact of glycine concentration on the experimentally determined stability of an antibody Fab fragment and then used molecular dynamics simulations to reveal mechanisms that underpin these complex behaviors. Tm values increased monotonically with glycine concentration, but associated ΔSvh measurements revealed more complex changes in the native ensemble dynamics, which reached a maximum at 30 mg/mL. The aggregation kinetics at 65 °C were similar at 0 and 20 mg/mL glycine, but then significantly slower at 50 mg/mL. These complex behaviors indicated changes in the dominant stabilizing mechanisms as the glycine concentration was increased. MD revealed a complex balance of glycine self-interaction, and differentially preferred interactions of glycine with the Fab as it displaced hydration-shell water, and surface-bound water and citrate buffer molecules. As a result, glycine binding to the Fab surface had different effects at different concentrations, and led from preferential interactions at low concentrations to preferential exclusion at higher concentrations. During preferential interaction, glycine displaced water from the Fab hydration shell, and a small number of water and citrate molecules from the Fab surface, which reduced the protein dynamics as measured by root-mean-square fluctuation (RMSF) on the short time scales of MD. By contrast, the native ensemble dynamics increased according to ΔSvh, suggesting increased conformational changes on longer time scales. The aggregation kinetics did not change at low glycine concentrations, and so the opposing dynamics effects either canceled out or were not directly relevant to aggregation. During preferential exclusion at higher glycine concentrations, glycine could only bind to the Fab surface through the displacement of citrate buffer molecules already favorably bound on the Fab surface. Displacement of citrate increased the flexibility (RMSF) of the Fab, as glycine formed fewer bridging hydrogen bonds to the Fab surface. Overall, the slowing of aggregation kinetics coincided with reduced flexibility in the Fab ensemble at the very highest glycine concentrations, as determined by both RMSF and ΔSvh, and occurred at a point where glycine binding displaced neither water nor citrate. These final interactions with the Fab surface were driven by mass action and were the least favorable, leading to a macromolecular crowding effect under the regime of preferential exclusion that stabilized the dynamics of Fab.

A human-specific cytotoxic neopeptide generated by the deafness gene Cingulin

Accumulation of mutant proteins in cells can induce proteinopathies and cause functional damage to organs. Recently, the Cingulin (CGN) protein has been shown to maintain the morphology of cuticular plates of inner ear hair cells and a frameshift mutation in CGN causes autosomal dominant non-syndromic hearing loss. Here, we find that the mutant CGN proteins form insoluble aggregates which accumulate intracellularly and lead to cell death. Expression of the mutant CGN in the inner ear results in severe hair cell death and hearing loss in mice, resembling the auditory phenotype in human patients. Interestingly, a human-specific residue (V1112) in the neopeptide generated by the frameshift mutation is critical for the aggregation and cytotoxicity of the mutant human CGN. Moreover, the expression of heat shock factor 1 (HSF1) decreases the accumulation of insoluble mutant CGN aggregates and rescues cell death. In summary, these findings identify mutant-specific toxic polypeptides as a disease-causing mechanism of the deafness mutation in CGN, which can be targeted by the expression of the cell chaperone response regulator HSF1.

Interferon lambda 4 is a gut antimicrobial protein

To withstand complex microbial challenges, the mammalian gut largely depends on the secretion of diverse antimicrobial proteins. Type III interferons (IFNλs) are ordinarily considered inducible antiviral cytokines involved in intestinal immunity. Unlike other IFNλs, we found that newly identified IFNλ4 is an intestinal antibacterial protein. Large amounts of natural IFNλ4 are present in the secretory layer of the intestinal tracts of healthy piglets, which suggests that IFNλ4 is in direct physiological contact with microbial pathogens. We also identified two biochemical functions of mammalian IFNλ4, the induction of bacterial agglutination and direct microbial killing, which are not functions of the other IFNλs. Further mechanistic investigations revealed that after binding to the carbohydrate fraction of lipopolysaccharide, mammalian IFNλ4 self-assembles into bacteria-surrounding nanoparticles that agglutinate bacteria, and that its unique cationic amphiphilic molecular structure facilitates the destruction of bacterial membranes. Our data reveal features of IFNλ4 distinct from those of previously reported IFNλs and suggest that noncanonical IFNλ4 is deeply involved in intestinal immunity, beyond simply cytokine signaling.

Click, Compute, Create: A Review of Web-based Tools for Enzyme Engineering

Enzyme engineering, though pivotal across various biotechnological domains, is often plagued by its time-consuming and labor-intensive nature. This review aims to offer an overview of supportive in silico methodologies for this demanding endeavor. Starting from methods to predict protein structures, to classification of their activity and even the discovery of new enzymes we continue with describing tools used to increase thermostability and production yields of selected targets. Subsequently, we discuss computational methods to modulate both, the activity as well as selectivity of enzymes. Last, we present recent approaches based on cutting-edge machine learning methods to redesign enzymes. With exception of the last chapter, there is a strong focus on methods easily accessible via web-interfaces or simple Python-scripts, therefore readily useable for a diverse and broad community.

Proteomic Evidence for Amyloidogenic Cross-Seeding in Fibrinaloid Microclots

In classical amyloidoses, amyloid fibres form through the nucleation and accretion of protein monomers, with protofibrils and fibrils exhibiting a cross-β motif of parallel or antiparallel β-sheets oriented perpendicular to the fibre direction. These protofibrils and fibrils can intertwine to form mature amyloid fibres. Similar phenomena can occur in blood from individuals with circulating inflammatory molecules (and also some originating from viruses and bacteria). Such pathological clotting can result in an anomalous amyloid form termed fibrinaloid microclots. Previous proteomic analyses of these microclots have shown the presence of non-fibrin(ogen) proteins, suggesting a more complex mechanism than simple entrapment. We thus provide evidence against such a simple entrapment model, noting that clot pores are too large and centrifugation would have removed weakly bound proteins. Instead, we explore whether co-aggregation into amyloid fibres may involve axial (multiple proteins within the same fibril), lateral (single-protein fibrils contributing to a fibre), or both types of integration. Our analysis of proteomic data from fibrinaloid microclots in different diseases shows no significant quantitative overlap with the normal plasma proteome and no correlation between plasma protein abundance and their presence in fibrinaloid microclots. Notably, abundant plasma proteins like α-2-macroglobulin, fibronectin, and transthyretin are absent from microclots, while less abundant proteins such as adiponectin, periostin, and von Willebrand factor are well represented. Using bioinformatic tools, including AmyloGram and AnuPP, we found that proteins entrapped in fibrinaloid microclots exhibit high amyloidogenic tendencies, suggesting their integration as cross-β elements into amyloid structures. This integration likely contributes to the microclots' resistance to proteolysis. Our findings underscore the role of cross-seeding in fibrinaloid microclot formation and highlight the need for further investigation into their structural properties and implications in thrombotic and amyloid diseases. These insights provide a foundation for developing novel diagnostic and therapeutic strategies targeting amyloidogenic cross-seeding in blood clotting disorders.

Intrinsic conformational preference in the monomeric protein governs amyloid polymorphism

The inherent stochasticity associated with the hierarchical self-assembly of either native-like or partially-unfolded protein monomers leads to the formation of transient, morphologically-diverse prefibrillar species resulting in structurally-distinct polymorphic protein aggregates. High-resolution structural characterization of mature aggregates has revealed heterogeneous supramolecular packing of protofibrils within amyloid polymorphs. However, little is known about whether initial monomeric protein conformers engender polymorphism at the onset of aggregation. Here, we show that intrinsic conformational preference in aggregation-competent monomeric ovalbumin, an archetypal serpin, dictates fibrillar polymorphism by modulating aggregation pathways. Using fluorescence, FT-IR, and vibrational Raman spectroscopy coupled with dynamic light scattering and electron microscopy, we demonstrate that conformationally-diverse amyloidogenic monomers, formed via an interplay of electrostatic and hydrophobic interactions before the commencement of aggregation, play a crucial role in promoting amyloid polymorphism. Moreover, the monomeric conformational fingerprints, accrued at the onset of aggregation, persist and propagate during the formation of polymorphic amyloids. Our results delineate essential conformational characteristics of the monomeric protein preceding aggregation, which will have broad implications in the mechanistic understanding of amyloid strain diversity observed in disease-related proteins.

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.

Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity

Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.

Massive experimental quantification of amyloid nucleation allows interpretable deep learning of protein aggregation

Protein aggregation is a pathological hallmark of more than fifty human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experimental datasets. Here we directly address this data shortage by experimentally quantifying the amyloid nucleation of >100,000 protein sequences. This unprecedented dataset reveals the limited performance of existing computational methods and allows us to train CANYA, a convolution-attention hybrid neural network that accurately predicts amyloid nucleation from sequence. We adapt genomic neural network interpretability analyses to reveal CANYA's decision-making process and learned grammar. Our results illustrate the power of massive experimental analysis of random sequence-spaces and provide an interpretable and robust neural network model to predict amyloid nucleation.

Unravelling aggregation propensity of rotavirus A VP6 expressed as E. coli inclusion bodies through in silico prediction

The inner capsid protein of rotavirus, VP6, emerges as a promising candidate for next-generation vaccines against rotaviruses owing to its abundance in virion particles and high conservation. However, the formation of inclusion bodies during prokaryotic VP6 expression poses a significant hurdle to rotavirus research and applications. Here, we employed experimental and computational approaches to investigate inclusion body formation and aggregation-prone regions (APRs). Heterologous recombinant VP6 expression in Escherichia coli BL21(DE3) cells resulted in inclusion body formation, confirmed by transmission electron microscopy revealing amorphous aggregates. Thioflavin T assay demonstrated incubation temperature-dependent aggregation of VP6 inclusion bodies. Computational predictions of APRs in rotavirus A VP6 protein were performed using sequence-based tools (TANGO, AGGRESCAN, Zyggregator, Waltz, FoldAmyloid, ANuPP, Camsol intrinsic) and structure-based tools (SolubiS, CamSol structurally corrected, Aggrescan3D). A total of 24 consensus APRs were identified, with 21 of them being surface-exposed in VP6. All identified APRs display a predominance of hydrophobic amino acids, ranging from 33 to 100%. Computational identification of these APRs corroborates our experimental observation of VP6 inclusion body or aggregate formation. Characterization of VP6's aggregation propensity facilitates understanding of its behaviour during prokaryotic expression and opens avenues for protein engineering of soluble variants, advancing research on rotavirus VP6 in pathology, therapy, and diagnostics.

Computational peptide engineering approach for selection of the new C05 antibody-driven peptide with potency to blocking influenza a virus attachment; from in silico to in vivo

Antiviral drugs are currently used to prevent or treat viral infections like influenza A Virus (IAV). Nonetheless, annual genetic mutations of influenza viruses make them resistant to efficient treatment by current medications. Antiviral peptides have recently attracted researchers' attention and can potentially supplant the current medications. This study aimed to design peptides against IAV propagation. For this purpose, P2 and P3 peptides were computationally designed based on the HCDR3 region of the C05 antibody (a monoclonal antibody that neutralizes influenza HA protein and inhibits the virus attachment). The synthesized peptides were tested against the influenza A virus (A/Puerto Rico/8/34 (H1N1)) in vitro, and the most efficient peptide was selected for in vivo experiments. It was shown that the designed peptide shows much more prophylactic and therapeutic effects against the virus. These findings demonstrated that the designed peptide can control the virus infection without any cytotoxicity effect. Antiviral peptide design is acknowledged as a critical tactic to manage viral infections by preventing viral binding to the host cells.Communicated by Ramaswamy H. Sarma.

De Novo Rational Design of Peptide-Based Protein-Protein Inhibitors (Pep-PPIs) Approach by Mapping the Interaction Motifs of the PP Interface and Physicochemical Filtration: A Case on p25-Cdk5-Mediated Neurodegenerative Diseases

Protein-protein interactions, or PPIs, are a part of every biological activity and have been linked to a number of diseases, including cancer, infectious diseases, and neurological disorders. As such, targeting PPIs is considered a strategic and vital approach in the development of new medications. Nonetheless, the wide and flat contact interface makes it difficult to find small-molecule PP inhibitors. An alternative strategy would be to use the PPI interaction motifs as building blocks for the design of peptide-based inhibitors. Herein, we designed 12-mer peptide inhibitors to target p25-inducing-cyclin-dependent kinase (Cdk5) hyperregulation, a PPI that has been shown to perpetuate neuroinflammation, which is one of the major causal implications of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and frontotemporal dementia. We generated a library of 5 062 500 peptide combination sequences (PCS) derived from the interaction motif of Cdk5/p25 PP interface. The 20 amino acids were differentiated into six groups, namely, hydrophobic (aliphatic), aromatic, basic, acidic, unique, and polar uncharged, on the basis of their physiochemical properties. To preserve the interaction motif necessary for ideal binding, de novo modeling of all possible peptide sequence substitutions was considered. A set of filters, backed by the Support Vector Machine (SVM) algorithm, was then used to create a shortlisted custom peptide library that met specific bioavailability, toxicity, and therapeutic relevance, leading to a refined library of 15 PCS. A greedy algorithm and coarse-grained force field were used to predict peptide structure and folding before subsequent modeling studies. Molecular docking was performed to estimate the relative binding affinities, and out of the top hits, Pep15 was subjected to molecular dynamics simulations and binding free-energy calculations in comparison to a known peptide inhibitor with experimental data (template peptide). Interestingly, the identified peptide through our protocol, Pep15, was found to show a significantly higher binding affinity than the reference template peptide (-48.10 ± 0.23 kcal/mol and -17.53 ± 0.27 kcal/mol, respectively). In comparison to the template peptide, Pep15 was found to possess a more compact and buried surface area, tighter binding landscape, and reduced conformational variability, leading to enhanced structural and kinetic stability of the Cdk5/p25 complex. Notably, both peptide inhibitors were found to have a minimal impact on the architectural integrity of the Cdk5/p25 secondary structure. Herein, we propose Pep15 as a novel and potentially disruptive peptide drug for Cdk5/p25-mediated neurodegenerative phenotypes that require further clinical investigation. The systematic protocol and findings of this report would serve as a valuable tool in the identification of critical PPI interface reactive residues, designing of analogs, and identification of more potent peptide-based PPI inhibitors.

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.

Leech, potato, and tomato carboxypeptidase inhibitors against Anopheles stephensi carboxypeptidase B1 and B2

Carboxypeptidase B (CPB) in Anopheles spp. breaks down blood and releases free amino acids, which promote Plasmodium sexual development in the mosquito midgut. Our goal was to computationally assess the inhibitory effectiveness of carboxypeptidase inhibitors obtained from tomato, potato (CPiSt), and leech against the Anopheles stephensi CPBAs1 and CPBAs2 enzymes. The tertiary structures of CPB inhibitors were predicted and their interaction mode with CPBAs1 and CPBAs2 were examined using molecular docking. Next, this data was compared with four licensed medications that are known to reduce the Anopheles' CPB activity. Molecular dynamics simulations were used to evaluate the stability of complexes containing CPiSt and its mutant form. Both CPiSt and its mutant form showed promise as possible candidates for further evaluations in the paratransgenesis technique for malaria control, based on the similar bindings of CPiSt and CPiSt-Mut to the active sites of CPBAs1 and CPBAs2, as well as their binding affinity in comparison to the drugs.

Variant Impact Predictor database (VIPdb), version 2: trends from three decades 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 three decades, 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 190 VIPs, resulting in a total of 407 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 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

Advanced vaccinomic, immunoinformatic, and molecular modeling strategies for designing Multi- epitope vaccines against the Enterobacter cloacae complex

The increasing and ongoing issue of antibiotic resistance in bacteria is of huge concern globally, mainly to healthcare facilities. It is now crucial to develop a vaccine for therapeutic and preventive purposes against the bacterial species causing hospital-based infections. Among the many antibiotic- resistant bacterial pathogens, the Enterobacter cloacae complex (ECC) including six species, E. Colcae, E. absuriae, E. kobie, E. hormaechei, E. ludwigii, and E. nimipressuralis, are dangerous to public health and may worsen the situation. Vaccination plays a vital role in the prevention of infections and infectious diseases. This research highlighted the construction and design of a multi-epitope vaccine for the E. cloacae complex by retrieving their complete sequenced proteome. The retrieved proteome was assessed to opt for potential vaccine candidates using immunoinformatic tools. Both B and T-cell epitopes were predicted in order to create both humoral and cellular immunity and further scrutinized for antigenicity, allergenicity, water solubility, and toxicity analysis. The final potential epitopes were subjected to population coverage analysis. Major histocompatibility complex (MHC) class combined, and MHC Class I and II world population coverage was obtained as 99.74%, and 98.55% respectively while a combined 81.81% was covered. A multi-epitope peptide-based vaccine construct consisting of the adjuvant, epitopes, and linkers was subjected to the ProtParam tool to calculate its physiochemical properties. The total amino acids were 236, the molecular weight was 27.64kd, and the vaccine construct was stable with an instability index of 27.01. The Grand Average of Hydropathy (GRAVY) (hydrophilicity) value obtained was -0.659, being more negative and depicting the hydrophilic character. It was non-allergen antigenic with an antigenicity of 0.8913. The vaccine construct was further validated for binding efficacy with immune cell receptors MHC-I, MHC-II, and Toll-like receptor (TLR)-4. The molecular docking results depict that the designed vaccine has good binding potency with immune receptors crucial for antigen presentation and processing. Among the Vaccine-MHC-I, Vaccine-MHC-II, and Vaccine-TLR-4 complexes, the best-docked poses were identified based on their lowest binding energy scores of -886.8, -995.6, and -883.6, respectively. Overall, we observed that the designed vaccine construct can evoke a proper immune response and the construct could help experimental researchers in the formulation of a vaccine against the targeted pathogens.

Solvent induced amyloid polymorphism and the uncovering of the elusive class 3 amyloid topology

Aggregation-prone-motifs (APRs) of proteins are short segments, which - as isolated peptides - form diverse amyloid-like crystals. We introduce two APRs - designed variants of the incretin mimetic Exendin-4 - that both display crystal-phase polymorphism. Crystallographic and spectroscopic analysis revealed that a single amino-acid substitution can greatly reduce topological variability: while LYIQWL can form both parallel and anti-parallel β-sheets, LYIQNL selects only the former. We also found that the parallel/anti-parallel switch of LYIQWL can be induced by simply changing the crystallization temperature. One crystal form of LYIQNL was found to belong to the class 3 topology, an arrangement previously not encountered among proteinogenic systems. We also show that subtle environmental changes lead to crystalline assemblies with different topologies, but similar interfaces. Spectroscopic measurements showed that polymorphism is already apparent in the solution state. Our results suggest that the temperature-, sequence- and environmental sensitivity of physiological amyloids is reflected in assemblies of the APR segments, which, complete with the new class 3 crystal form, effectively sample all the originally proposed basic topologies of amyloid-like aggregates.

Quercetin-Loaded Nanocarriers as Effective Inhibitors for Copper Metal Ion-Induced γD-Crystallin Aggregation

Cataract is one of the leading causes of blindness worldwide. Till date, the only solution for cataracts is surgery, which is a resource-intensive solution. A much simpler solution is to find a potential drug that could inhibit aggregation. It is well established that nonamyloid aggregates of eye lens protein result in cataract. γD-Crystallin, a thermodynamically stable protein, is one of the most abundant proteins in the core of the eye lens and is found to aggregate under stress conditions, leading to the cataract. It has also been found that in cataractous lens, the concentration of metals like copper is elevated significantly as compared to healthy eye lens, suggesting their role in inducing aggregation. In our present study, aggregation of γD-Crystallin was carried out in the presence of Cu (II). Using techniques like turbidity assay, CD spectroscopy, ANS binding assay, and microscopic studies like TEM, it could be confirmed that protein aggregates in the presence of Cu (II) and the nature of aggregates is amorphous. Various polyphenols were tested to suppress aggregation of the protein. Quercetin was observed to be the most efficient. To overcome the problems associated with the delivery of polyphenols, such as solubility and bioavailability, quercetin was encapsulated in two types of nanocarriers. Their characterization was done using TEM, DLS, and other techniques. The potency of quercetin-loaded CS-TPP/CS-PLGA NPs as inhibitors of γD-Crystallin aggregation was confirmed by various experiments.

Rapid classification of a novel ALS-causing I149S variant in superoxide dismutase-1

Variants of the oxygen free radical scavenging enzyme superoxide dismutase-1 (SOD1) are associated with the neurodegenerative disease amyotrophic lateral sclerosis (ALS). These variants occur in roughly 20% of familial ALS cases, and 1% of sporadic ALS cases. Here, we identified a novel SOD1 variant in a patient in their 50s who presented with movement deficiencies and neuropsychiatric features. The variant was heterozygous and resulted in the isoleucine at position 149 being substituted with a serine (I149S). In silico analysis predicted the variant to be destabilizing to the SOD1 protein structure. Expression of the SOD1I149S variant with a C-terminal EGFP tag in neuronal-like NSC-34 cells resulted in extensive inclusion formation and reduced cell viability. Immunoblotting revealed that the intramolecular disulphide between Cys57 and Cys146 was fully reduced for SOD1I149S. Furthermore, SOD1I149S was highly susceptible to proteolytic digestion, suggesting a large degree of instability to the protein fold. Finally, fluorescence correlation spectroscopy and native-PAGE of cell lysates showed that SOD1I149S was monomeric in solution in comparison to the dimeric SOD1WT. This experimental data was obtained within 3 months and resulted in the rapid re-classification of the variant from a variant of unknown significance (VUS) to a clinically actionable likely pathogenic variant.

Characterizing the amyloid core region of the tumor suppressor protein p16INK4a using a limited proteolysis and peptide-based approach

The human tumor suppressor p16INK4a is a small monomeric protein that can form amyloid structures. Formation of p16INK4a amyloid fibrils is induced by oxidation which creates an intermolecular disulfide bond. The conversion into amyloid is associated with a change from an all α-helical structure into β-sheet fibrils. Currently, structural insights into p16INK4a amyloid fibrils are lacking. Here, we investigate the amyloid-forming regions of this tumor suppressor using isotope-labeling limited-digestion mass spectrometry analysis. We discover two key regions that likely form the structured core of the amyloid. Further investigations using thioflavin-T fluorescence assays, electron microscopy, and solution nuclear magnetic resonance spectroscopy of shorter peptide regions confirm the self-assembly of the identified sequences that include methionine and leucine repeat regions. This work describes a simple approach for studying protein motifs involved in the conversion of monomeric species into aggregated fibril structures. It provides insight into the polypeptide sequence underlying the core structure of amyloid p16INK4a formed after a unique oxidation-driven structural transition.

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.

Aggrescan4D: structure-informed analysis of pH-dependent protein aggregation

Protein aggregation is behind the genesis of incurable diseases and imposes constraints on drug discovery and the industrial production and formulation of proteins. Over the years, we have been advancing the Aggresscan3D (A3D) method, aiming to deepen our comprehension of protein aggregation and assist the engineering of protein solubility. Since its inception, A3D has become one of the most popular structure-based aggregation predictors because of its performance, modular functionalities, RESTful service for extensive screenings, and intuitive user interface. Building on this foundation, we introduce Aggrescan4D (A4D), significantly extending A3D's functionality. A4D is aimed at predicting the pH-dependent aggregation of protein structures, and features an evolutionary-informed automatic mutation protocol to engineer protein solubility without compromising structure and stability. It also integrates precalculated results for the nearly 500,000 jobs in the A3D Model Organisms Database and structure retrieval from the AlphaFold database. Globally, A4D constitutes a comprehensive tool for understanding, predicting, and designing solutions for specific protein aggregation challenges. The A4D web server and extensive documentation are available at https://biocomp.chem.uw.edu.pl/a4d/. This website is free and open to all users without a login requirement.

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/.

A new lysine biosynthetic enzyme from a bacterial endosymbiont shaped by genetic drift and genome reduction

The effect of population bottlenecks and genome reduction on enzyme function is poorly understood. Candidatus Liberibacter solanacearum is a bacterium with a reduced genome that is transmitted vertically to the egg of an infected psyllid-a population bottleneck that imposes genetic drift and is predicted to affect protein structure and function. Here, we define the function of Ca. L. solanacearum dihydrodipicolinate synthase (CLsoDHDPS), which catalyzes the committed branchpoint reaction in diaminopimelate and lysine biosynthesis. We demonstrate that CLsoDHDPS is expressed in Ca. L. solanacearum and expression is increased ~2-fold in the insect host compared to in planta. CLsoDHDPS has decreased thermal stability and increased aggregation propensity, implying mutations have destabilized the enzyme but are compensated for through elevated chaperone expression and a stabilized oligomeric state. CLsoDHDPS uses a ternary-complex kinetic mechanism, which is to date unique among DHDPS enzymes, has unusually low catalytic ability, but an unusually high substrate affinity. Structural studies demonstrate that the active site is more open, and the structure of CLsoDHDPS with both pyruvate and the substrate analogue succinic-semialdehyde reveals that the product is both structurally and energetically different and therefore evolution has in this case fashioned a new enzyme. Our study suggests the effects of genome reduction and genetic drift on the function of essential enzymes and provides insights on bacteria-host co-evolutionary associations. We propose that bacteria with endosymbiotic lifestyles present a rich vein of interesting enzymes useful for understanding enzyme function and/or informing protein engineering efforts.

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.

Protonation-State Dependent Modulation of Hen Egg-White Lysozyme Fibrillation under the Influence of a Short Synthetic Peptide

Under the influence of various conditions, misfolding of soluble proteins occurs, leading to the formation of toxic insoluble amyloids. The formation and deposition of such amyloids within the body are associated with detrimental biological consequences such as the onset of several amyloid-related diseases. Previously, we established a strategy for the rational design of peptide inhibitors against amyloid formation based on the amyloidogenic-prone region of the protein. In the current study, we have designed and identified an Asp-containing rationally designed hexapeptide (SqP4) as an excellent inhibitor of hen egg-white lysozyme (HEWL) amyloid progression in vitro. First, SqP4 showed strong affinity toward the native monomeric HEWL leading to the stabilization of the native form and restriction in the unfolding process of monomeric HEWL. Second, SqP4 was found to arrest the amyloidogenic misfolded structure of HEWL in a nonfibrillar monomer-like stage. We also observed the differential effect of the protonation state of the charged amino acid (Asp) within the peptide inhibitor on the amyloid formation of HEWL and explored the reason behind the observations. The findings of this study can be implemented in future strategies for the development of potent therapeutics against other amyloid-related diseases.

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.

Amyloidogenic regions in beta-strands II and III modulate the aggregation and toxicity of SOD1 in living cells

Mutations in the protein superoxide dismutase-1 (SOD1) promote its misfolding and aggregation, ultimately causing familial forms of the debilitating neurodegenerative disease amyotrophic lateral sclerosis (ALS). Currently, over 220 (mostly missense) ALS-causing mutations in the SOD1 protein have been identified, indicating that common structural features are responsible for aggregation and toxicity. Using in silico tools, we predicted amyloidogenic regions in the ALS-associated SOD1-G85R mutant, finding seven regions throughout the structure. Introduction of proline residues into β-strands II (I18P) or III (I35P) reduced the aggregation propensity and toxicity of SOD1-G85R in cells, significantly more so than proline mutations in other amyloidogenic regions. The I18P and I35P mutations also reduced the capability of SOD1-G85R to template onto previously formed non-proline mutant SOD1 aggregates as measured by fluorescence recovery after photobleaching. Finally, we found that, while the I18P and I35P mutants are less structurally stable than SOD1-G85R, the proline mutants are less aggregation-prone during proteasome inhibition, and less toxic to cells overall. Our research highlights the importance of a previously underappreciated SOD1 amyloidogenic region in β-strand II (15QGIINF20) to the aggregation and toxicity of SOD1 in ALS mutants, and suggests that β-strands II and III may be good targets for the development of SOD1-associated ALS therapies.

Hotspot site microenvironment in the deubiquitinase OTUB1 drives its stability and aggregation

Lewy bodies (LB) are aberrant protein accumulations observed in the brain cells of individuals affected by Parkinson's disease (PD). A comprehensive analysis of LB proteome identified over a hundred proteins, many co-enriched with α-synuclein, a major constituent of LB. Within this context, OTUB1, a deubiquitinase detected in LB, exhibits amyloidogenic properties, yet the mechanisms underlying its aggregation remain elusive. In this study, we identify two critical sites in OTUB1-namely, positions 133 and 173-that significantly impact its amyloid aggregation. Substituting alanine at position 133 and lysine at position 173 enhances both thermodynamic and kinetic stability, effectively preventing amyloid aggregation. Remarkably, lysine at position 173 demonstrates the highest stability without compromising enzymatic activity. The increased stability and inhibition of amyloid aggregation are attributed mainly to the changes in the specific microenvironment at the hotspot. In our exploration of the in-vivo co-occurrence of α-synuclein and OTUB1 in LB, we observed a synergistic modulation of each other's aggregation. Collectively, our study unveils the molecular determinants influencing OTUB1 aggregation, shedding light on the role of specific residues in modulating aggregation kinetics and structural transition. These findings contribute valuable insights into the complex interplay of amino acid properties and protein aggregation, with potential implications for understanding broader aspects of protein folding and aggregation phenomena.

PACSAB Server: A Web-Based Tool for the Study of Aggregation and the Conformational Ensemble of Disordered and Folded Proteins

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page.

Recombinant multiepitope proteins expressed in Escherichia coli cells and their potential for immunodiagnosis

Recombinant multiepitope proteins (RMPs) are a promising alternative for application in diagnostic tests and, given their wide application in the most diverse diseases, this review article aims to survey the use of these antigens for diagnosis, as well as discuss the main points surrounding these antigens. RMPs usually consisting of linear, immunodominant, and phylogenetically conserved epitopes, has been applied in the experimental diagnosis of various human and animal diseases, such as leishmaniasis, brucellosis, cysticercosis, Chagas disease, hepatitis, leptospirosis, leprosy, filariasis, schistosomiasis, dengue, and COVID-19. The synthetic genes for these epitopes are joined to code a single RMP, either with spacers or fused, with different biochemical properties. The epitopes' high density within the RMPs contributes to a high degree of sensitivity and specificity. The RMPs can also sidestep the need for multiple peptide synthesis or multiple recombinant proteins, reducing costs and enhancing the standardization conditions for immunoassays. Methods such as bioinformatics and circular dichroism have been widely applied in the development of new RMPs, helping to guide their construction and better understand their structure. Several RMPs have been expressed, mainly using the Escherichia coli expression system, highlighting the importance of these cells in the biotechnological field. In fact, technological advances in this area, offering a wide range of different strains to be used, make these cells the most widely used expression platform. RMPs have been experimentally used to diagnose a broad range of illnesses in the laboratory, suggesting they could also be useful for accurate diagnoses commercially. On this point, the RMP method offers a tempting substitute for the production of promising antigens used to assemble commercial diagnostic kits.

Gut microbiota produces biofilm-associated amyloids with potential for neurodegeneration

Age-related neurodegenerative diseases involving amyloid aggregation remain one of the biggest challenges of modern medicine. Alterations in the gastrointestinal microbiome play an active role in the aetiology of neurological disorders. Here, we dissect the amyloidogenic properties of biofilm-associated proteins (BAPs) of the gut microbiota and their implications for synucleinopathies. We demonstrate that BAPs are naturally assembled as amyloid-like fibrils in insoluble fractions isolated from the human gut microbiota. We show that BAP genes are part of the accessory genomes, revealing microbiome variability. Remarkably, the abundance of certain BAP genes in the gut microbiome is correlated with Parkinson's disease (PD) incidence. Using cultured dopaminergic neurons and Caenorhabditis elegans models, we report that BAP-derived amyloids induce α-synuclein aggregation. Our results show that the chaperone-mediated autophagy is compromised by BAP amyloids. Indeed, inoculation of BAP fibrils into the brains of wild-type mice promote key pathological features of PD. Therefore, our findings establish the use of BAP amyloids as potential targets and biomarkers of α-synucleinopathies.

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.

Furosemide Derails Human Lysozyme Fibrillation by Interacting with Aggregation Hot Spots: A Biophysical Comprehension

Kidney-associated human lysozyme amyloidosis leads to renal impairments;thus, patients are often prescribed furosemide. Based on this fact, the effect of furosemide on induced human lysozyme fibrillation, in vitro, is evaluated by spectroscopic, calorimetric, computational, and cellular-based assays/methods. Results show that furosemide increases the lag phase and decreases the apparent rate of aggregation of human lysozyme, thereby decelerating the nucleation phase and amyloid fibril formation, as confirmed by the decrease in the level of Thioflavin-T fluorescence. Fewer entities of hydrodynamic radii of ∼171 nm instead of amyloid fibrils (∼412 nm) are detected in human lysozyme in the presence of furosemide by dynamic light scattering. Moreover, furosemide decreases the extent of conversion of the α/β structure of human lysozyme into a predominant β-sheet. The isothermal titration calorimetry established that furosemide forms a complex with human lysozyme, which was also confirmed through fluorescence quenching and computational studies. Also, human lysozyme lytic activity is inhibited competitively by furosemide due to the involvement of amino acid residues of the active site in catalysis, as well as complex formation. Conclusively, furosemide interacts with Gln58, Ile59, Asn60, Ala108, and Trp109 of aggregation-prone regions 2 and 4 of human lysozyme, thereby masking its sites of aggregation and generating only lower-order entities that are less toxic to red blood cells than the fibrils. Thus, furosemide slows the progression of amyloid fibrillation in human lysozyme.

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/.

Intrinsically disordered Pseudomonas chaperone FapA slows down the fibrillation of major biofilm-forming functional amyloid FapC

Functional bacterial amyloids play a crucial role in the formation of biofilms, which mediate chronic infections and contribute to antimicrobial resistance. This study focuses on the FapC amyloid fibrillar protein from Pseudomonas, a major contributor to biofilm formation. We investigate the initial steps of FapC amyloid formation and the impact of the chaperone-like protein FapA on this process. Using solution nuclear magnetic resonance (NMR), we recently showed that both FapC and FapA are intrinsically disordered proteins (IDPs). Here, the secondary structure propensities (SSPs) are compared to alphafold (DeepMind, protein structure prediction tool/algorithm: https://alphafold.ebi.ac.uk/) models. We further demonstrate that the FapA chaperone interacts with FapC and significantly slows down the formation of FapC fibrils. Our NMR titrations reveal ~ 18% of the resonances show FapA-induced chemical shift perturbations (CSPs), which has not been previously observed, the largest being for A82, N201, C237, C240, A241, and G245. These sites may suggest a specific interaction site and/or hotspots of fibrillation inhibition/control interface at the repeat-1 (R1)/loop-2 (L2) and L2/R3 transition areas and at the C-terminus of FapC. Remarkably, ~ 90% of FapA NMR signals exhibit substantial CSPs upon titration with FapC, the largest being for S63, A69, A80, and I92. A temperature-dependent effect of FapA was observed on FapC by thioflavin T (ThT) and NMR experiments. This study provides a detailed understanding of the interaction between the FapA and FapC, shedding light on the regulation and slowing down of amyloid formation, and has important implications for the development of therapeutic strategies targeting biofilms and associated infections.

A Rationally Designed Synthetic Antiviral Peptide Binder Targeting the Receptor-Binding Domain of SARS-CoV-2

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a novel coronavirus, is the causative agent responsible for the spread of the COVID19 pandemic across the globe. The global impact of the COVID19 pandemic, the successful approval of vaccines for controlling the pandemic, and the further resurgence of COVID19 necessitate the exploration and validation of alternative therapeutic avenues targeting SARS-CoV-2. The initial entry and further invasion by SARS-CoV-2 require strong protein-protein interactions (PPIs) between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and the human angiotensin-converting enzyme 2 (ACE2) receptors expressed on the cell surfaces of various tissues. In principle, disruption of the PPIs between the RBD of SARS-CoV-2 and the ACE2 receptor by designer peptides with optimized pharmacology appears to be an ideal choice for potentially preventing viral entry with minimal immunogenicity. In this context, the current study describes a short, synthetic designer peptide (codenamed SR16, ≤18 aa, molecular weight ≤2.5 kDa), which has a few noncoded amino acids, demonstrates a helical conformation in solution, and also engages the RBD of SARS-CoV-2 through a high-affinity interaction, as judged from a battery of biophysical studies. Further, the designer peptide demonstrates resistance to trypsin degradation, appears to be nontoxic to mammalian cells, and also does not induce hemolysis in freshly isolated human erythrocytes. In summary, SR16 appears to be an ideal peptide binder targeting the RBD of SARS-CoV-2, which has the potential for further optimization and development as an antiviral agent targeting SARS-CoV-2.

Prediction of protein aggregation

The scientific community is very interested in protein aggregation because of its involvement in several neurodegenerative diseases and its significance in industry. Remarkably, fibrillar aggregates are utilized naturally for constructing structural scaffolds or creating biological switches and may be intentionally designed to construct versatile nanomaterials. Consequently, there is a significant need to rationalize and predict protein aggregation. Researchers have developed various computational methodologies and algorithms to predict protein aggregation and understand its underlying mechanics. This chapter aims to summarize the significant advancements in computational methods, accessible resources, and prospective developments in the field of in silico research. We assess the existing computational tools for predicting protein aggregation propensities, detecting areas that are prone to sequential and structural aggregation, analyzing the effects of mutations on protein aggregation, or identifying prion-like domains.

Pathways of amyloid fibril formation and protein aggregation

The main cause of many neurodegenerative diseases and systemic amyloidoses is protein and peptide aggregation and the formation of amyloid fibrils. The study of aggregation mechanisms, the discovery and description of aggregate structures, and a comprehensive understanding of the molecular mechanisms of amyloid formation are of great importance for the diagnostic processes at the molecular level and for the development of therapeutic strategies to counter aggregation-associated disorders. Given that understanding protein misfolding phenomena is directly related to the protein folding process, we will briefly explain the protein folding mechanism and then discuss the important factors involved in protein aggregation. In the following, we review different mechanisms of amyloid formation and finally represent the current knowledge on how amyloid fibrils are formed based on kinetic and thermodynamic factors.

Rational design of antibody-like peptides for targeting the human complement fragment protein C5a

Human complement fragment 5a (C5a) is one of the most potent glycoproteins generated downstream of C3a and C4a during late-stage activation of the complement signaling cascade. C5a recruits receptors like C5aR1 and C5aR2 and is established to play a critical role in complement-mediated inflammation. Thus, excessive C5a in the plasma due to aberrant activation of the complement contributes to the pathophysiology of several chronic inflammatory diseases. Therefore, restricting the excessive interaction of C5a with its receptors by neutralizing C5a has been one of the most effective therapeutic strategies for the management of inflammatory diseases. Indeed, antibodies targeting C5 (Eculizumab), the precursor of C5a, and C5a (Vilobelimab) have already been approved by the FDA. Still, small designer peptides that work like antibodies and can target and stop C5a from interacting with its receptors seem to be a possible therapeutic alternative to antibodies because they are smaller, cheaper to make, more specific to their target, and can get through membrane barriers. As a proof-of-principle, the current study describes the computational design and evaluation of a pair of peptides that are able to form stable high-affinity complexes with the epitope regions of C5a that are important for the recruitment of C5aR1 and C5aR2. The computational data further supports the potential of designer peptides for mimicking the function of antibodies targeting C5a. However, further experimental studies will be required to establish the structure-function relationship of the designer peptides and also to establish the hypothesis of antibody-like peptides targeting C5a.

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.