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

Multiple Antimicrobial Effects of Hybrid Peptides Synthesized Based on the Sequence of Ribosomal S1 Protein from Staphylococcus aureus

The need to develop new antimicrobial peptides is due to the high resistance of pathogenic bacteria to traditional antibiotics now and in the future. The creation of synthetic peptide constructs is a common and successful approach to the development of new antimicrobial peptides. In this work, we use a simple, flexible, and scalable technique to create hybrid antimicrobial peptides containing amyloidogenic regions of the ribosomal S1 protein from Staphylococcus aureus. While the cell-penetrating peptide allows the peptide to enter the bacterial cell, the amyloidogenic site provides an antimicrobial effect by coaggregating with functional bacterial proteins. We have demonstrated the antimicrobial effects of the R23F, R23DI, and R23EI hybrid peptides against Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), Pseudomonas aeruginosa, Escherichia coli, and Bacillus cereus. R23F, R23DI, and R23EI can be used as antimicrobial peptides against Gram-positive and Gram-negative bacteria resistant to traditional antibiotics.

Prediction of the Effect of pH on the Aggregation and Conditional Folding of Intrinsically Disordered Proteins with SolupHred and DispHred

Proteins microenvironments modulate their structures. Binding partners, organic molecules, or dissolved ions can alter the protein's compaction, inducing aggregation or order-disorder conformational transitions. Surprisingly, bioinformatic platforms often disregard the protein context in their modeling. In a recent work, we proposed that modeling how pH affects protein net charge and hydrophobicity might allow us to forecast pH-dependent aggregation and conditional disorder in intrinsically disordered proteins (IDPs). As these approaches showed remarkable success in recapitulating the available bibliographical data, we made these prediction methods available for the scientific community as two user-friendly web servers. SolupHred is the first dedicated software to predict pH-dependent aggregation, and DispHred is the first pH-dependent predictor of protein disorder. Here we dissect the features of these two software applications to train and assist scientists in studying pH-dependent conformational changes in IDPs.

Protocols for Rational Design of Protein Solubility and Aggregation Properties Using Aggrescan3D Standalone

Protein aggregation is a major hurdle in the development and manufacturing of protein-based therapeutics. Development of aggregation-resistant and stable protein variants can be guided by rational redesign using computational tools. Here, we describe the architecture and functionalities of the Aggrescan3D (A3D) standalone package for the rational design of protein solubility and aggregation properties based on three-dimensional protein structures. We present the case studies of the three therapeutic proteins, including antibodies, exploring the practical use of the A3D standalone tool. The case studies demonstrate that protein solubility can be easily improved by the A3D prediction of non-destabilizing amino acid mutations at the protein surfaces.

A3D 2.0 Update for the Prediction and Optimization of Protein Solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this chapter is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

Intrinsically disordered proteins identified in the aggregate proteome serve as biomarkers of neurodegeneration

A protein's structure is determined by its amino acid sequence and post-translational modifications, and provides the basis for its physiological functions. Across all organisms, roughly a third of the proteome comprises proteins that contain highly unstructured or intrinsically disordered regions. Proteins comprising or containing extensive unstructured regions are referred to as intrinsically disordered proteins (IDPs). IDPs are believed to participate in complex physiological processes through refolding of IDP regions, dependent on their binding to a diverse array of potential protein partners. They thus play critical roles in the assembly and function of protein complexes. Recent advances in experimental and computational analyses predicted multiple interacting partners for the disordered regions of proteins, implying critical roles in signal transduction and regulation of biological processes. Numerous disordered proteins are sequestered into aggregates in neurodegenerative diseases such as Alzheimer's disease (AD) where they are enriched even in serum, making them good candidates for serum biomarkers to enable early detection of AD.

Is amyloid fibrillation related to 3D domain swapping for the C-terminal domain of SARS-CoV main protease?

The C-terminal domain of SARS-CoV main protease (M^pro-C) can form 3D domain-swapped dimer by exchanging the α₁-helices fully buried inside the protein hydrophobic core, under non-denaturing conditions. Here, we report that M^pro-C can also form amyloid fibrils under the 3D domain-swappable conditions in vitro, and the fibrils are not formed through runaway/propagated domain swapping. It is found that there are positive correlations between the rates of domain swapping dimerization and amyloid fibrillation at different temperatures, and for different mutants. However, some M^pro-C mutants incapable of 3D domain swapping can still form amyloid fibrils, indicating that 3D domain swapping is not essential for amyloid fibrillation. Furthermore, NMR H/D exchange data and molecular dynamics simulation results suggest that the protofibril core region tends to unpack at the early stage of 3D domain swapping, so that the amyloid fibrillation can proceed during the 3D domain swapping process. We propose that 3D domain swapping makes it possible for the unpacking of the amyloidogenic fragment of the protein and thus accelerates the amyloid fibrillation process kinetically, which explains the well-documented correlations between amyloid fibrillation and 3D domain swapping observed in many proteins.

Heterotypic amyloid interactions: Clues to polymorphic bias and selective cellular vulnerability?

The number of atomic-resolution structures of disease-associated amyloids has greatly increased in recent years. These structures have confirmed not only the polymorphic nature of amyloids but also the association of specific polymorphs to particular proteinopathies. These observations are strengthening the view that amyloid polymorphism is a marker for specific pathological subtypes (e.g. in tauopathies or synucleinopathies). The nature of this association and how it relates to the selective cellular vulnerability of amyloid nucleation, propagation and toxicity are still unclear. Here, we provide an overview of the mechanistic insights provided by recent patient-derived amyloid structures. We discuss the framework organisation of amyloid polymorphism and how heterotypic amyloid interactions with the physiological environment could modify the solubility and assembly of amyloidogenic proteins. We conclude by hypothesising how such interactions could contribute to selective cellular vulnerability.

Peptides derived from gp43, the most antigenic protein from Paracoccidioides brasiliensis, form amyloid fibrils in vitro: implications for vaccine development

Fungal infection is an important health problem in Latin America, and in Brazil in particular. Paracoccidioides (mainly P. brasiliensis and P. lutzii) is responsible for paracoccidioidomycosis, a disease that affects mainly the lungs. The glycoprotein gp43 is involved in fungi adhesion to epithelial cells, which makes this protein an interesting target of study. A specific stretch of 15 amino acids that spans the region 181–195 (named P10) of gp43 is an important epitope of gp43 that is being envisioned as a vaccine candidate. Here we show that synthetic P10 forms typical amyloid aggregates in solution in very short times, a property that could hamper vaccine development. Seeds obtained by fragmentation of P10 fibrils were able to induce the aggregation of P4, but not P23, two other peptides derived from gp43. In silico analysis revealed several regions within the P10 sequence that can form amyloid with steric zipper architecture. Besides, in-silico proteolysis studies with gp43 revealed that aggregation-prone, P10-like peptides could be generated by several proteases, which suggests that P10 could be formed under physiological conditions. Considering our data in the context of a potential vaccine development, we redesigned the sequence of P10, maintaining the antigenic region (HTLAIR), but drastically reducing its aggregation propensity.

Binder design for targeting SARS-CoV-2 spike protein: An in silico perspective

Introduction

The COVID-19 pandemic is now affecting all people around the world and getting worse. New antiviral medications are desperately needed other than the few approved medications that have shown no promising efficacy so far.

Methods

Here we report three blocking binders for targeting SARS-CoV-2 spike protein to block the interaction between the spike protein on the SARS-CoV-2 and the angiotensin-converting enzyme 2 (ACE2) receptors, responsible for viral homing into the alveolar epithelium type II cells (AECII).

Results

The design process is based on the collected natural scaffolds and using Rosetta interface for designing the binders.

Conclusion

Based on the structural analysis, three binders were selected, and the results showed that they might be promising as new therapeutic targets for blocking COVID-19.

Influence of the macromolecular crowder alginate in the fibrillar organization of the functional amyloid FapC from Pseudomonas aeruginosa

Bacterial biofilms are an alternative lifestyle in which communities of bacteria are embedded in an extracellular matrix manly composed by polysaccharides, nucleic acids and proteins, being the hallmark of bacterial survival in a variety of ecological niches. Amyloid fibrils are one of the proteinaceous components of such extracellular crowded environments. FapC is the main component of the functional amyloid recently discovered in Pseudomonas species, including the opportunistic pathogen P. aeruginosa, which is a major cause of nosocomial infections and contamination of medical devices. Considering that several functional roles have been attributed to this bacterial amyloid, FapC emerged as a novel target to control Pseudomonas biofilm formation and to design new treatments against chronic infections. In this study, we used complementary biophysical techniques to evaluate conformational signatures of FapC amyloids formed in the presence of alginate, the major exopolysaccharide associated with the mucoid phenotype of P. aeruginosa strains isolated from cystic fibrosis patients. We found that the this naturally occurring macromolecular crowder leads to morphological similar yet polymorphic FapC fibrils, highlighting the importance of considering the complexity of the extracellular matrix in order to improve our understanding of microbial functional amyloids.

Protection of human γD-crystallin protein from ultraviolet C-induced aggregation by ortho-vanillin

Cataract is known as one of the leading causes of vision impairment worldwide. While the detailed mechanism of cataratogenesis remains unclear, cataract is believed to be correlated with the aggregation and/or misfolding of human ocular lens proteins called crystallins. A 173-residue structural protein human γD-crystallin is a major γ-crystallin protein in the human eye lens and associated with the development of juvenile and mature-onset cataracts. This work is aimed at investigating the effect of a small molecule, e.g., ortho-vanillin, on human γD-crystallin aggregation upon exposure to ultraviolet-C irradiation. According to the findings of right-angle light scattering, transmission electron microscopy, and gel electrophoresis, ortho-vanillin was demonstrated to dose-dependently suppress ultraviolet-C-triggered aggregation of human γD-crystallin. Results from the synchronous fluorescence spectroscopy, tryptophan fluorescence quenching, and molecular docking studies revealed the structural change of γD-crystallin induced by the interaction/binding between ortho-vanillin and protein. We believe the outcome from this work may contribute to the development of potential therapeutics for cataract.

ReRF-Pred: predicting amyloidogenic regions of proteins based on their pseudo amino acid composition and tripeptide composition

BACKGROUND

Amyloids are insoluble fibrillar aggregates that are highly associated with complex human diseases, such as Alzheimer's disease, Parkinson's disease, and type II diabetes. Recently, many studies reported that some specific regions of amino acid sequences may be responsible for the amyloidosis of proteins. It has become very important for elucidating the mechanism of amyloids that identifying the amyloidogenic regions. Accordingly, several computational methods have been put forward to discover amyloidogenic regions. The majority of these methods predicted amyloidogenic regions based on the physicochemical properties of amino acids. In fact, position, order, and correlation of amino acids may also influence the amyloidosis of proteins, which should be also considered in detecting amyloidogenic regions.

RESULTS

To address this problem, we proposed a novel machine-learning approach for predicting amyloidogenic regions, called ReRF-Pred. Firstly, the pseudo amino acid composition (PseAAC) was exploited to characterize physicochemical properties and correlation of amino acids. Secondly, tripeptides composition (TPC) was employed to represent the order and position of amino acids. To improve the distinguishability of TPC, all possible tripeptides were analyzed by the binomial distribution method, and only those which have significantly different distribution between positive and negative samples remained. Finally, all samples were characterized by PseAAC and TPC of their amino acid sequence, and a random forest-based amyloidogenic regions predictor was trained on these samples. It was proved by validation experiments that the feature set consisted of PseAAC and TPC is the most distinguishable one for detecting amyloidosis. Meanwhile, random forest is superior to other concerned classifiers on almost all metrics. To validate the effectiveness of our model, ReRF-Pred is compared with a series of gold-standard methods on two datasets: Pep-251 and Reg33. The results suggested our method has the best overall performance and makes significant improvements in discovering amyloidogenic regions.

CONCLUSIONS

The advantages of our method are mainly attributed to that PseAAC and TPC can describe the differences between amyloids and other proteins successfully. The ReRF-Pred server can be accessed at http://106.12.83.135:8080/ReRF-Pred/.

Role of mutations and post-translational modifications in systemic AL amyloidosis studied by cryo-EM

Systemic AL amyloidosis is a rare disease that is caused by the misfolding of immunoglobulin light chains (LCs). Potential drivers of amyloid formation in this disease are post-translational modifications (PTMs) and the mutational changes that are inserted into the LCs by somatic hypermutation. Here we present the cryo electron microscopy (cryo-EM) structure of an ex vivo λ1-AL amyloid fibril whose deposits disrupt the ordered cardiomyocyte structure in the heart. The fibril protein contains six mutational changes compared to the germ line and three PTMs (disulfide bond, N-glycosylation and pyroglutamylation). Our data imply that the disulfide bond, glycosylation and mutational changes contribute to determining the fibril protein fold and help to generate a fibril morphology that is able to withstand proteolytic degradation inside the body.

Zinc oxide nanoparticle interface moderation with tyrosine and tryptophan reverses the pro-amyloidogenic property of the particle

Zinc oxide nanoparticle with negative surface potential (ZnONP) enhances bovine insulin fibrillation. Here, we are exploring ZnONP with positive surface potential (ZnONP_Unc) and surface functionalized with tyrosine and tryptophan amino acids to observe the effects of surface potential and surface functional groups on the fibrillation. ZnONP_Unc, despite of inversed surface potential, enhances the insulin fibrillation with increase in the interface concentration at physiological pH. Whereas, the interface moderation with the amino acids mitigates the surface-mediated insulin fibrillation propensity. Additionally, the study indicates that the change in interfacial functional groups at ZnONP_Unc significantly reverses the interface-mediated destabilization of insulin conformation. The functional groups from the amino acids, like CO, N-H and aromatic functional groups, are anticipated to further stabilize the insulin conformation by forming hydrogen bond and van der Waals interactions with the key amyloidogenic sequences of insulin, A13-A20 from A-chain and B9-B20 from B-chain. Hence, the altered interaction profile, with change in interfacial functional groups, mitigates the interface-mediated insulin fibrillation and the ZnONP_Unc-/fibril-mediated cytotoxicity.

Non-specific porins of Gram-negative bacteria as proteins containing intrinsically disordered regions with amyloidogenic potential

Features of the structure and functional activity of bacterial outer membrane porins, coupled with their dynamic "behavior," suggests that intrinsically disordered regions (IDPRs) are contained in their structure. Using bioinformatic analysis, the quantitative content of amyloidogenic regions in the amino acid sequence of non-specific porins inhabiting various natural niches was determined: from terrestrial bacteria of the genus Yersinia (OmpF and OmpC proteins of Y. pseudotuberculosis and Y. ruckeri) and from the marine bacterium Marinomonas primoryensis (MpOmp). It was found that OmpF and OmpC porins can be classified as moderately disordered proteins, while MpOmp can be classified as highly disordered protein. Mapping of IDPRs, performed using 3D structures of monomers of the proteins, showed that the regions of increased conformational plasticity fall on the regions, the functional importance of which has been reliably confirmed as a result of numerous experimental studies. The revealed correlation made it possible to explain the differences in the physicochemical characteristics and properties of not only porins from terrestrial and marine bacteria, but also non-specific porins of different types, OmpF and OmpC proteins. First of all, this concerns the flexible outer loops that form the pore vestibule, as well as regions of the barrel with an increased "ability" for aggregation, the so-called "hot spots" of aggregation. The abnormally high content of IDPRs in the MpOmp structure made it possible to suggest that the high adaptive potential of bacteria may correlate with an increase in the number of IDPRs and/or regions with increased conformational variability.

In Silico Analysis of Therapeutic Antibody Aggregation and the Influence of Glycosylation

The aggregation of therapeutic antibodies is a major issue for the pharmaceutical industry leading to loss of drug quality, increased dosage, and unwanted immune responses such as the production of anti-drug antibodies (ADA). As aggregation can occur at various stages of development and storage, much work has been performed to reduce or eliminate it. In this report we analyzed four antibodies available in the PDB (1IGT, 1IGY, 1HZH, and 5DK3) using the online software UCSF Chimera to study the structural features of the proteins and the associated N-linked glycans in the CH2 domains of the Fc region. To study antibody aggregation in silico we used the online software TANGO and AGGRESCAN to identify aggregation prone regions (APR) in the antibodies and the influence of the Fc glycans on hydrophobic and aromatic residues present in the APRs. In the 3D structures of 1IGT and 1IGY the glycan chains are in close enough proximity to influence and protect these hydrophobic regions. However, in the 3D structures of 1HZH and 5DK3 the glycans do not appear to influence the likely APRs of the antibodies. Therefore, in these structures we modified the Fc glycan regions by adjusting the glycosylated asparagine side chains and glycosidic bonds. We successfully adjusted the glycan chains of 1HZH and 5DK3 and reduced the distance between them and the APRs to show potential influence on aggregation. However, similar to 5DK3, the influence of glycosylation on the APRs of the antibody was limited due to the size of the glycans present in the 3D structure. This report is based on in silico studies to show how antibody glycans can influence aggregation.

HvLEAFY controls the early stages of floral organ specification and inhibits the formation of multiple ovaries in barley

Transition to the reproductive phase, inflorescence formation and flower development are crucial elements that ensure maximum reproductive success in a plant's life cycle. To understand the regulatory mechanisms underlying correct flower development in barley (Hordeum vulgare), we characterized the multiovary 5 (mov5.o) mutant. This mutant develops abnormal flowers that exhibit mosaic floral organs typified by multiple carpels at the total or partial expense of stamens. Genetic mapping positioned mov5 on the long arm of chromosome 2H, incorporating a region that encodes HvLFY, the barley orthologue of LEAFY from Arabidopsis. Sequencing revealed that, in mov5.o plants, HvLFY contains a single amino acid substitution in a highly conserved proline residue. CRISPR-mediated knockout of HvLFY replicated the mov5.o phenotype, suggesting that HvLFY_mov5 represents a loss of function allele. In heterologous assays, the HvLFY_mov5 polymorphism influenced protein-protein interactions and affinity for a putative binding site in the promoter of HvMADS58, a C-class MADS-box gene. Moreover, molecular analysis indicated that HvLFY interacts with HvUFO and regulates the expression of floral homeotic genes including HvMADS2, HvMADS4 and HvMADS16. Other distinct changes in expression differ from those reported in the rice LFY mutants apo2/rfl, suggesting that LFY function in the grasses is modulated in a species-specific manner. This pathway provides a key entry point for the study of LFY function and multiple ovary formation in barley, as well as cereal species in general.

Cryptic amyloidogenic regions in intrinsically disordered proteins: Function and disease association

The amyloid conformation is considered a fundamental state of proteins and the propensity to populate it a generic property of polypeptides. Multiple proteome-wide analyses addressed the presence of amyloidogenic regions in proteins, nurturing our understanding of their nature and biological implications. However, these analyses focused on highly aggregation-prone and hydrophobic stretches that are only marginally found in intrinsically disordered regions (IDRs). Here, we explore the prevalence of cryptic amyloidogenic regions (CARs) of polar nature in IDRs. CARs are widespread in IDRs and associated with IDPs function, with particular involvement in protein–protein interactions, but their presence is also connected to a risk of malfunction. By exploring this function/malfunction dichotomy, we speculate that ancestral CARs might have evolved into functional interacting regions playing a significant role in protein evolution at the origins of life.

Is It Possible to Create Antimicrobial Peptides Based on the Amyloidogenic Sequence of Ribosomal S1 Protein of P. aeruginosa?

The development and testing of new antimicrobial peptides (AMPs) represent an important milestone toward the development of new antimicrobial drugs that can inhibit the growth of pathogens and multidrug-resistant microorganisms such as Pseudomonas aeruginosa, Gram-negative bacteria. Most AMPs achieve these goals through mechanisms that disrupt the normal permeability of the cell membrane, which ultimately leads to the death of the pathogenic cell. Here, we developed a unique combination of a membrane penetrating peptide and peptides prone to amyloidogenesis to create hybrid peptide: "cell penetrating peptide + linker + amyloidogenic peptide". We evaluated the antimicrobial effects of two peptides that were developed from sequences with different propensities for amyloid formation. Among the two hybrid peptides, one was found with antibacterial activity comparable to antibiotic gentamicin sulfate. Our peptides showed no toxicity to eukaryotic cells. In addition, we evaluated the effect on the antimicrobial properties of amino acid substitutions in the non-amyloidogenic region of peptides. We compared the results with data on the predicted secondary structure, hydrophobicity, and antimicrobial properties of the original and modified peptides. In conclusion, our study demonstrates the promise of hybrid peptides based on amyloidogenic regions of the ribosomal S1 protein for the development of new antimicrobial drugs against P. aeruginosa.

Exploring Amyloidogenicity of Peptides From Ribosomal S1 Protein to Develop Novel AMPs

Antimicrobial peptides (AMPs) and similar compounds are potential candidates for combating antibiotic-resistant bacteria. The hypothesis of directed co-aggregation of the target protein and an amyloidogenic peptide acting as an antimicrobial peptide was successfully tested for peptides synthesized on the basis of ribosomal S1 protein in the bacterial culture of T. thermophilus. Co-aggregation of the target protein and amyloidogenic peptide was also tested for the pathogenic ribosomal S1 protein from P. aeruginosa. Almost all peptides that we selected as AMPs, prone to aggregation and formation of fibrils, based on the amino acid sequence of ribosomal S1 protein from E. coli, T. thermophilus, P. aeruginosa, formed amyloid fibrils. We have demonstrated that amyloidogenic peptides are not only toxic to their target cells, but also some of them have antimicrobial activity. Controlling the aggregation of vital bacterial proteins can become one of the new directions of research and form the basis for the search and development of targeted antibacterial drugs.

SGnn: A Web Server for the Prediction of Prion-Like Domains Recruitment to Stress Granules Upon Heat Stress

Proteins bearing prion-like domains (PrLDs) are essential players in stress granules (SG) assembly. Analysis of data on heat stress-induced recruitment of yeast PrLDs to SG suggests that this propensity might be connected with three defined protein biophysical features: aggregation propensity, net charge, and the presence of free cysteines. These three properties can be read directly in the PrLDs sequences, and their combination allows to predict protein recruitment to SG under heat stress. On this basis, we implemented SGnn, an online predictor of SG recruitment that exploits a feed-forward neural network for high accuracy classification of the assembly behavior of PrLDs. The simplicity and precision of our strategy should allow its implementation to identify heat stress-induced SG-forming proteins in complete proteomes.

Identification of a Region in the Common Amino-terminal Domain of Hendra Virus P, V, and W Proteins Responsible for Phase Transition and Amyloid Formation

Henipaviruses are BSL-4 zoonotic pathogens responsible in humans for severe encephalitis. Their V protein is a key player in the evasion of the host innate immune response. We previously showed that the Henipavirus V proteins consist of a long intrinsically disordered N-terminal domain (NTD) and a β-enriched C-terminal domain (CTD). These terminals are critical for V binding to DDB1, which is a cellular protein that is a component of the ubiquitin ligase E3 complex, as well as binding to MDA5 and LGP2, which are two host sensors of viral RNA. Here, we serendipitously discovered that the Hendra virus V protein undergoes a liquid-to-hydrogel phase transition and identified the V region responsible for this phenomenon. This region, referred to as PNT3 and encompassing residues 200-310, was further investigated using a combination of biophysical and structural approaches. Congo red binding assays, together with negative-staining transmisison electron microscopy (TEM) studies, show that PNT3 forms amyloid-like fibrils. Fibrillation abilities are dramatically reduced in a rationally designed PNT3 variant in which a stretch of three contiguous tyrosines, falling within an amyloidogenic motif, were replaced by three alanines. Worthy to note, Congo red staining experiments provided hints that these amyloid-like fibrils form not only in vitro but also in cellula after transfection or infection. The present results set the stage for further investigations aimed at assessing the functional role of phase separation and fibrillation by the Henipavirus V proteins.

Determination of amyloid core regions of insulin analogues fibrils

A rapid-acting insulin lispro and long-acting insulin glargine are commonly used for the treatment of diabetes. Clinical cases have described the formation of injectable amyloidosis with these insulin analogues, but their amyloid core regions of fibrils were unknown. To reveal these regions, we have analysed the hydrolyzates of insulin fibrils and its analogues using high-performance liquid chromatography and mass spectrometry methods and found that insulin and its analogues have almost identical amyloid core regions that intersect with the predicted amyloidogenic regions. The obtained results can be used to create new insulin analogues with a low ability to form fibrils.

Abbreviations

a.a., amino acid residues; HPLC-MS, high-performance liquid chromatography/mass spectrometry; m/z, mass-to-charge ratio; TEM, transmission electron microscopy.

Prion-like proteins: from computational approaches to proteome-wide analysis

Prions are self-perpetuating proteins able to switch between a soluble state and an aggregated-and-transmissible conformation. These proteinaceous entities have been widely studied in yeast, where they are involved in hereditable phenotypic adaptations. The notion that such proteins could play functional roles and be positively selected by evolution has triggered the development of computational tools to identify prion-like proteins in different kingdoms of life. These algorithms have succeeded in screening multiple proteomes, allowing the identification of prion-like proteins in a diversity of unrelated organisms, evidencing that the prion phenomenon is well conserved among species. Interestingly enough, prion-like proteins are not only connected with the formation of functional membraneless protein-nucleic acid coacervates, but are also linked to human diseases. This review addresses state-of-the-art computational approaches to identify prion-like proteins, describes proteome-wide analysis efforts, discusses these unique proteins' functional role, and illustrates recently validated examples in different domains of life.

Mechanism of Anti-Inflammatory Activity of TLR4-Interacting SPA4 Peptide

The TLR4-interacting SPA4 peptide suppresses inflammation. We assessed the structural and physicochemical properties and binding of SPA4 peptide to TLR4-MD2. We also studied the changes at the whole transcriptome level, cell morphology, viability, secreted cytokines and chemokines, and cell influx in cell systems and mouse models challenged with LPS and treated with SPA4 peptide. Our results demonstrated that the SPA4 peptide did not alter the cell viability and size and only moderately affected the transcriptome of the cells. Computational docking and rendering suggested that the SPA4 peptide intercalates with LPS-induced TLR4-MD2 complex. Results with alanine mutations of D-2 amino acid and NYTXXXRG-12-19 motif of SPA4 peptide suggested their role in binding to TLR4 and in reducing the cytokine response against LPS stimulus. Furthermore, therapeutically administered SPA4 peptide significantly suppressed the secreted levels of cytokines and chemokines in cells and bronchoalveolar lavage fluids of LPS-challenged mice. The results suggest that the SPA4 peptide intercalates with LPS-induced TLR4 complex and signaling for the suppression of inflammation.

An accelerated surface-mediated stress assay of antibody instability for developability studies

High physical stability is required for the development of monoclonal antibodies (mAbs) into successful therapeutic products. Developability assays are used to predict physical stability issues such as high viscosity and poor conformational stability, but protein aggregation remains a challenging property to predict. Among different types of stresses, air–water and solid–liquid interfaces are well known to potentially trigger protein instability and induce aggregation. Yet, in contrast to the increasing number of developability assays to evaluate bulk properties, there is still a lack of experimental methods to evaluate antibody stability against interfaces. Here, we investigate the potential of a hydrophobic nanoparticle surface-mediated stress assay to assess the stability of mAbs during the early stages of development. We evaluate this surface-mediated accelerated stability assay on a rationally designed library of 14 variants of a humanized IgG4, featuring a broad span of solubility values and other developability properties. The assay could identify variants characterized by high instability against agitation in the presence of air–water interfaces. Remarkably, for the set of investigated molecules, we observe strong correlations between the extent of aggregation induced by the surface-mediated stress assay and other developability properties of the molecules, such as aggregation upon storage at 45°C, self-association (evaluated by affinity-capture self-interaction nanoparticle spectroscopy) and nonspecific interactions (estimated by cross-interaction chromatography, stand-up monolayer chromatography (SMAC), SMAC*). This highly controlled surface-mediated stress assay has the potential to complement and increase the ability of the current set of screening techniques to assess protein aggregation and developability potential of mAbs during the early stages of drug development.

Abbreviations:AC-SINS: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy; AMS: Ammonium sulfate precipitation; ANS: 1-anilinonaphtalene-8-sulfonate; CIC: Cross-interaction chromatography; DLS: Dynamic light scattering; HIC: Hydrophobic interaction chromatography; HNSSA: Hydrophobic nanoparticles surface-stress assay; mAb: Monoclonal antibody; NP: Nanoparticle; SEC: Size exclusion chromatography; SMAC: Stand-up monolayer chromatography; WT: Wild type

Lysine245 plays a crucial role in stability and function of glycerol 3-phosphate dehydrogenase (Gpd1) in Saccharomyces cerevisiae

Glycerol 3-phosphate dehydrogenase (Gpd1 isoform) catalyzes the rate limiting step of glycerol synthesis and is a critical component of the osmo-responsive machinery in yeast. The three-dimensional structure of the enzyme is similar to the enzyme from many other organisms, including humans. A recent study with the human enzyme has proposed K120 (K152 in yeast) to be in the correct orientation for catalysis; K204 (K245 in yeast) is out of plane and is not a participant in the catalytic cycle. The current work was carried out to establish the role of K245 in the catalytic cycle of yeast Gpd1. K245A mutant was found to possess lower catalytic activity. Osmotically stressed cells expressing Gpd1 (K245A) showed no change in intracellular glycerol as compared with wild-type cells which showed ~60% increase. Fluorescence microscopy, native polyacrylamide gel electrophoresis (PAGE) analysis, fluorescence spectroscopy, and Thioflavin T spectrofluorimetry showed a relatively unstable, aggregation- and degradation-prone conformation for the mutant. In silico studies showed an aggregation "hotspot" around K245. This study establishes the requirement of K245 for conformational stability and functional adaptation of Gpd1 in Saccharomyces cerevisiae.

Energy landscapes of protein aggregation and conformation switching in intrinsically disordered proteins

The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of 'simple' protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.

Nucleobindin-2 consists of two structural components: The Zn2+-sensitive N-terminal half, consisting of nesfatin-1 and -2, and the Ca2+-sensitive C-terminal half, consisting of nesfatin-3

Nucleobindin-2 (Nucb2) is a protein that has been suggested to play roles in a variety of biological processes. Nucb2 contains two Ca2+/Mg2+-binding EF-hand domains separated by an acidic amino acid residue-rich region and a leucine zipper. All of these domains are located within the C-terminal half of the protein. At the N-terminal half, Nucb2 also possesses a putative Zn2+-binding motif. In our recent studies, we observed that Nucb2 underwent Ca2+-dependent compaction and formed a mosaic-like structure consisting of intertwined disordered and ordered regions at its C-terminal half. The aim of this study was to investigate the impact of two other potential ligands: Mg2+, which possesses chemical properties similar to those of Ca2+, and Zn2+, for which a putative binding motif was identified. In this study, we demonstrated that the binding of Mg2+ led to oligomerization state changes with no significant secondary or tertiary structural alterations of Nucb2. In contrast, Zn2+ binding had a more pronounced effect on the structure of Nucb2, leading to the local destabilization of its N-terminal half while also inducing changes within its C-terminal half. These structural rearrangements resulted in the oligomerization and/or aggregation of Nucb2 molecules. Taken together, the results of our previous and current research help to elucidate the structure of the Nucb2, which can be divided into two parts: the Zn2+-sensitive N-terminal half (consisting of nesfatin-1 and -2) and the Ca2+-sensitive C-terminal half (consisting of nesfatin-3). These results may also help to open a new discussion regarding the diverse roles that metal cations play in regulating the structure of Nucb2 and the various physiological functions of this protein.

Multiscale pharmacokinetic modeling of systemic exposure of subcutaneously injected biotherapeutics

Subcutaneously injected formulations have been developed for many biological products including monoclonal antibodies (mAbs). A knowledge gap nonetheless remains regarding the absorption and catabolism mechanisms and kinetics of a large molecule at the administration site. A multiscale pharmacokinetic (PK) model was thus developed by coupling multiphysics simulations of subcutaneous (SC) absorption kinetics with whole-body pharmacokinetic (PK) modeling, bridged by consideration of the presystemic clearance by the initial lymph. Our local absorption simulation of SC-injected albumin enabled the estimation of its presystemic clearance and led to the whole-body PK modeling of systemic exposure. The local absorption rate of albumin was found to be influential on the PK profile. Additionally, nineteen mAbs were explored via this multiscale simulation and modeling framework. The computational results suggest that stability propensities of the mAbs are correlated with the presystemic clearance, and electrostatic charges in the complementarity-determining region influence the local absorption rate. Still, this study underscores a critical need to experimentally determine various biophysical characteristics of a large molecule and the biomechanical properties of human skin tissues.

The Interplay Between Disordered Regions in RNAs and Proteins Modulates Interactions Within Stress Granules and Processing Bodies

Condensation, or liquid-like phase separation, is a phenomenon indispensable for the spatiotemporal regulation of molecules within the cell. Recent studies indicate that the composition and molecular organization of phase-separated organelles such as Stress Granules (SGs) and Processing Bodies (PBs) are highly variable and dynamic. A dense contact network involving both RNAs and proteins controls the formation of SGs and PBs and an intricate molecular architecture, at present poorly understood, guarantees that these assemblies sense and adapt to different stresses and environmental changes. Here, we investigated the physico-chemical properties of SGs and PBs components and studied the architecture of their interaction networks. We found that proteins and RNAs establishing the largest amount of contacts in SGs and PBs have distinct properties and intrinsic disorder is enriched in all protein-RNA, protein-protein and RNA-RNA interaction networks. The increase of disorder in proteins is accompanied by an enrichment in single-stranded regions of RNA binding partners. Our results suggest that SGs and PBs quickly assemble and disassemble through dynamic contacts modulated by unfolded domains of their components.

Characterization of a Stable Form of Carboxypeptidase G2 (Glucarpidase), a Potential Biobetter Variant, From Acinetobacter sp. 263903-1

Carboxypeptidase G2 (CPG2) is a bacterial enzyme widely used to detoxify methotrexate (MTX) and in enzyme/prodrug therapy for cancer treatment. However, several drawbacks, such as instability, have limited its efficiency. Herein, we have evaluated the properties of a putative CPG2 from Acinetobacter sp. 263903-1 (AcCPG2). AcCPG2 is compared with a CPG2 derived from Pseudomonas sp. strain RS-16 (PsCPG2), available as an FDA-approved medication called glucarpidase. After modeling AcCPG2 using the I-TASSER program, the refined model was validated by PROCHECK, VERIFY 3D and according to the Z score of the model. Using computational analyses, AcCPG2 displayed higher thermodynamic stability and a lower aggregation propensity than PsCPG2. AcCPG2 showed an optimum pH of 7.5 against MTX and was stable over a pH range of 5-10. AcCPG2 exhibited optimum activity at 50 °C and higher thermal stability at a temperature range of 20-70 °C compared to PsCPG2. The K_m value of the purified AcCPG2 toward folate and MTX was 31.36 µM and 44.99 µM, respectively. The V_max value of AcCPG2 for folate and MTX was 125.80 µmol/min/mg and 48.90  µmol/min/mg, respectively. Accordingly, thermostability and pH versatility makes AcCPG2 a potential biobetter variant for therapeutic applications.

The intrinsic amyloidogenic propensity of cofilin-1 is aggravated by Cys-80 oxidation: A possible link with neurodegenerative diseases

Cofilin-1, an actin dynamizing protein, forms actin-cofilin rods, which is one of the major events that exacerbates the pathophysiology of amyloidogenic diseases. Cysteine oxidation in cofilin-1 under oxidative stress plays a crucial role in the formation of these rods. Others and we have reported that cofilin-1 possesses a self-oligomerization property in vitro and in vivo under physiological conditions. However, it remains elusive if cofilin-1 itself forms amyloid-like structures. We, therefore, hypothesized that cofilin-1 might form amyloid-like assemblies, with a potential to intensify the pathophysiology of amyloid-linked diseases. We used various in silico and in vitro techniques and examined the amyloid-forming propensity of cofilin-1. The study confirms that cofilin-1 possesses an intrinsic tendency of aggregation and forms amyloid-like structures in vitro. Further, we studied the effect of cysteine oxidation on the stability and structural features of cofilin-1. Our data show that oxidation at Cys-80 renders cofilin-1 unstable, leading to a partial loss of protein structure. The results substantiate our hypothesis and establish a strong possibility that cofilin-1 aggregation might play a role in cofilin-mediated pathology and the progression of several amyloid-linked diseases.

Identification of Amyloidogenic Regions in Pseudomonas aeruginosa Ribosomal S1 Protein

Bacterial S1 protein is a functionally important ribosomal protein. It is a part of the 30S ribosomal subunit and is also able to interact with mRNA and tmRNA. An important feature of the S1 protein family is a strong tendency towards aggregation. To study the amyloidogenic properties of S1, we isolated and purified the recombinant ribosomal S1 protein of Pseudomonas aeruginosa. Using the FoldAmyloid, Waltz, Pasta 2.0, and AGGRESCAN programs, amyloidogenic regions of the protein were predicted, which play a key role in its aggregation. The method of limited proteolysis in combination with high performance liquid chromatography and mass spectrometric analysis of the products, made it possible to identify regions of the S1 protein from P. aeruginosa that are protected from the action of proteinase K, trypsin, and chymotrypsin. Sequences of theoretically predicted and experimentally identified amyloidogenic regions were used to synthesize four peptides, three of which demonstrated the ability to form amyloid-like fibrils, as shown by electron microscopy and fluorescence spectroscopy. The identified amyloidogenic sites can further serve as a basis for the development of new antibacterial peptides against the pathogenic microorganism P. aeruginosa.

Exploring the sequence features determining amyloidosis in human antibody light chains

The light chain (AL) amyloidosis is caused by the aggregation of light chain of antibodies into amyloid fibrils. There are plenty of computational resources available for the prediction of short aggregation-prone regions within proteins. However, it is still a challenging task to predict the amyloidogenic nature of the whole protein using sequence/structure information. In the case of antibody light chains, common architecture and known binding sites can provide vital information for the prediction of amyloidogenicity at physiological conditions. Here, in this work, we have compared classical sequence-based, aggregation-related features (such as hydrophobicity, presence of gatekeeper residues, disorderness, β-propensity, etc.) calculated for the CDR, FR or V_L regions of amyloidogenic and non-amyloidogenic antibody light chains and implemented the insights gained in a machine learning-based webserver called "V_LAmY-Pred" ( https://web.iitm.ac.in/bioinfo2/vlamy-pred/ ). The model shows prediction accuracy of 79.7% (sensitivity: 78.7% and specificity: 79.9%) with a ROC value of 0.88 on a dataset of 1828 variable region sequences of the antibody light chains. This model will be helpful towards improved prognosis for patients that may likely suffer from diseases caused by light chain amyloidosis, understanding origins of aggregation in antibody-based biotherapeutics, large-scale in-silico analysis of antibody sequences generated by next generation sequencing, and finally towards rational engineering of aggregation resistant antibodies.

Evaluation of in silico tools for the prediction of protein and peptide aggregation on diverse datasets

Several prediction algorithms and tools have been developed in the last two decades to predict protein and peptide aggregation. These in silico tools aid to predict the aggregation propensity and amyloidogenicity as well as the identification of aggregation-prone regions. Despite the immense interest in the field, it is of prime importance to systematically compare these algorithms for their performance. In this review, we have provided a rigorous performance analysis of nine prediction tools using a variety of assessments. The assessments were carried out on several non-redundant datasets ranging from hexapeptides to protein sequences as well as amyloidogenic antibody light chains to soluble protein sequences. Our analysis reveals the robustness of the current prediction tools and the scope for improvement in their predictive performances. Insights gained from this work provide critical guidance to the scientific community on advantages and limitations of different aggregation prediction methods and make informed decisions about their research needs.

Computational Methods and Tools in Antimicrobial Peptide Research

The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that has increased the number of diseases and infections that risk going untreated. There is an urgent need to develop alternative strategies and treatments to address this issue. One class of molecules that is attracting significant interest is that of antimicrobial peptides (AMPs). Their design and development has been aided considerably by the applications of molecular models, and we review these here. These methods include the use of tools to explore the relationships between their structures, dynamics, and functions and the increasing application of machine learning and molecular dynamics simulations. This review compiles resources such as AMP databases, AMP-related web servers, and commonly used techniques, together aimed at aiding researchers in the area toward complementing experimental studies with computational approaches.

[Antibacterial effects of peptides synthesized based on the sequence of ribosome protein S1]

Antibiotic resistance of bacteria is a topical problem on a global scale. Sometimes vigorous human activity leads to an increase in the number of bacteria carrying resistance genes in the environment. Antimicrobial peptides (AMPs) and similar compounds are potential candidates for combating antibiotic-resistant bacteria. Previously, we proposed and successfully tested on Thermus thermophilus a new mechanism of AMP action. This mechanism of directed coaggregation is based on the interaction of a peptide capable of forming fibrils with a target protein. In this work, we discuss the criteria for choosing a target for the targeted action of AMP, describe the features of the "parental" S1 ribosomal proteins T. thermophilus and Escherichia coli and the studied peptides using bioinformatic analysis methods, assess the antimicrobial effect of the synthesized peptides on a model organism of E. coli and cytotoxicity on cells of human fibroblasts. The obtained results will be important for the creation of new AMPs for pathogenic organisms.

Investigating the Disordered and Membrane-Active Peptide A-Cage-C Using Conformational Ensembles

The driving forces and conformational pathways leading to amphitropic protein-membrane binding and in some cases also to protein misfolding and aggregation is the subject of intensive research. In this study, a chimeric polypeptide, A-Cage-C, derived from α-Lactalbumin is investigated with the aim of elucidating conformational changes promoting interaction with bilayers. From previous studies, it is known that A-Cage-C causes membrane leakages associated with the sporadic formation of amorphous aggregates on solid-supported bilayers. Here we express and purify double-labelled A-Cage-C and prepare partially deuterated bicelles as a membrane mimicking system. We investigate A-Cage-C in the presence and absence of these bicelles at non-binding (pH 7.0) and binding (pH 4.5) conditions. Using in silico analyses, NMR, conformational clustering, and Molecular Dynamics, we provide tentative insights into the conformations of bound and unbound A-Cage-C. The conformation of each state is dynamic and samples a large amount of overlapping conformational space. We identify one of the clusters as likely representing the binding conformation and conclude tentatively that the unfolding around the central W23 segment and its reorientation may be necessary for full intercalation at binding conditions (pH 4.5). We also see evidence for an overall elongation of A-Cage-C in the presence of model bilayers.

Cellular Chaperone Function of Intrinsically Disordered Dehydrin ERD14

Disordered plant chaperones play key roles in helping plants survive in harsh conditions, and they are indispensable for seeds to remain viable. Aside from well-known and thoroughly characterized globular chaperone proteins, there are a number of intrinsically disordered proteins (IDPs) that can also serve as highly effective protecting agents in the cells. One of the largest groups of disordered chaperones is the group of dehydrins, proteins that are expressed at high levels under different abiotic stress conditions, such as drought, high temperature, or osmotic stress. Dehydrins are characterized by the presence of different conserved sequence motifs that also serve as the basis for their categorization. Despite their accepted importance, the exact role and relevance of the conserved regions have not yet been formally addressed. Here, we explored the involvement of each conserved segment in the protective function of the intrinsically disordered stress protein (IDSP) A. thaliana's Early Response to Dehydration (ERD14). We show that segments that are directly involved in partner binding, and others that are not, are equally necessary for proper function and that cellular protection emerges from the balanced interplay of different regions of ERD14.

AbsoluRATE: An in-silico method to predict the aggregation kinetics of native proteins

Protein aggregation has two aspects, namely, mechanistic and kinetics. Understanding protein aggregation kinetics is critical for prediction of progression of diseases caused by amyloidosis, accumulation of aggregates in biotherapeutics during storage and engineering commercial nano-biomaterials. In this work, we have collected experimentally determined absolute protein aggregation rates and developed an SVM based regression model to predict absolute rates of protein and peptide aggregation near-physiological conditions. The regression model achieved a correlation coefficient of 0.72 with MAE of 0.91 (natural log of k_app, where k_app is in hour^-1) using leave-one-out cross-validation on a dataset of 82 non-redundant proteins/peptides. The model accounts for the experimental conditions (such as temperature, pH, ionic and protein concentration) and sequence-based properties. The amino acid sequence features revealed by this model as being important for aggregation kinetics, are also associated with the aggregation mechanism. In particular, inherent aggregation propensity of the protein/peptide sequence and number of aggregation prone regions (APRs) unpunctuated by the gatekeeping residues, were found to play important roles in the prediction of the absolute aggregation rates. This analysis shows that mechanism and kinetics of protein aggregation are coupled via common sequence attributes. The aggregation kinetic prediction method developed in this work is available at https://web.iitm.ac.in/bioinfo2/absolurate-pred/index.html.

Challenges for design of aggregation-resistant variants of granulocyte colony-stimulating factor

Non-native protein aggregation is a long-standing issue in pharmaceutical biotechnology. A rational design approach was used in order to identify variants of recombinant human granulocyte colony-stimulating factor (rhG-CSF) with lower aggregation propensity at solution conditions that are typical of commercial formulation. The approach used aggregation-prone-region (APR) predictors to select single amino acid substitutions that were predicted to decrease intrinsic aggregation propensity (IAP). The results of static light scattering temperature-ramps and chemical unfolding experiments demonstrated that none of the selected variants exhibited improved aggregation resistance, and the apparent conformational stability of each variant was lower than that of WT. Aggregation studies under partly denaturing conditions suggested that the IAP of at least one variant remained unaltered. Overall, this study highlights a general challenge in designing aggregation resistance for proteins, due to the need to accurately predict both APRs and conformational stability.

Bacterial Protein Homeostasis Disruption as a Therapeutic Intervention

Cells have evolved a complex molecular network, collectively called the protein homeostasis (proteostasis) network, to produce and maintain proteins in the appropriate conformation, concentration and subcellular localization. Loss of proteostasis leads to a reduction in cell viability, which occurs to some degree during healthy ageing, but is also the root cause of a group of diverse human pathologies. The accumulation of proteins in aberrant conformations and their aggregation into specific beta-rich assemblies are particularly detrimental to cell viability and challenging to the protein homeostasis network. This is especially true for bacteria; it can be argued that the need to adapt to their changing environments and their high protein turnover rates render bacteria particularly vulnerable to the disruption of protein homeostasis in general, as well as protein misfolding and aggregation. Targeting bacterial proteostasis could therefore be an attractive strategy for the development of novel antibacterial therapeutics. This review highlights advances with an antibacterial strategy that is based on deliberately inducing aggregation of target proteins in bacterial cells aiming to induce a lethal collapse of protein homeostasis. The approach exploits the intrinsic aggregation propensity of regions residing in the hydrophobic core regions of the polypeptide sequence of proteins, which are genetically conserved because of their essential role in protein folding and stability. Moreover, the molecules were designed to target multiple proteins, to slow down the build-up of resistance. Although more research is required, results thus far allow the hope that this strategy may one day contribute to the arsenal to combat multidrug-resistant bacterial infections.

β-Defensin from the Asian Sea Bass, Lates calcarifer: Molecular Prediction and Phylogenetic Analysis

Antimicrobial peptides (AMPs) are an important element of the innate immune system of all living organisms and serve as a barrier that safeguards the organisms against a wide range of pathogens. Fishes are proven to be a prospective source of AMPs, and β-defensins form an important family of AMPs with potent antimicrobial, chemotactic and immunomodulatory activities. The present study reports a β-defensin AMP sequence (Lc-BD) from the Asian sea bass, Lates calcarifer, a commercially important fish species in tropical and subtropical regions of Asia and the Pacific. A 202-bp cDNA fragment with an open reading frame encoding 63 amino acids (aa) was obtained from the mRNA of gill tissue by RT-PCR. The deduced aa sequence of Lc-BD possessed a signal and a mature peptide region with 20 and 43 aa residues, respectively. Lc-BD was characterized at the molecular level, and a molecular weight of 5.24 kDa and a net charge of +4.5 was predicted for the mature peptide. The molecular characterization of Lc-BD revealed the presence of three intramolecular disulphide bonds involving the six conserved cysteine residues in the sequence, and the phylogenetic analysis of Lc-BD showed a close relationship with β-defensins from fishes like Siniperca chuatsi, Argyrosomus regius, Trachinotus ovatus and Oplegnathus fasciatus.

Structural effects driven by rare point mutations in amylin hormone, the type II diabetes-associated peptide

BACKGROUND

Amylin is a 37-amino-acid peptide hormone co-secreted with insulin, which participates in glucose homeostasis. This hormone is able to aggregate in a β-sheet conformation and deposit in islet amyloids, a hallmark in type II diabetes. Since amylin is a gene-encoded hormone, this peptide has variants caused by point mutations that can impact its functions.

METHODS

Here, we analyzed the structural effects caused by S20G and G33R point mutations which, according to the 1000 Genomes Project, have frequency in East Asian and European populations, respectively. The analyses were performed by means of aggrescan server, SNP functional effect predictors, and molecular dynamics.

RESULTS

We found that both mutations have aggregation potential and cause changes in the monomeric forms when compared with wild-type amylin. Furthermore, comparative analyses with pramlintide, an amylin drug analogue, allowed us to infer that second α-helix maintenance may be related to the aggregation potential.

CONCLUSIONS

The S20G mutation has been described as pathologically related, which is in agreement with our findings. In addition, our data suggest that the G33R mutation might have a deleterious effect. The data presented here also provide new therapy opportunities, whether for creating more effective drugs for diabetes or implementing specific treatment for patients with these mutations.

GENERAL SIGNIFICANCE

Our data could help to better understand the impact of mutations on the wild-type amylin sequence, as a starting point for the evaluation and characterization of other variations. Moreover, these findings could improve the health of patients with type II diabetes.

Optimized expression and purification of a soluble BMP2 variant based on in-silico design

Bone morphogenetic protein 2 (BMP2¹) is a highly interesting therapeutic growth factor due to its strong osteogenic/osteoinductive potential. However, its pronounced aggregation tendency renders recombinant and soluble production troublesome and complex. While prokaryotic expression systems can provide BMP2 in large amounts, the typically insoluble protein requires complex denaturation-renaturation procedures with medically hazardous reagents to obtain natively folded homodimeric BMP2. Based on a detailed aggregation analysis of wildtype BMP2, we designed a hydrophilic variant of BMP2 additionally containing an improved heparin binding site (BMP2-2Hep-7M). Consecutive optimization of BMP2-2Hep-7M expression and purification enabled production of soluble dimeric BMP2-2Hep-7M in high yield in E. coli. This was achieved by a) increasing protein hydrophilicity via introducing seven point mutations within aggregation hot spots of wildtype BMP2 and a longer N-terminus resulting in higher affinity for heparin, b) by employing E. coli strain SHuffle® T7, which enables the structurally essential disulfide-bond formation in BMP2 in the cytoplasm, c) by using BMP2 variant characteristic soluble expression conditions and application of l-arginine as solubility enhancer. The BMP2 variant BMP2-2Hep-7M shows strongly attenuated although not completely eliminated aggregation tendency.

Utilizing Red Spotted Apollo Butterfly Transcriptome to Identify Antimicrobial Peptide Candidates against Porphyromonas gingivalis

Classical antibiotics are the foremost treatment strategy against microbial infections. Overuse of this has led to the evolution of antimicrobial resistance. Antimicrobial peptides (AMPs) are natural defense elements present across many species including humans, insects, bacteria, and plants. Insect AMPs are our area of interest, because of their stronger abilities in host defense. We have deciphered AMPs from an endangered species Parnassius bremeri, commonly known as the red spotted apollo butterfly. It belongs to the second largest insect order Lepidoptera, comprised of butterflies and moths, and lives in the high altitudes of Russia, China, and Korea. We aimed at identifying the AMPs from the larvae stages. The rationale of choosing this stage is that the P. bremeri larvae development occurs at extremely low temperature conditions, which might serve as external stimuli for AMP production. RNA was isolated from larvae (L1 to L5) instar stages and subjected to next generation sequencing. The transcriptomes obtained were curated in in-silico pipelines. The peptides obtained were screened for requisite AMP physicochemical properties and in vitro antimicrobial activity. With the sequential screening and validation, we obtained fifteen candidate AMPs. One peptide TPS-032 showed promising antimicrobial activity against Porphyromonas gingivalis, a primary causative organism of periodontitis.