TANGO-Inspired Design of Anti-Amyloid Cyclic Peptides

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.

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

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

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

Proteolytically Stable Diaza-Peptide Foldamers Mimic Helical Hot Spots of Protein-Protein Interactions and Act as Natural Chaperones

A novel class of peptidomimetic foldamers based on diaza-peptide units are reported. Circular dichroism, attenuated total reflection -Fourier transform infrared, NMR, and molecular dynamics studies demonstrate that unlike the natural parent nonapeptide, the specific incorporation of one diaza-peptide unit at the N-terminus allows helical folding in water, which is further reinforced by the introduction of a second unit at the C-terminus. The ability of these foldamers to resist proteolysis, to mimic the small helical hot spot of transthyretin-amyloid β (Aβ) cross-interaction, and to decrease pathological Aβ aggregation demonstrates that the introduction of diaza-peptide units is a valid approach for designing mimics or inhibitors of protein-protein interaction and other therapeutic peptidomimetics. This study also reveals that small peptide foldamers can play the same role as physiological chaperone proteins and opens a new way to design inhibitors of amyloid protein aggregation, a hallmark of more than 20 serious human diseases such as Alzheimer's disease.

DES-Amyloidoses “Amyloidoses through the looking-glass”: A knowledgebase developed for exploring and linking information related to human amyloid-related diseases

More than 30 types of amyloids are linked to close to 50 diseases in humans, the most prominent being Alzheimer’s disease (AD). AD is brain-related local amyloidosis, while another amyloidosis, such as AA amyloidosis, tends to be more systemic. Therefore, we need to know more about the biological entities’ influencing these amyloidosis processes. However, there is currently no support system developed specifically to handle this extraordinarily complex and demanding task. To acquire a systematic view of amyloidosis and how this may be relevant to the brain and other organs, we needed a means to explore "amyloid network systems" that may underly processes that leads to an amyloid-related disease. In this regard, we developed the DES-Amyloidoses knowledgebase (KB) to obtain fast and relevant information regarding the biological network related to amyloid proteins/peptides and amyloid-related diseases. This KB contains information obtained through text and data mining of available scientific literature and other public repositories. The information compiled into the DES-Amyloidoses system based on 19 topic-specific dictionaries resulted in 796,409 associations between terms from these dictionaries. Users can explore this information through various options, including enriched concepts, enriched pairs, and semantic similarity. We show the usefulness of the KB using an example focused on inflammasome-amyloid associations. To our knowledge, this is the only KB dedicated to human amyloid-related diseases derived primarily through literature text mining and complemented by data mining that provides a novel way of exploring information relevant to amyloidoses.

Polyglutamine spinocerebellar ataxias: emerging therapeutic targets

INTRODUCTION

Six of the most frequent dominantly inherited spinocerebellar ataxias (SCAs) worldwide - SCA1, SCA2, SCA3, SCA6, SCA7, and SCA17 - are caused by an expansion of a polyglutamine (polyQ) tract in the corresponding proteins. While the identification of the causative mutation has advanced knowledge on the pathogenesis of polyQ SCAs, effective therapeutics able to mitigate the severe clinical manifestation of these highly incapacitating disorders are not yet available.

AREAS COVERED

This review provides a comprehensive and critical perspective on well-established and emerging therapeutic targets for polyQ SCAs; it aims to inspire prospective drug discovery efforts.

EXPERT OPINION

The landscape of polyQ SCAs therapeutic targets and strategies includes (1) the mutant genes and proteins themselves, (2) enhancement of endogenous protein quality control responses, (3) abnormal protein-protein interactions of the mutant proteins, (4) disturbed neuronal function, (5) mitochondrial function, energy availability and oxidative stress, and (6) glial dysfunction, growth factor or hormone imbalances. Challenges include gaining a clearer definition of therapeutic targets for the drugs in clinical development, the discovery of novel drug-like molecules for challenging key targets, and the attainment of a stronger translation of preclinical findings to the clinic.

The Positive Side of the Alzheimer's Disease Amyloid Cross-Interactions: The Case of the Aβ 1-42 Peptide with Tau, TTR, CysC, and ApoA1

Alzheimer's disease (AD) represents a progressive amyloidogenic disorder whose advancement is widely recognized to be connected to amyloid-β peptides and Tau aggregation. However, several other processes likely contribute to the development of AD and some of them might be related to protein-protein interactions. Amyloid aggregates usually contain not only single type of amyloid protein, but also other type of proteins and this phenomenon can be rationally explained by the process of protein cross-seeding and co-assembly. Amyloid cross-interaction is ubiquitous in amyloid fibril formation and so a better knowledge of the amyloid interactome could help to further understand the mechanisms of amyloid related diseases. In this review, we discuss about the cross-interactions of amyloid-β peptides, and in particular Aβ1-42, with other amyloids, which have been presented either as integrated part of Aβ neurotoxicity process (such as Tau) or conversely with a preventive role in AD pathogenesis by directly binding to Aβ (such as transthyretin, cystatin C and apolipoprotein A1). Particularly, we will focus on all the possible therapeutic strategies aiming to rescue the Aβ toxicity by taking inspiration from these protein-protein interactions.

Peptide-Based Molecular Strategies To Interfere with Protein Misfolding, Aggregation, and Cell Degeneration

Protein misfolding into amyloid fibrils is linked to more than 40 as yet incurable cell- and neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and type 2 diabetes. So far, however, only one of the numerous anti-amyloid molecules has reached patients. This Minireview gives an overview of molecular strategies and peptide chemistry "tools" to design, develop, and discover peptide-based molecules as anti-amyloid drug candidates. We focus on two major inhibitor rational design strategies: 1) the oldest and most common strategy, based on molecular recognition elements of amyloid self-assembly, and 2) a more recent approach, based on cross-amyloid interactions. We discuss why peptide-based amyloid inhibitors, in particular their advanced generations, can be promising leads or candidates for anti-amyloid drugs as well as valuable tools for deciphering amyloid-mediated cell damage and its link to disease pathogenesis.

ROSETTA-informed design of structurally stabilized cyclic anti-amyloid peptides

β-amyloid oligomers are thought to be the most toxic species formed en route to fibril deposition in Alzheimer's disease. Transthyretin is a natural sequestering agent of β-amyloid oligomers: the binding site to β-amyloid has been traced to strands G/H of the inner β-sheet of transthyretin. A linear peptide, with the same primary sequence as the β-amyloid binding domain on transthyretin, was moderately effective at inhibiting β-amyloid fibril growth. Insertion of a β-turn template and cyclization greatly increased stability against proteolysis and improved efficacy as an amyloid inhibitor. However, the cyclic peptide still contained a significant amount of disorder. Using the Simple Cyclic Peptide Application within ROSETTA as an in silico predictor of cyclic peptide conformation and stability, we investigated putative structural enhancements, including stabilization by disulfide linkages and insertion of a second β-turn template. Several candidates were synthesized and tested for secondary structure and ability to inhibit β-amyloid aggregation. The results demonstrate that cyclization, β-sheet structure and conformational homogeneity are all preferable design features, whereas disulfide bond formation across the two β-strands is not preferable.

Inhibition of amyloid beta fibril formation by monomeric human transthyretin

Transthyretin (TTR) is a homotetrameric protein that is found in the plasma and cerebrospinal fluid. Dissociation of TTR tetramers sets off a downhill cascade of amyloid formation through polymerization of monomeric TTR. Interestingly, TTR has an additional, biologically relevant activity, which pertains to its ability to slow the progression of amyloid beta (Aβ) associated pathology in transgenic mice. In vitro, both TTR and a kinetically stable variant of monomeric TTR (M-TTR) inhibit the fibril formation of Aβ1-40/42 molecules. Published evidence suggests that tetrameric TTR binds preferentially to Aβ monomers, thus destabilizing fibril formation by depleting the pool of Aβ monomers from aggregating mixtures. Here, we investigate the effects of M-TTR on the in vitro aggregation of Aβ1-42 . Our data confirm previous observations that fibril formation of Aβ is suppressed in the presence of sub-stoichiometric amounts of M-TTR. Despite this, we find that sub-stoichiometric levels of M-TTR are not bona fide inhibitors of aggregation. Instead, they co-aggregate with Aβ to promote the formation of large, micron-scale insoluble, non-fibrillar amorphous deposits. Based on fluorescence correlation spectroscopy measurements, we find that M-TTR does not interact with monomeric Aβ. Two-color coincidence analysis of the fluorescence bursts of Aβ and M-TTR labeled with different fluorophores shows that M-TTR co-assembles with soluble Aβ aggregates and this appears to drive the co-aggregation into amorphous precipitates. Our results suggest that mimicking the co-aggregation activity with protein-based therapeutics might be a worthwhile strategy for rerouting amyloid beta peptides into inert, insoluble, and amorphous deposits.

Transthyretin Mimetics as Anti-β-Amyloid Agents: A Comparison of Peptide and Protein Approaches

β-Amyloid (Aβ) aggregation is causally linked to neuronal pathology in Alzheimer's disease; therefore, several small molecules, antibodies, and peptides have been tested as anti-Aβ agents. We developed two compounds based on the Aβ-binding domain of transthyretin (TTR): a cyclic peptide cG8 and an engineered protein mTTR, and compared them for therapeutically relevant properties. Both mTTR and cG8 inhibit fibrillogenesis of Aβ, with mTTR inhibiting at a lower concentration than cG8. Both inhibit aggregation of amylin but not of α-synuclein. They both bind more Aβ aggregates than monomer, and neither disaggregates preformed fibrils. cG8 retained more of its activity in the presence of biological materials and was more resistant to proteolysis than mTTR. We examined the effect of mTTR or cG8 on Aβ binding to human neurons. When mTTR was co-incubated with Aβ under oligomer-forming conditions, Aβ morphology was drastically changed and Aβ-cell deposition significantly decreased. In contrast, cG8 did not affect morphology but decreased the amount of Aβ deposited. These results provide guidance for further evolution of TTR-mimetic anti-amyloid agents.

Inhibition and Degradation of Amyloid Beta (Aβ40) Fibrillation by Designed Small Peptide: A Combined Spectroscopy, Microscopy, and Cell Toxicity Study

A designed nontoxic, nonhemolytic 11-residue peptide, NF11 (NAVRWSLMRPF), not only inhibits the aggregation of amyloid beta (Aβ40) protein but also disaggregates the preformed oligomers and mature Aβ fibrils, thereby reducing associated-toxicity. NMR experiments provide evidence of NF11's ability to inhibit fibril formation, primarily through interaction with the N-terminus region as well as the central hydrophobic cluster of Aβ40. NF11 has micromolar binding affinity toward both monomeric and aggregated species for efficient clearance of toxic aggregates. From these in vitro results, the future development of a next generation peptidomimetic therapeutic agent for amyloid disease may be possible.