aSynPEP-DB: a database of biogenic peptides for inhibiting α-synuclein aggregation

In silico screening of peptide inhibitors targeting α-synuclein for Parkinson's disease

Parkinson's disease affects cognitive, motor, and autonomic functions due to nervous system degeneration. Though no cure exists, medications and therapies can help alleviate symptoms, but their effectiveness diminishes as the disease progresses, ultimately increasing the need for alternative treatments. α-Synuclein has long been one of the main targets in addressing Parkinson's through drug design studies, but no drugs are yet approved against α-Synuclein aggregation. Therefore, this study aims to develop potential inhibitors of fibrillization by screening thousands of peptides in terms of their binding abilities via Molecular Docking and Molecular Dynamics simulations. Our results show that peptides with Lysine and Arginine at terminal groups result in higher binding affinities to the C-terminal domain. Among the heptapeptides examined, RWRRKRL shows the highest binding free energy to the protein while KKRHKWR exhibits superior stabilizing effect, interacting with both N- and C-terminal regions of α-Synuclein. The inhibitory potential of peptides on the fibrillar structure of protein varies with concentration, and RWRRKRL at 1:3 protein-peptide monomer ratio shows promise as an inhibitor by reducing the internal H-bonds of the protein and increasing RMSD values. These results reveal that short-chain peptides can be designed against α-Synuclein oligomerization offering a potential therapeutic approach for preventing Parkinson's.

Green tea polyphenol EGCG acts differentially on end-stage amyloid polymorphs of α-synuclein formed in different polyol osmolytes

Synucleinopathies are heterogenous group of disorders characterized by α-synuclein amyloid aggregates in the nervous system. Different synucleinopathy clinical subtypes are encoded by structurally diverse α-synuclein amyloid polymorphs referred to as 'strains'. The underlying structural differences between polymorphs can potentially hamper the drug design against synucleinopathies. Polyphenolic compounds like EGCG have shown promise in inhibiting and remodeling of α-synuclein amyloid aggregates, but their effects on different polymorphs are not well-studied. The cellular environment is one factor contributing to the heterogeneity in the amyloid landscape. Herein, we generated diverse polymorphs of α-synuclein by fine-tuning its aggregation using different polyol osmolytes, varying in their physicochemical properties. These osmolytes act as globular protein stabilizers and conformational modulators of intrinsically disordered proteins. While the buffer control α-synuclein aggregates were evenly dispersed, the polyol-induced aggregate solutions contained a heterogeneous mixture of co-existing polymorphs, as evidenced by AFM and TEM measurements. The polyol-induced aggregated solutions consisted of a mixture of both fibrillar and nonfibrillar cross-β-rich species. Using various spectroscopic tools, we observed differences in the structures of osmolyte-induced polymorphic aggregates. We incubated these aggregates with EGCG and observed its disparate action over polymorphs wherein the treated species were either disintegrated or structurally altered. Contrary to previous reports, all EGCG-treated polymorphs were β-sheet-rich and seeding-competent. Our findings are relevant in assessing the efficacy of polyphenolic compounds on diverse aggregate strains encoding different proteinopathy variants. The formation of β-sheet-rich species in our study also engenders a more critical examination of EGCG's mode of action on diverse classes of amyloids.

Structural information in therapeutic peptides: Emerging applications in biomedicine

Peptides are attracting a growing interest as therapeutic agents. This trend stems from their cost-effectiveness and reduced immunogenicity, compared to antibodies or recombinant proteins, but also from their ability to dock and interfere with large protein-protein interaction surfaces, and their higher specificity and better biocompatibility relative to organic molecules. Many tools have been developed to understand, predict, and engineer peptide function. However, most state-of-the-art approaches treat peptides only as linear entities and disregard their structural arrangement. Yet, structural details are critical for peptide properties such as solubility, stability, or binding affinities. Recent advances in peptide structure prediction have successfully addressed the scarcity of confidently determined peptide structures. This review will explore different therapeutic and biotechnological applications of peptides and their assemblies, emphasizing the importance of integrating structural information to advance these endeavors effectively.

The role of amphipathic and cationic helical peptides in Parkinson's disease

Peptides are attracting a growing interest for therapeutic applications in biomedicine. In Parkinson's disease (PD), different human endogenous peptides have been associated with beneficial effects, including protein aggregation inhibition, reduced inflammation, or the protection of dopaminergic neurons. Such effects seem to be connected to the spatial arrangement of peptide side chains, and many of these human molecules share common conformational traits, displaying a distinctive amphipathic and cationic helical structure, which is believed to be crucial for their activities. This review delves into the relationship between these structural properties and the current evidence connecting biogenic peptides to the amelioration of PD symptoms. We discuss their implications in the disease, the different mechanisms of action, their state of validation, and their therapeutic potential.

Aggregating amyloid resources: A comprehensive review of databases on amyloid-like aggregation

Protein aggregation is responsible for several degenerative conditions in humans, and it is also a bottleneck in industrial protein production and storage of biotherapeutics. Bioinformatics tools have been developed to predict and redesign protein solubility more efficiently by understanding the underlying principles behind aggregation. As more experimental data become available, dedicated resources for storing, indexing, classifying and consolidating experimental results have emerged. These resources vary in focus, including aggregation-prone regions, 3D patches or protein stretches capable of forming amyloid fibrils. Some of these resources also consider the experimental conditions that cause protein aggregation and how they affect the process. This review article explores how protein aggregation databases have evolved and surveys state-of-the-art resources. We highlight their applications, complementarity and existing limitations. Moreover, we showcase the existing symbiosis between amyloid-related databases and predictive tools. To increase the usefulness of our review, we supplement it with a comprehensive list of present and past amyloid databases: https://biogenies.info/amyloid-database-list/.