aSynPep is a complementary tool to aSynPEP-DB for screening candidate peptides with potentital to bind and inhibit the aggregation of alpha-synuclein.

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aSynPEP complementary server tool


α-Synuclein aggregation is a key driver of neurodegeneration in Parkinson’s disease and related syndromes. Accordingly, obtaining a molecule that targets α-synuclein toxic assemblies with high affinity is a long-pursued objective. We exploited the biophysical properties of toxic oligomers and amyloid fibrils to identify a family of α-helical peptides that bind to these α-synuclein species with low nanomolar affinity, without interfering with the monomeric functional protein. We identified amphipaticyty, alpha-helical content and positive net charge as three key properties that these peptides share. This activity is translated into a high anti-aggregation potency and the ability to abrogate oligomer-induced cell damage. Using a structure-guided search we identified a human peptide expressed in the brain and the gastrointestinal tract with analogous binding, anti-aggregation, and detoxifying properties. The chemical entities we described may represent a therapeutic avenue for the synucleinopathies and are promising tools to assist diagnosis by discriminating between native and toxic α-synuclein species.

The aSynPEP server is a complementary tool which applies the algorithm used in aSynPEP-DB to predict potential candidates to selectively bind alpha-synuclein and inhibit its aggregation. If the prediction for a full-length peptide is negative, aSynPep runs a sliding window of 18aa (5 helical turns) to find inhibitory regions within the peptide.

How to use the server

Under the "Submission" section, upload a valid FASTA file or paste the peptide sequence(s) in FASTA format in the textbox area. aSynPep is trained only on short peptides and, as a consequence, it is not intended to work with full protein sequences. Peptide range spans from 18 up to 54 aminoacids. Additionally, users can select the option of N- and C- terminal protection to mimic peptide's charge state in the native protein. Also, given that some peptides can adopt local helical structures upon binding to partners, we also allow users to specify the helicity threshold for considering positive candidates. We have stablished a default threshold of 2 to account for high-confident alpha-helical peptides and avoid the number of false positives.

aSynPep will analyze the helical propensity with AGADIR software, amphipaticity, net charge, hydrophobicity, sequence length and the longest inhibitory region found, while providing a prediction on whether each peptide is a good inhibitory candidate or not.



aSynPep will display a table with the sequence IDs, the outcome and the calculated parameters: helical content (with AGADIR software), amphipaticity (uH), net charge, hidrophobicity (H) and length. If the number of peptides is <= 10, the corresponding helical wheels for each positive peptide can be be accessed by clicking on the identifiers.

Columns in online output, and in the downloadable summary table:

Peptide ID: Sequence identifier, tag line.
Prediction: It informs whether peptide is predicted to bind and inhibit the aggregation of alpha-synuclein (positive) or not (negative). Positive outcomes are those cationic peptides (or a region within) with an AGADIR score >= 2 (or the defined helical threshold) and uH >= 0.2.
Helicity (AGADIR): Binarized helical prediction obtained from AGADIR external software.
Amphipaticity (uH): Hydrophobic dipole moment obtained from an array of hydrophobicity values, as described in Eisenberg's equation (1982).
Net charge: Global net charge obtained using the Henderson-Hasselbalch equation.
Hydrophobicity (H): Hydrophobic score obtained with Fauchere et al. scale (1983).
Length: Peptide's number of residues.
Longest inhibitory region: Full-length peptide/Defined region/None.

Users can alternatively download the numerical calculations in CSV format or the whole project data in a compressed ZIP folder (including JSON and CSV formats, tables and images) by clicking the upper left links.