How to Use CleaveNet Peptide Substrate Design
Commercially Available Online Web Server
Use CleaveNet online to predict MMP cleavage and design peptide substrates.
CleaveNet designs peptide substrates for matrix metalloproteinases. Submit peptides for cleavage prediction, generate an unconditional library, or condition generation on target Z-scores across all 18 MMPs. The released model includes MMP24.
The model was evaluated primarily on 10-residue substrates. Shorter peptides are centered with terminal padding. Generated sequences may repeat and should be validated experimentally.
How CleaveNet Peptide Substrate Design Works
Choose Mode, then fill the relevant section. For prediction, submit Input Peptides. For generation, set Number of Peptides, Temperature, and Repeat Penalty. Conditional generation additionally requires rows in Target Cleavage Profiles; unspecified cells default to zero. The peptide count applies per row, with at most 1000 peptides total.
The results CSV contains peptide names, sequences, model inputs, predicted cleavage Z-scores, and ensemble standard deviations. Conditional results identify the target profile by its one-based row number. Higher scores indicate greater relative predicted cleavage; scores are not cleavage probabilities or rates. Ensemble SD measures disagreement across five predictors, not an experimental confidence interval. Generation also provides FASTA for downstream screening.
What is Neurosnap?
Neurosnap is the leading platform for bioinformatics and computational science focused on expanding access to powerful modeling and simulation tools. Because many state-of-the-art machine learning systems remain complex to install, configure, and scale, Neurosnap offers a clean, browser-based workspace that removes the burden of infrastructure management, dependency conflicts, and command-line tooling.
Built for biologists, chemists, and cross-disciplinary scientists, the platform enables advanced computational workflows without requiring expertise in software engineering or cloud architecture. Researchers can launch analyses through an intuitive interface, connect programmatically through a comprehensive API, and rely on automated resource management to scale workloads efficiently. By taking care of the underlying compute and operational complexity, Neurosnap allows teams to devote their energy to scientific progress and faster iteration. Security and data protection remain foundational principles, with clear safeguards outlined in our Terms of Use and Privacy Policy to ensure your work stays protected.
Advancing Discovery with CleaveNet Peptide Substrate Design on Neurosnap
Using CleaveNet Peptide Substrate Design on Neurosnap could drastically accelerate peptide substrate screening and MMP-selective library design.
- Score peptide libraries across 18 MMPs.
- Condition generation on desired cleavage profiles.
- Compare candidates using CSV predictions and FASTA sequences.
How to Use CleaveNet Peptide Substrate Design on Neurosnap
To harness the capabilities of CleaveNet Peptide Substrate Design, researchers can follow this streamlined workflow within Neurosnap:
- Access Neurosnap: Start by logging in to the Neurosnap website.
- Select Tool: From the list of available tools, choose CleaveNet Peptide Substrate Design.
- Provide Inputs: Provide all the inputs specified within the submission panel and optionally configure the tool as desired.
- Run Tool: Submit the CleaveNet Peptide Substrate Design job and Neurosnap will execute it in the cloud, automatically notifying you as soon as your results are ready.
- Review Output: Explore your results through rich visualizations, including figures, plots, and interactive views designed to help you analyze findings with clarity and confidence.
Citations
Please cite the original work when using CleaveNet Peptide Substrate Design in publications or research outputs.
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CleaveNet: protease substrate prediction and generation. https://www.biorxiv.org/content/10.1101/2025.02.27.640681v1. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |
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