How to use In Silico Digestion

Generate peptides from enzyme-specific cleavage rules with optional missed cleavages, length filtering, positional coordinates, and monoisotopic mass and m/z.

This service uses Pyteomics 5.0.1 with local sequence algorithms and bundled mass constants. Modified peptides and mass-spectrometry data-file analysis are outside this workflow.

How In Silico Digestion | Pyteomics Works

Submit protein sequences and select an enzyme. Trypsin uses Pyteomics' ExPASy specificity including its documented exceptions; Lys-C cleaves after K, Arg-C after R, Asp-N before D, and Glu-C here is E-specific. Chymotrypsin uses the high-specificity ExPASy rule. Select the maximum number of missed cleavage sites and an inclusive peptide length range. Digestion is fully specific; semi-specific digestion is not included. Repeated peptides are retained at each position, and coordinates are one-based and inclusive. No peptide passing the filters produces an empty table with a valid downloadable CSV header. Masses assume unmodified peptides with free termini, and m/z uses the chosen positive precursor charge. These rules describe theoretical digestion, not experimentally measured cleavage efficiencies.

Submit up to 100 sequences and 50000 residues total. Output tables are capped at 200000 rows; narrow the digestion range or fragment selections for large submissions.

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 In Silico Digestion | Pyteomics on Neurosnap

Using In Silico Digestion | Pyteomics on Neurosnap could drastically accelerate sequence-based peptide analysis with downloadable results.

Analyze multiple named sequences in a single submission.
Review sortable tables and download CSV results.
Use consistent mass and cleavage conventions across sequences.

How to Use In Silico Digestion | Pyteomics on Neurosnap

To harness the capabilities of In Silico Digestion | Pyteomics, 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 In Silico Digestion | Pyteomics.
Provide Inputs: Provide all the inputs specified within the submission panel and optionally configure the tool as desired.
Run Tool: Submit the In Silico Digestion | Pyteomics 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 In Silico Digestion | Pyteomics in publications or research outputs.

Goloborodko AA et al. Pyteomics—a Python framework for exploratory data analysis and rapid software prototyping in proteomics. Analytical Chemistry (2013). https://doi.org/10.1021/ac301425u.

Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/

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