With Neurosnap you can
We model, screen, and optimize peptide binders against challenging targets entirely in silico.
Trusted by 50,000+ scientists across 5,000+ labs and organizations
Proudly used by top companies and institutions globally
State-of-the-art structure prediction for cyclic peptides and protein–peptide complexes from any sequence.
Scaffold motifs or design de novo cyclic peptides targeted to your protein of interest.
Run hundreds of thousands of protein–peptide structure predictions and calculate free energies for complexes.
Use physics-based simulations to explore binding modes, refine structures, and assess stability over time.
Access a vetted library of 100+ published, state-of-the-art models and workflows with demonstrated track records.
Run folding, docking, and simulations end-to-end in our web workspace to review, refine, and share results instantly.
Neurosnap pipelines let you chain tools, pass outputs downstream, and automate decisions with custom logic.
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Our tools and models utilize cutting edge optimization techniques as well as proprietary post-processing steps that ensure you get the highest quality results possible.
Only you and your colleagues will have access to the data submitted and produced by our platform. We firmly believe that your data is yours, and do not share data with any third parties.
Neurosnap employs state of the art cyber security measures used by both militaries and banks to ensure your data is always kept safe.
With Neurosnap, you get to keep all your IP. No royalties, no equity. The only thing you need to pay for is usage and users.
Our team of qualified experts are ready to guide and onboard you throughout the whole process.
Ajinomoto highlights how Neurosnap’s bioinformatics tools are well-organized and easy to discover, with tags and categories that make it simple to find exactly what they need.
Their teams values the user-friendly, browser-based interfaces—especially for scientists unfamiliar with command-line tools—so they can run workflows quickly without technical setup.
Rapid releases of state-of-the-art tools mean they can screen new methods immediately, avoid time-consuming local installations and dependency issues, and only install the tools that prove useful. This saves time on setup and literature checks while keeping their research moving fast.
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