Mol-1
All-atom biomolecular structure prediction with ranked models and token-level confidence.
Overview
Predict all-atom structures of proteins, DNA, RNA, and small molecules together using Mol-1. Model a single chain or a mixed biomolecular assembly, with optional residue modifications and covalent bonds. Compare ranked models using local, global, and interface confidence scores.
Run Mol-1 on Neurosnap
The Mol-1 online webserver allows anybody with a Neurosnap account to run and access Mol-1, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Predict proteins, DNA, RNA, and ligands together in one assembly.
- Support residue modifications and optional covalent bonds.
- Generate protein alignments using Neurosnap's private MSA pipeline, or predict without MSAs.
- Inspect ranked mmCIF models, pLDDT, pTM, ipTM, predicted distance error, and token-level PAE.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access Mol-1 using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using Mol-1 in publications or research outputs.
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Molence Bio. Mol-1: Open Frontier Biomolecular Intelligence. https://github.com/molence/Mol-1. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |