ESMFold v2 leverages advanced deep learning techniques to predict the 3D structures of proteins with unprecedented speed and accuracy, making it an essential tool for researchers in structural biology, drug discovery, and related fields.
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ESMFold v2
High-speed, high-accuracy protein folding model.
Developed by Meta AI
- Drug discoveryOptimized Capability
- Protein designOptimized Capability
- Structural biology researchOptimized Capability
- Genomic data analysisOptimized Capability
Predict the 3D structure of a protein sequence: 'MKTAYIAKQRQISFVKSHFSRQDILD' with ESMFold v2.
- ✓ Faster structure predictions compared to its predecessor, enabling real-time applications in drug discovery.
- ✓ Improved accuracy in fold predictions, enhancing reliability in structural biology experiments.
- ✓ Open-source availability promotes collaborative research and rapid advancement within the scientific community.
- ✗ High computational resource requirements, which may limit accessibility for some users.
- ✗ Complex setup process that may deter users lacking advanced technical expertise.
- ✗ Potential limitations in predicting structures of very large proteins or complex protein complexes.
Technical Documentation
Best For
Research institutions and biotech companies focused on protein structure and drug development.
Alternatives
AlphaFold 2, RoseTTAFold, RaptorX
Pricing Summary
Free and open-source under the MIT license.
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