ESMFold is an open-source protein folding model developed by Meta AI that uses a large language model backbone (ESM-2) to directly predict 3D atomic coordinates from a protein sequence. Unlike AlphaFold2, it does not require multiple sequence alignments or external databases, resulting in significantly faster inference times. It is available via Hugging Face with Transformers integration and is intended for researchers working in structural biology and protein design.
In the Other AI space, Esmfold takes a focused approach. It focuses on predicting accurate 3D protein structures quickly without the computational overhead of multiple sequence alignment databases. It is built as an open-source project for computational biologists and researchers. Esmfold is open source under the Open Source license. It ships for the web and API.
It is developed by Meta AI (United States), and it first shipped in 2022. Among its 5 catalogued features are protein structure prediction, end-to-end folding, and No MSA required. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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