Biohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from the same release: masked-LM logits, hidden states, mutation scoring, contact prediction, and the SAE interpretability head. MIT-licensed weights on HuggingFace org biohub. Use this skill when: (1) Predicting complex structures with single-sequence input, (2) Validating designed binders with ESMFold2-Fast, (3) Running ESMFold2 with MSA input, (4) Getting ESMC embeddings or per-residue mutation scores, (5) Choosing kernel backend and sampling-step settings for paper-faithful throughput.
How to install esmfold2?
xuzhougeng/wisp-science/esmfold2
$npx -y skills add xuzhougeng/wisp-science --skill esmfold2Installs into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/xuzhougeng/wisp-science" --skill "xuzhougeng/wisp-science/esmfold2"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/xuzhougeng/wisp-science" that are relevant to the current task. Run `npx skills add "https://github.com/xuzhougeng/wisp-science"` and select the relevant skills, then follow their instructions.
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