{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "biohub-esm--predict-protein-structures-with-esmfold2",
 "repo": "Biohub/esm",
 "repo_url": "https://github.com/Biohub/esm",
 "repo_slug": "biohub-esm",
 "title": "Predict an all atom structure from a sequence",
 "page_title": "How to predict an all atom structure from a sequence with Esm",
 "summary": "Run ESMFold2 locally to fold a protein, including DNA chains and ligands, and write the result as mmCIF.",
 "who": "A structural biologist who wants a predicted complex without a cluster job.",
 "problem": "Structure prediction pipelines are hard to assemble and slow to run.",
 "outcome": "A .cif file of the predicted complex plus pLDDT, pTM and ipTM scores.",
 "steps": [
  "Install the package with `pip install esm`",
  "Build a StructurePredictionInput with ProteinInput, DNAInput and LigandInput entries as in the README example",
  "Load the model with EsmFold2Model.from_pretrained and call ESMFold2InputBuilder().fold with num_loops, num_sampling_steps and a seed",
  "Print result.plddt, result.ptm and result.iptm, then write result.complex.to_mmcif() to a .cif file"
 ],
 "agent_prompt": "With Biohub/esm, fold <my protein sequence> with ESMFold2 using ESMFold2InputBuilder().fold, print pLDDT, pTM and ipTM, and save the structure as a mmCIF file I can open in a viewer.",
 "agents": [
  "claude-code",
  "codex",
  "cursor",
  "gemini-cli"
 ],
 "difficulty": "Advanced",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "The README notes the model is validated for protein protein interaction design; treat any prediction as a hypothesis to test.",
 "category": "Security and science",
 "tags": [
  "Security and science"
 ],
 "lang": "",
 "requirements": [
  "Python with pip; `pip install esm` is about 5.6 GB, of which about 4.6 GB is the CUDA build of torch",
  "A CUDA GPU for the local examples, which load models with device set to cuda",
  "A Biohub Platform API token if you use the hosted client instead of local weights"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "platform",
   "notice": "AMD ROCm users need ROCm 6.4 or newer, and Esm requires PyTorch 2.11."
  }
 ],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/biohub-esm/predict-protein-structures-with-esmfold2/",
 "md": "https://dedupedai.com/use-cases/biohub-esm/predict-protein-structures-with-esmfold2/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/biohub-esm--predict-protein-structures-with-esmfold2.json",
 "api_version": "v1"
}