{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "sokrypton-colabfold--prepare-alphafold3-inputs-with-colabfold-msas",
 "repo": "sokrypton/ColabFold",
 "repo_url": "https://github.com/sokrypton/ColabFold",
 "repo_slug": "sokrypton-colabfold",
 "title": "Prepare AlphaFold3 inputs with Colab Fold alignments",
 "page_title": "How to prepare AlphaFold3 inputs with Colab Fold alignments with Colab Fold",
 "summary": "Export Colab Fold MSAs as AlphaFold3-compatible JSON, including ligands and nucleic acids written in the FASTA.",
 "who": "A structural biologist running AlphaFold3 who wants Colab Fold's fast MMseqs2 alignments instead of AF3's own search.",
 "problem": "Generating MSAs inside AlphaFold3 is slow, and hand-writing its JSON for complexes with ligands is error prone.",
 "outcome": "AlphaFold3 input JSON files, one per entry, ready to feed to AlphaFold3.",
 "steps": [
  "Write complexes in FASTA, adding non-protein parts as molecule type|sequence|(copies), for example ccd|ATP|2 or dna|ATCG",
  "With local databases run `colabfold_search --mmseqs /path/to/bin/mmseqs input_sequences.fasta /path/to/db_folder msas --af3-json`",
  "Or with the MSA server run `colabfold_batch input_sequences.fasta out_dir --af3-json` (prediction is skipped, only JSON is written)",
  "Speed up searches on GPUs: set up GPU databases with `GPU=1 ./setup_databases.sh /path/to/db_folder` and add --gpu 1",
  "Pass the generated JSON files to AlphaFold3"
 ],
 "agent_prompt": "With sokrypton/ColabFold, turn <my FASTA with proteins and ligands> into AlphaFold3 input JSON using --af3-json. Check the FASTA uses the molecule type|sequence|(copies) format and replace aromatic ':' bonds in SMILES with ';'.",
 "agents": [
  "claude-code",
  "codex",
  "cursor",
  "gemini-cli"
 ],
 "difficulty": "Advanced",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "MMseqs2 MSAs are only generated for protein sequences; RNA entries get a null unpaired MSA so AlphaFold3 builds its own.",
 "category": "Security and science",
 "tags": [
  "Security and science"
 ],
 "lang": "jupyter notebook",
 "requirements": [
  "A Google account for the Colab notebooks, or a local ColabFold install for colabfold_search and colabfold_batch",
  "For local searches: MMseqs2 and the ColabFold databases (large downloads, a lot of CPU)",
  "A GPU for structure prediction; about 16 GB of GPU memory handles sequences up to roughly 2000 residues",
  "For GPU search: GPU databases set up with GPU=1"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/sokrypton-colabfold/prepare-alphafold3-inputs-with-colabfold-msas/",
 "md": "https://dedupedai.com/use-cases/sokrypton-colabfold/prepare-alphafold3-inputs-with-colabfold-msas/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/sokrypton-colabfold--prepare-alphafold3-inputs-with-colabfold-msas.json",
 "api_version": "v1"
}