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Bio Af2 Folding Inference

skill-onescience-ai-oneskills-af2-folding-inference · by onescience-ai

AlphaFold v2 / OpenFold 蛋白结构推理 skill。用于执行 OneScience 中 AlphaFold JAX、AlphaFold-Multimer 或 OpenFold PyTorch 的 FASTA/MSA/template 推理,收紧 model_preset、db_preset、feature pipeline、checkpoint、输出 PDB/PAE/pLDDT 校验和常见失败恢复。

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Install

$ agentstack add skill-onescience-ai-oneskills-af2-folding-inference

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

AF2 / OpenFold 结构推理

使用边界

用于 AF2 风格蛋白结构预测:AlphaFold JAX/Haiku 或 OpenFold PyTorch。若输入含蛋白、核酸、配体多分子复合物并使用 AF3 JSON,读取 ../af3-protenix-complex-inference/SKILL.md

可复用资源

  • {onescience_path}/onescience/examples/biosciences/_manifests/model_requests/af2_inference_request.yaml:FASTA、preset、数据库、参数和输出模板。
  • references/af2_openfold_execution.md:AlphaFold 和 OpenFold 的入口、协议差异、preflight 和输出检查。
  • 公共检查工具:{onescience_path}/onescience/examples/biosciences/_manifests/tools/validate_bio_inference_manifest.py{onescience_path}/onescience/examples/biosciences/_manifests/tools/check_inference_outputs.py

推荐流程

  1. 选择模型:原版 AF2/JAX 用 AlphaFold;PyTorch/OpenFold 权重或 OpenFold pipeline 用 OpenFold
  2. 明确输入:FASTA、monomer/multimer、MSA 是否预计算、template 最大日期、数据库 preset。
  3. 读模型卡:onescience-coder/assets/models/alphafold.mdopenfold.md
  4. 固定入口:
  • AlphaFold:{onescience_path}/onescience/examples/biosciences/alphafold/run_alphafold.py
  • OpenFold:{onescience_path}/onescience/examples/biosciences/openfold/run_pretrained_openfold.py
  1. Preflight:参数目录、数据库目录、MSA 工具、template、输出目录、设备和精度。
  2. Postflight:ranked PDB、unrelaxed/relaxed 区分、ranking_debug、pLDDT/PAE、链数和残基数。

交接物

bio_task_family: bio-inference
selected_concrete_skill: af2-folding-inference
model_family: AlphaFold_or_OpenFold
inference_mode: monomer_or_multimer
input_protocol: FASTA_plus_MSA_template_pipeline
entrypoint:
checkpoint_or_model_dir:
database_preset:
model_preset:
preflight_checks:
expected_outputs:
output_validation_plan:
execution_entry:

禁止事项

  • 不要把 AlphaFold JAX feature dict 直接交给 OpenFold PyTorch batch。
  • Multimer 不能只把多条链拼成 monomer FASTA;必须走对应 preset 和 pipeline。
  • 不要把 relaxed PDB 当作模型原始结构误差分析对象。

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.