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数据与复现蛋白结构与设计FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
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alphafold

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm. For QC thresholds, use protein-….

OpenClawNanoClaw分析处理复现实验alphafold🔬 omics & computational biologyprotein structure & designvalidate

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/alphafold

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • First time? See Installation Guide to set up Modal 、 biomodals。

原始文档

SKILL.md 摘录

Option 1: ColabFold (recommended for multimer)

GPU: A100 (40GB) | Timeout: 3600s default

Key parameters

ParameterDefaultOptionsDescription
--model_presetmonomermonomer/multimerModel type
--num_recycle31-20Recycling iterations
--max_template_date-YYYY-MM-DDTemplate cutoff
--use_templatesTrueTrue/FalseUse template search

Successful run

What good output looks like:

  • pLDDT: > 85 (mean, on 0-100 scale) or > 0.85 (normalized)
  • pTM: > 0.70
  • ipTM: > 0.50 for complexes
  • PAE_interface: < 10

适用场景

  • Use alphafold in 科研工作流 aligned ，支持 this subject area。
  • Follow upstream documentation ，用于 full working procedure。

不适用场景

  • Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。

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