adaptyvbio/protein-design-skills/protenix

Claude Code and agent skill by adaptyvbio/protein-design-skills

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Structure prediction with Protenix, an open AlphaFold3 reproduction. Use this skill when: (1) Predicting complex structures with an AF3-class model, (2) Wanting an open alternative to AF3 alongside Boltz and Chai, (3) Validating designed binder-target complexes. For QC thresholds, use protein-qc. For ipSAE ranking, use ipsae.

Install

npx vskill@latest install adaptyvbio/protein-design-skills/protenix

SKILL.md

Protenix Structure Prediction

Protenix is ByteDance's open PyTorch reproduction of AlphaFold3 (Apache 2.0). It is an AF3-class complex predictor, useful next to boltz and chai for cross-checking designed complexes. Runnable through biomodals.

Use Protenix-v2 for antibody-antigen complexes. The v2 model (464M params, April 2026) adds 9 to 13 percentage points of antibody-antigen accuracy over v1 at the DockQ > 0.23 threshold and is more sample-efficient (v2 at 5 seeds exceeds v1 at 1000). Select it with --model-name protenix-v2. For general complexes, the v1 base model is fine.

Prerequisites

RequirementValue
RunnerModal (biomodals)
GPUL40S (default; GPU env var)
SetupSee Getting started

How to run

bash
git clone https://github.com/hgbrian/biomodals && cd biomodals
 
printf '>protein|A\nMAWTPLLLLLLSHCTGSLSQ...\n' > target.faa
 
uv run --with modal modal run modal_protenix.py \
  --input-faa target.faa \
  --seeds 42 \
  --no-use-msa

Key parameters

ParameterDefaultDescription
--input-faaone requiredFASTA input (or --input-json)
--seeds42Comma-separated seeds
--use-msa / --no-use-msaMSA onPass --no-use-msa for single-sequence
--model-namev1 baseSet protenix-v2 for antibody-antigen complexes
--use-minioffSwitch to the smaller protenix_mini model
--out-dir./out/protenixOutput directory

When to use Protenix vs Boltz vs Chai

NeedTool
Affinity head (small molecules)boltz (Boltz-2)
Fastest, ligand supportchai
Open AF3 reproductionprotenix (v1 base)
Antibody-antigen complexesprotenix-v2

Ranking a shortlist across more than one predictor is more reliable than trusting a single model.

Troubleshooting

IssueCauseFix
Missing input errorNo --input-faa/--input-jsonProvide one
Slow runMSA enabledAdd --no-use-msa
OOMLarge complexUse --use-mini or a larger GPU

Next: Rank with ipsae, filter with protein-qc.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

See the full security report

Quality evaluation

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Source

Popularity

Repository stars
142
Repository forks
16
7-day trend score
25

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