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

Requirement	Value
Runner	Modal (biomodals)
GPU	L40S (default; GPU env var)
Setup	See Getting started

How to run

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

Parameter	Default	Description
--input-faa	one required	FASTA input (or --input-json)
--seeds	42	Comma-separated seeds
--use-msa / --no-use-msa	MSA on	Pass --no-use-msa for single-sequence
--model-name	v1 base	Set protenix-v2 for antibody-antigen complexes
--use-mini	off	Switch to the smaller protenix_mini model
--out-dir	./out/protenix	Output directory

When to use Protenix vs Boltz vs Chai

Need	Tool
Affinity head (small molecules)	boltz (Boltz-2)
Fastest, ligand support	chai
Open AF3 reproduction	protenix (v1 base)
Antibody-antigen complexes	protenix-v2

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

Troubleshooting

Issue	Cause	Fix
Missing input error	No --input-faa/--input-json	Provide one
Slow run	MSA enabled	Add --no-use-msa
OOM	Large complex	Use --use-mini or a larger GPU

---

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