solublempnn

name	solublempnn
description	Solubility-optimized protein sequence design using SolubleMPNN. Use this skill when: (1) Designing for E. coli expression, (2) Optimizing solubility of designed proteins, (3) Reducing aggregation propensity, (4) Need high-yield expression, (5) Avoiding inclusion body formation. For standard design, use proteinmpnn. For ligand-aware design, use ligandmpnn.
license	MIT
category	design-tools
tags	["sequence-design","inverse-folding","solubility"]
source	https://github.com/adaptyvbio/protein-design-skills

SolubleMPNN Solubility-Optimized Design

Prerequisites

Requirement	Minimum	Recommended
Python	3.8+	3.10
GPU VRAM	8GB	16GB (T4)

How to run

cd biomodals
modal run modal_proteinmpnn.py \
  --pdb-path backbone.pdb \
  --num-seq-per-target 16 \
  --sampling-temp 0.1 \
  --model-name v_48_020

Model Variants

Model	Description	Use Case
v_48_002	Standard	General design
v_48_020	Soluble-trained	E. coli expression
v_48_030	High solubility	Difficult targets

Decision tree

When to use SolubleMPNN?
├─ E. coli expression → SolubleMPNN ✓
├─ History of aggregation → SolubleMPNN ✓
├─ History of low yield → SolubleMPNN ✓
├─ Ligand in binding site → LigandMPNN
└─ No expression issues → ProteinMPNN is fine

Expected improvement: +15-30% solubility score vs standard ProteinMPNN.

Next: Structure prediction → protein-qc for filtering.