solublempnn

Name: solublempnn
Availability: InStock
Author: junior1p

Generate solubility-optimized protein sequences using SolubleMPNN workflows.

11|Updated Mar 4, 2026

Search Tags:#aggregation #inverse-folding #sequence-design #protein-design #solubility #solublempnn #ecoli-expression

Ready to run

npx skills add https://github.com/junior1p/ProteinClaw --skill solublempnn-junior1p

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: solublempnn
Source: https://github.com/junior1p/ProteinClaw/tree/main/skills/solublempnn
Command: npx skills add https://github.com/junior1p/ProteinClaw --skill solublempnn-junior1p

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Soluble MPNN enables the design of protein sequences with enhanced solubility, reducing aggregation and improving expression yields in bacterial systems such as E. coli.

Core Features & Use Cases

Solubility-focused sequence design to minimize aggregation propensity during expression.
Ligand-aware and standard design modes enabling flexible workflows (SolubleMPNN variants and recommended usage alongside ProteinMPNN).
Clear design guidance including prerequisites, model variants, and decision logic for when to use SolubleMPNN vs LigandMPNN.

Quick Start

Provide a target protein sequence and run the SolubleMPNN workflow to generate solubility-optimized designs.

Frequently Asked Questions about solublempnn

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design soluble protein sequences for E. coli expression?▼

To design soluble protein sequences, provide a target protein sequence to the SolubleMPNN workflow, which generates solubility-optimized designs that reduce aggregation and improve expression yields in E. coli systems.

What is the difference between standard and ligand-aware inverse folding for solubility?▼

Standard inverse folding uses the ProteinMPNN model variant for solubility-focused sequence design, whereas ligand-aware design uses the LigandMPNN mode to account for specific molecular interactions during the solubility optimization process.

Do I need GPU resources to run solubility-optimized protein design?▼

Yes, solubility-optimized protein design requires GPU resources and Python 3.8 or higher to execute the SolubleMPNN workflow for generating sequences with enhanced solubility and reduced aggregation propensity.

When should I use SolubleMPNN instead of standard ProteinMPNN?▼

Use SolubleMPNN instead of standard ProteinMPNN when your target protein is aggregation-prone and you need solubility-focused sequence design to achieve high-yield production in bacterial expression systems like E. coli.

Can I optimize aggregation-prone proteins for high-yield bacterial production?▼

Yes, you can optimize aggregation-prone proteins by applying the SolubleMPNN workflow to generate solubility-optimized sequences, effectively reducing aggregation propensity and improving expression yields in bacterial systems.