Generate solubility-optimized protein sequences using SolubleMPNN workflows.
npx skills add https://github.com/junior1p/ProteinClaw --skill solublempnn-junior1p
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
Soluble MPNN enables the design of protein sequences with enhanced solubility, reducing aggregation and improving expression yields in bacterial systems such as E. coli.
Provide a target protein sequence and run the SolubleMPNN workflow to generate solubility-optimized designs.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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