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Related Experiment Video

Updated: Jan 7, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Prodigy protein: Python package for zero-shot protein engineering using protein language models.

Matthew Massett1, Adrian Carr2

  • 1AI Innovation, Sanofi, Babraham Research Campus, Cambridge, CB22 3AT, UK. matthew.massett@sanofi.com.

BMC Bioinformatics
|December 30, 2025
PubMed
Summary
This summary is machine-generated.

Prodigy Protein is a new tool for protein design that uses Protein Language Models (PLMs) to suggest amino acid changes. It enables faster, more flexible in silico protein engineering by integrating multiple PLMs for variant design.

Keywords:
Directed evolutionProtein Language ModelProtein designSequence optimisation

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Protein Engineering

Background:

  • Protein Language Models (PLMs) are advanced AI tools for protein design.
  • PLMs can predict mutation effects and suggest amino acid substitutions without fine-tuning.

Purpose of the Study:

  • Introduce Prodigy Protein, a novel tool for protein design.
  • Enable stepwise amino acid substitutions and efficient protein variant generation.

Main Methods:

  • Prodigy Protein utilizes DirectedEvolution classes for stepwise amino acid substitutions.
  • Employs two scoring strategies to evaluate substitutions and sample promising candidates.
  • Allows customization of evolution steps, target regions, and score thresholds.

Main Results:

  • Prodigy Protein facilitates rapid and flexible in silico protein design.
  • Integrates any masked language modeling PLM via Hugging Face.
  • Supports the integration of multiple PLMs for designing protein variants.

Conclusions:

  • Prodigy Protein offers a unique probabilistic framework for protein design.
  • Enables the design of protein variants by combining multiple PLMs, a feature not found in other tools.
  • Provides a fast, flexible, and efficient solution for in silico protein engineering.