MemConverter: An Iterative Pipeline for Reprogramming Protein Localization in Membrane or Aqueous Solution

Area of Science:

• Computational biology
• Protein engineering
• Biophysics

Background:

• Engineering proteins for specific cellular localization is crucial for biotechnology and therapeutics.
• Existing methods for protein localization reprogramming often lack precision and efficiency.
• Predicting and controlling protein-environment interactions, particularly membrane association, remains a challenge.

Purpose of the Study:

• To introduce MemConverter, a novel computational pipeline for converting soluble proteins to membrane proteins and vice versa.
• To enable precise reprogramming of protein surface properties for targeted localization.
• To provide a validated computational tool for designing proteins for membrane or aqueous environments.

Main Methods:

• Development of MemProtMPNN by fine-tuning ProteinMPNN on a membrane protein dataset.
• Integration of MemProtMPNN with AlphaFold2 for iterative structure refinement.
• Utilization of membrane contact probability (MCP) for guided sequence fusion and protein design.
• Validation using molecular dynamics simulations.

Main Results:

• The MemConverter pipeline demonstrated superior performance over existing methods.
• Designed proteins showed stable membrane integration or enhanced solubility, as confirmed by molecular dynamics simulations.
• Successful reprogramming of protein localization based on MCP predictions.

Conclusions:

• MemConverter offers a powerful new computational approach for engineering protein localization.
• The pipeline facilitates the design of proteins for targeted integration into membranes or soluble environments.
• This work advances the field of protein engineering with a tool for precise control over protein localization.