Project

Directed evolution of modular proteins driven by machine learning: the VersaTile Platform 2.0

Duration
01 January 2019 → Ongoing
Funding
Research Foundation - Flanders (FWO)
Promotor
Research disciplines
  • Natural sciences
    • Data mining
    • Machine learning and decision making
  • Engineering and technology
    • Medical molecular engineering of nucleic acids and proteins
    • Bio-informatics
Keywords
protein engineering machine learning alternative antibiotics
 
Project description

The VersaTile Platform 1.0 is a technology developed for the synthetic biology of modular proteins. This technology is a molecular equivalent of LEGO: first, you make a collection of LEGO building blocks (equivalent of a protein module), subsequently you can make any construction (equivalent of modular protein) with these lego building blocks in a highly efficient way and with a very high throughput (up to millions of modular protein variants can be made in a day). This technology is of high interest for the industry as many biologicals have a modular structure (industrial enzymes, antibodies, vaccines, biopolymers…). In this doctoral research proposal, I aim to leverage the economic potential of the platform with an upgrade to the VersaTile Platform 2.0. I will develop computational methods to learn as much as possible from natural evolution of modular proteins and introduce machine learning to obtained fully optimized modular proteins. Specifically, I will use enzybiotics, or modular enzyme-based antibiotics, as a case study and validate the whole process in the lab. The expected outcome is that we create a specific enzybiotic that is highly active against vancomycin resistant enterococci. Importantly, I will develop all tools as such that they can be generally applied to any modular protein, regardless of their application field.