A Genetic Programming Approach to Engineering MRI Reporter Genes

Alexander R. Bricco, Iliya Miralavy, Shaowei Bo, Or Perlman, David E. Korenchan, Christian T. Farrar, Michael T. McMahon, Wolfgang Banzhaf, Assaf A. Gilad

Research output: Contribution to journalArticlepeer-review

Abstract

Here we develop a mechanism of protein optimization using a computational approach known as “genetic programming”. We developed an algorithm called Protein Optimization Engineering Tool (POET). Starting from a small library of literature values, the use of this tool allowed us to develop proteins that produce four times more MRI contrast than what was previously state-of-the-art. Interestingly, many of the peptides produced using POET were dramatically different with respect to their sequence and chemical environment than existing CEST producing peptides, and challenge prior understandings of how those peptides function. While existing algorithms for protein engineering rely on divergent evolution, POET relies on convergent evolution and consequently allows discovery of peptides with completely different sequences that perform the same function with as good or even better efficiency. Thus, this novel approach can be expanded beyond developing imaging agents and can be used widely in protein engineering.

Original languageEnglish (US)
Pages (from-to)1154-1163
Number of pages10
JournalACS Synthetic Biology
Volume12
Issue number4
DOIs
StatePublished - Apr 21 2023

Keywords

  • CEST MRI
  • genetic programming
  • protein engineering

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)

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