A Genetic Programming Approach to Engineering MRI Reporter Genes

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@Article{Bricco:2023:ACSsynbio,

• author = "Alexander R. Bricco and Iliya Miralavy and Shaowei Bo and Or Perlman and David E. Korenchan and Christian T. Farrar and Michael T. McMahon and Wolfgang Banzhaf and Assaf A. Gilad",
• title = "A Genetic Programming Approach to Engineering {MRI} Reporter Genes",
• journal = "ACS Synthetic Biology",
• year = "2023",
• volume = "12",
• number = "4",
• pages = "1154--1163",
• keywords = "genetic algorithms, genetic programming, protein engineering, CEST MRI",
• ISSN = "2161-5063",
• URL = "https://www.sciencedirect.com/science/article/pii/S2161506323002140",
• DOI = "doi:10.1021/acssynbio.2c00648",
• abstract = "Here we develop a mechanism of protein optimization using a computational approach known as genetic programming. We developed an algorithm called Protein Optimisation 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.",

}

Genetic Programming entries for Alexander R Bricco Iliya Miralavy Shaowei Bo Or Perlman David E Korenchan Christian T Farrar Michael T McMahon Wolfgang Banzhaf Assaf A Gilad

Citations