Site-specific tyrosine-type recombinases are effective tools for genome engineering, with the first engineered variants having demonstrated therapeutic potential. So far, adaptation to new DNA target site selectivity of designerrecombinases has been achieved mostly through iterative cycles of directed molecular evolution. While effective, directed molecular evolution methods are laborious and time consuming. Here we present RecGen (Recombinase Generator), an algorithm for the intelligent generation of designerrecombinases. We gather the sequence information of over one million Crelike recombinase sequences evolved for 89 different target sites with whichwe train Conditional Variational Autoencoders for recombinase generation. Experimental validation demonstrates that the algorithm can predict recombinase sequences with activity on novel target-sites, indicating that RecGen is useful to accelerate the development of future designer-recombinases.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:91838 |
Date | 04 June 2024 |
Creators | Schmitt, Lukas Theo, Paszkowski-Rogacz, Maciej, Jug, Florian, Buchholz, Frank |
Publisher | Nature Publishing Group |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 2041-1723, 7966, 10.1038/s41467-022-35614-6, info:eu-repo/grantAgreement/European Commission/H2020 | RIA/825825//Unlocking Precision Gene Therapy/UPGRADE, info:eu-repo/grantAgreement/European Commission/H2020 | ERC | ERC-ADG/742133//Designer recombinases for efficient and safe genome surgery/GENSURGE |
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