ArticleProceedings of the National Academy of Sciences of the United States of America2011
A general strategy for the evolution of bond-forming enzymes using yeast display.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 262 papers.
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Who cites it
262 citing papers in PubMed, 585 citations in OpenAlex.
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202 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
The ability to routinely generate efficient protein catalysts of bond-forming reactions chosen by researchers, rather than nature, is a long-standing goal of the molecular life sciences. Here, we describe a directed evolution strategy for enzymes that catalyze, in principle, any bond-forming reaction. The system integrates yeast display, enzyme-mediated bioconjugation, and fluorescence-activated cell sorting to isolate cells expressing proteins that catalyze the coupling of two substrates chosen by the researcher. We validated the system using model screens for Staphylococcus aureus sortase A-catalyzed transpeptidation activity, resulting in enrichment factors of 6,000-fold after a single round of screening. We applied the system to evolve sortase A for improved catalytic activity. After eight rounds of screening, we isolated variants of sortase A with up to a 140-fold increase in LPETG-coupling activity compared with the starting wild-type enzyme. An evolved sortase variant enabled much more efficient labeling of LPETG-tagged human CD154 expressed on the surface of HeLa cells compared with wild-type sortase. Because the method developed here does not rely on any particular screenable or selectable property of the substrates or product, it represents a powerful alternative to existing enzyme evolution methods.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.