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Directed Evolution: Comparison
Please note this is a comparison between Version 1 by Yu Peng and Version 2 by Yu Peng.

Directed evolution is an iterative, selection-driven process that generates heritable molecular diversity and enriches variants according to a defined functional criterion [1][2]. In protein engineering, a campaign typically begins with a parent gene or a library of genes encoding protein variants, and the encoded proteins are evaluated by screening or selection [2]. Molecular diversity is introduced through mutagenesis and recombination, and sequences associated with the selected phenotype are recovered to seed the next round of diversification [1][2]. This iterative cycle requires a recoverable linkage between the measured or selected phenotype and its encoding nucleic acid sequence, so that functional information can be translated back into sequence information [3]. The outcome of a directed-evolution campaign is therefore determined by the starting sequence population, the accessible variation, the assay and selection conditions, and the number of iterative rounds; the final sequence distribution reflects both the variants generated and the functional constraints imposed during evaluation [4].

  • genetic diversity
  • selection
  • protein variants
  • iterative evolution

🔵 Evolution and Genetic Dynamics • 🟣 Genetics • 🟡 Biochemistry, Genetics and Molecular Biology • 🔴 Life Sciences

References

  1. David Medina-Ortiz; Ashkan Khalifeh; Hoda Anvari-Kazemabad; Mehdi D. Davari; Interpretable and Explainable Predictive Machine Learning Models for Data-driven Protein Engineering. Biotechnol. Adv. 2024, 79, 108495. [CrossRef]
  2. Frances H. Arnold; Directed Evolution: Bringing New Chemistry to Life. Angew. Chem. Int. Ed. 2017, 57, 4143-4148. [CrossRef]
  3. David Medina-Ortiz; Ashkan Khalifeh; Hoda Anvari-Kazemabad; Mehdi D. Davari; Interpretable and Explainable Predictive Machine Learning Models for Data-driven Protein Engineering. Biotechnol. Adv. 2024, 79, 108495. [CrossRef]
  4. Alexandre Barrozo; Rok Borstnar; Gaël Marloie; Shina Caroline Lynn Kamerlin; Computational Protein Engineering: Bridging the Gap between Rational Design and Laboratory Evolution. Int. J. Mol. Sci. 2012, 13, 12428-12460. [CrossRef]
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