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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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Evolutionary Processes in Microbes01:26

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Updated: Jun 20, 2026

Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli
09:01

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Published on: March 16, 2011

Evolución dirigida rápida guiada por modelos de lenguaje de proteínas e interacciones epistáticas

Vincent Q Tran1,2, Matthew Nemeth1, Liam J Bartie1

  • 1Arc Institute, 3181 Porter Drive, Palo Alto, CA, USA.

Science (New York, N.Y.)
|February 19, 2026
PubMed
Resumen

Desarrollamos MULTI-evolve, un marco rápido de ingeniería de proteínas para descubrir eficientemente mutaciones sinérgicas. Este enfoque guiado por aprendizaje automático acelera el descubrimiento de funciones proteicas mejoradas.

Palabras clave:
ingeniería de proteínasevolución dirigidamodelos de lenguaje de proteínasinteracciones epistáticasdiseño de multimutantesaprendizaje automático

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Área de la Ciencia:

  • Bioquímica y Biología Molecular
  • Biología Computacional
  • Ingeniería de Proteínas

Sus antecedentes:

  • La ingeniería de proteínas enfrenta desafíos para navegar por vastos espacios de secuencias en busca de mutaciones sinérgicas.
  • Los métodos actuales, como la acumulación de mutaciones paso a paso y el aprendizaje automático, a menudo son ineficientes o requieren muchos recursos.

Objetivo del estudio:

  • Presentar MULTI-evolve, un marco novedoso para la ingeniería sistemática de multimutantes de proteínas.
  • Superar las limitaciones en la síntesis de genes y acelerar el descubrimiento de mutaciones beneficiosas.

Principales métodos:

  • Utilización de modelos de lenguaje de proteínas o datos funcionales combinados con modelado epistático para predecir combinaciones de mutaciones sinérgicas.
  • Empleo de MULTI-assembly, una técnica de mutagénesis de alta eficiencia para ensamblar secuencias de varios kilobases.

Principales resultados:

  • Se lograron mejoras de hasta 10 veces en la proteína en una sola ronda de evolución dirigida en tres proteínas diferentes.
  • Se demostró la capacidad del marco para optimizar la ingeniería de multimutantes de extremo a extremo.

Conclusiones:

  • MULTI-evolve ofrece una solución rápida y eficiente para diseñar proteínas con funciones mejoradas.
  • El marco es aplicable a una amplia gama de tipos y funcionalidades de proteínas.