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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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STAR: predicting recombination sites from amino acid sequence.

Denis C Bauer1, Mikael Bodén, Ricarda Thier

  • 1Institute for Molecular Bioscience, The University of Queensland, QLD 4072, Australia. d.bauer@imb.uq.edu.au

BMC Bioinformatics
|October 10, 2006
PubMed
Summary

We developed STAR, a machine learning tool to predict useful recombination sites in protein sequences. STAR helps design novel proteins by identifying optimal locations for swapping sequence parts, even without structural information.

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Area of Science:

  • Protein engineering
  • Computational biology
  • Machine learning in bioinformatics

Background:

  • Site-directed recombination is crucial for designing novel proteins with desired properties.
  • Current methods for identifying recombination sites are often limited by prohibitive requirements.
  • Machine learning offers a promising approach to identify recombination sites from amino acid sequences alone.

Purpose of the Study:

  • To develop a machine learning tool to predict useful recombination sites in amino acid sequences.
  • To assist in the design of novel proteins through site-directed recombination.
  • To overcome limitations of existing tools for identifying recombination sites.

Main Methods:

  • Developed STAR (Site Targeted Amino acid Recombination predictor), a machine learning model.
  • STAR predicts structural disruption scores for recombination at each amino acid position.
  • Evaluated STAR's performance against existing tools and experimental data.

Main Results:

  • STAR provides scores indicating structural disruption from recombination at each sequence position.
  • STAR's predictions are useful for identifying effective recombination sites.
  • STAR shows a high correlation (0.89) with the SCHEMA protein design algorithm's predictions.

Conclusions:

  • STAR enables exploration of recombination sites in protein sequences of unknown structure or origin.
  • The STAR predictor service is publicly available online.
  • STAR facilitates the design of novel proteins by predicting optimal recombination sites.