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Related Concept Videos

Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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A web-based tool for rational screening of mutants libraries using ProSAR.

Magali Berland1, Bernard Offmann2, Isabelle André3

  • 1DSIMB, INSERM UMR-S1134, Université de La Réunion, 97715 Saint-Denis, France Laboratory of Excellence GR-Ex, 75015 Paris, France Université de Nantes, UFIP, UMR CNRS 6286, 2 chemin de la Houssinière, 44000 Nantes, France.

Protein Engineering, Design & Selection : PEDS
|August 30, 2014
PubMed
Summary

Screening mutant libraries in directed evolution is crucial. A new web tool, ProSAR, uses in silico statistical models to efficiently link sequence data to protein activity, improving the search for optimal mutants.

Keywords:
epistatic interactions between mutationsfitness landscape explorationprotein engineeringrational screeningsequence–activity relationship

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Area of Science:

  • Biotechnology
  • Computational Biology
  • Protein Engineering

Background:

  • Directed evolution requires efficient screening of mutant libraries to identify proteins with improved functions.
  • Current screening methods can be time-consuming and resource-intensive, limiting the scope of evolutionary experiments.

Purpose of the Study:

  • To introduce a web-based tool implementing the ProSAR (Protein Structure-Activity Relationship) in silico method for rational screening of mutant libraries.
  • To provide a user-friendly platform for predicting protein activity based on sequence data and experimental results.

Main Methods:

  • The ProSAR method utilizes statistical models trained on user-provided experimental datasets.
  • These models integrate sequence information and can account for epistatic interactions between mutations.
  • The approach is designed for broad applicability across diverse biological contexts.

Main Results:

  • The ProSAR method significantly enhances the efficiency of identifying superior mutants.
  • It provides a rational approach to screening, reducing the need for extensive experimental testing.
  • The web tool offers a practical implementation of this in silico screening strategy.

Conclusions:

  • The ProSAR web tool offers a powerful and efficient solution for screening mutant libraries in directed evolution.
  • This computational approach accelerates the discovery of improved protein variants.
  • The tool is freely accessible for non-commercial use, promoting advancements in protein engineering.