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Screening and selection methods for large-scale analysis of protein function.

Hening Lin1, Virginia W Cornish

  • 1Department of Chemistry, Columbia University, New York, NY 10027, USA.

Angewandte Chemie (International Ed. in English)
|November 30, 2002
PubMed
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High-throughput assays are revolutionizing protein engineering and proteomics. These powerful tools enable the evolution of novel protein functions and the rapid assignment of functions to newly discovered proteins.

Area of Science:

  • Biochemistry and Molecular Biology
  • Protein Engineering
  • Proteomics

Background:

  • High-throughput assays offer significant potential for advancing protein engineering and proteomics.
  • Current challenges include evolving proteins with specific activities and assigning functions to genomic proteins.

Purpose of the Study:

  • To review the types of high-throughput assays developed for protein engineering and proteomics.
  • To assess the progress towards engineering proteins with novel functions.
  • To evaluate the efficiency of assigning functions to thousands of proteins within a genome.

Main Methods:

  • Review of existing literature on high-throughput assay development.
  • Analysis of assay capabilities for protein evolution and functional characterization.

Related Experiment Videos

  • Discussion of strategies for applying assays to entire cDNA libraries.

    • Main Results:

    • Various high-throughput assays have been developed, demonstrating promise for protein engineering.
    • Significant advancements have been made in evolving proteins for specific applications, such as stereoselective esterases.
    • Progress is being made in developing methods for rapid functional assignment of proteins.

    Conclusions:

    • High-throughput assays are crucial for the future of protein engineering and proteomics.
    • Further development is needed to fully realize the potential of these assays for protein evolution and functional genomics.
    • The integration of high-throughput assays with genomic data will accelerate biological discovery.