Deep sequencing methods for protein engineering and design

Emily E. Wrenbeck, Matthew S. Faber, Timothy A. Whitehead

    Research output: Research - peer-reviewReview article

    • 3 Citations

    Abstract

    The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances.

    LanguageEnglish (US)
    Pages36-44
    Number of pages9
    JournalCurrent Opinion in Structural Biology
    Volume45
    DOIs
    StatePublished - Aug 1 2017

    Profile

    Protein Engineering
    High-Throughput Nucleotide Sequencing
    Proteins
    HIV-1
    Epitopes
    Genotype
    Phenotype
    DNA
    Enzymes
    Datasets

    ASJC Scopus subject areas

    • Structural Biology
    • Molecular Biology

    Cite this

    Deep sequencing methods for protein engineering and design. / Wrenbeck, Emily E.; Faber, Matthew S.; Whitehead, Timothy A.

    In: Current Opinion in Structural Biology, Vol. 45, 01.08.2017, p. 36-44.

    Research output: Research - peer-reviewReview article

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