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Deep sequencing methods for protein engineering and design.

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.

SUBMITTER: Wrenbeck EE

PROVIDER: S-EPMC5440218 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Deep sequencing methods for protein engineering and design.

Wrenbeck Emily E EE Faber Matthew S MS Whitehead Timothy A TA

Current opinion in structural biology 20161122

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 mole ...[more]

PMID: 27886568

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