Deep sequencing methods for protein engineering and design

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

Research output: Contribution to journalReview article

  • 11 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

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: Contribution to journalReview article

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