Deep sequencing methods for protein engineering and design

• Deep sequencing permits examination of local protein fitness landscapes.
• NGS aids in engineering affinity and specificity for protein molecular recognition.
• Application to enzymes is limited by paucity of functional selections.
• NGS enables fundamental studies of enzyme behavior and evolution.
• Gene tiling and molecular barcoding extend NGS to full-length proteins.

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.