Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry

Abstract

A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.

Combinatorial design of chemical‐dependent protein switches for controlling intracellular electron transfer

“…The pioneering studies by Frances Arnold and coworkers revealed that artificial proteins can be created in the lab by mimicking evolution In this directed evolution approach, proteins with novel functions are discovered by creating combinatorial libraries of mutants and mining those libraries for biomolecules with the desired functional properties using a selection or a screen. In cases where large fitness jumps are desired, libraries encoding topological mutants of proteins are increasingly used, such as random domain insertion libraries for creating protein switches . Several library approaches have been described for generating domain insertion libraries, including nuclease‐based and transposase‐mediated methods .…”

Family permutation profiling identifies a dynamic protein domain as functionally tolerant to increased conformational entropy

“…Deep mutational scanning is increasingly used to analyze the contributions that individual residues make to protein function (22,24,51). This approach has identified residues that underlie protein solubility (52), protein-protein interactions (53,54), membrane protein insertion (55), thermostability (56)(57)(58), substrate specificity (59), enzymatic function (56), and mutational epistasis (60).…”

“…One challenge with studying the effects of mutations on structure, function, and dynamics across a protein family is the limited throughput of in vitro measurements. In contrast, cellular selections represent a simple approach for rapidly assessing the functional tolerance of many mutations in parallel (21)(22)(23), although this approach yields more limited biophysical insight. With cellular assays, profiles of functional tolerance can be rapidly generated by creating a library of mutants, using a high-throughput assay to enrich for mutants that are active, sequencing the library of mutants before and after functional analysis, and calculating the relative abundance of each sequence following the functional enrichment (21,22,24).…”

“…In contrast, cellular selections represent a simple approach for rapidly assessing the functional tolerance of many mutations in parallel (21)(22)(23), although this approach yields more limited biophysical insight. With cellular assays, profiles of functional tolerance can be rapidly generated by creating a library of mutants, using a high-throughput assay to enrich for mutants that are active, sequencing the library of mutants before and after functional analysis, and calculating the relative abundance of each sequence following the functional enrichment (21,22,24). Changes in the abundances of each sequence can be used to estimate biological activity of each mutant by calculating a fitness score (25)(26)(27).…”

“…Changes in the abundances of each sequence can be used to estimate biological activity of each mutant by calculating a fitness score (25)(26)(27). To date, this approach has been applied to a wide range of proteins (21)(22)(23)(24)(25)(26)(27).…”