Improving Protein Expression, Stability, and Function with ProteinMPNN.

ABSTRACT: Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs wi

SUBMITTER: Sumida KH 

PROVIDER: S-EPMC10811672 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature