I-Corps: Translation potential of a protein discovery platform for improving the functional properties of enzymes

This I-Corps project is based on the development of a discovery platform to optimize enzymes for industrial processes. Enzymes are proteins that act as biological catalysts by accelerating chemical reactions. Enzymes may be used in the chemical industry and other industrial applications including food and beverage processing, pharmaceutical and cosmetic production, animal feeds, textiles, paper production, and household cleaning products.

Currently, enzymes are limited by the number of reactions they can catalyze and also by their lack of stability in organic solvents and at high temperatures. To address these challenges, protein engineering has been developed to create new enzymes with novel properties. However, this technology is often hampered by the inability to specifically identify or design enzymes with the combination of properties needed to make the process both technically feasible and economically viable.

The aim of this discovery platform is to identify enzyme variants that have the required combination of properties to create new industrial enzymes with superior properties that will improve industrial processes.

This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a platform to identify regions of the amino acid sequence space that encode proteins for enzyme-based industrial processes. Proteins in nature occur as protein families that share similar amino acid sequences and three-dimensional structures but often have considerable functional diversity.

Biotech companies developing, producing, or using enzymes may encounter a protein from a protein family of interest exhibiting excellent stability but slow catalytic activity while another protein from this protein family has the opposite pair of functional characteristics (excellent catalytic rate but poor stability). Currently, it is challenging to obtain an enzyme that combines both desirable properties.

A process has been developed that may yield dually optimized enzymes. This approach provides an enhanced sampling approach to identify previously undiscoverable functional proteins in sequence space. The solution is applicable to any enzyme or protein activity for which an optical readout is available either for the purified protein or in cell-based assays and it may be used to achieve optimal combinations of a wide range of protein properties.

The goal of the technology is to identify variants of proteins and enzymes that exhibit a combination of enhanced properties. This enhanced sampling technology is based on the design and experimental study of a series of computationally derived proteins. The technology combines gene synthesis, high-throughput measurements of the properties of enzyme variants, and strategies to select the most informative sequences.

Such proteins may make enzyme-based industrial processes economically viable and yield proteins with superior properties for a range of biotechnology applications.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.