SYSTEM FOR IDENTIFYING AND DEVELOPING FOOD INGREDIENTS FROM NATURAL SOURCES BY MACHINE LEARNING AND DATABASE MINING COMBINED WITH EMPIRICAL TESTING FOR A TARGET FUNCTION

This disclosure provides a technology for developing individual proteins for use in industrial processes that include food production. The technology mines sequence data from protein databases by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression, and testing are done to yield potential ingredients suitable for use in the production of foods, cosmetics, agricultural feed, pharmaceutical excipients, and other industrial products.