(593c) Computationally Guided Approaches to Produce Biological Polymers

Melanin, a natural biopolymer known for its unique ability to absorb a wide range of radiations has been noted as a versatile material for coatings, absorbents, and even as a building material. However, the mechanisms by which melanins are synthesized are often environmentally unfriendly, expensive chemical synthesis, or inefficient due to cellular toxicity. In this work, using cell-free bioprototyping, ab-initio density functional theory (DFT) methods, and machine-learning enabled enzyme discovery, we rapidly generate enzymatic libraries of predicted melanin producing enzymes and combinatorially reconstitute them with substrate libraries to measure melanin polymerization. The use of cell-free bioprototyping allows for precise and complex biomolecular transformations to occur in crude lysates without cells and enables the construction of large datasets to produce novel materials. Beyond simply producing large amounts of melanin, this work makes use of high-throughput computational and cell-free synthetic biology techniques to rapidly test novel substrates, such as non-cannonical amino acids, as building blocks for new melanin-like materials.