UC Berkeley

Water pollution, climate change, and human health are among many critical challenges that biodegradable plastics can help solve. The ideal plastic can be rapidly produced in large volumes with flexible dimensionality, as well as rapidly degraded to molecular products to avoid micro- and nano-plastic generation. Synthetic polymers offer desirable production time- and length-scales while biological polymers have desirable degradation time- and length-scales. By blending biotic and abiotic components a single biohybrid material with both synthetic scalability and biological sophistication can be realized. Pre-programming over which function will be dominant at each timescale can be achieved by designing across molecular-to-macroscopic length scales. By nanoscopically dispersing enzymes in a hydrophobic polymer matrix that is also the substrate for biocatalysis, we achieve control over the resulting hybrid plastic’s degradation timescale. During production and use, the abiotic properties are dominant, until biotic functionality is controllably activated upon end-of-life by basic environmental triggers e.g., water. To fully unlock the economic and bioremediative potential of biohybrid, biodegradable plastics a fundamental scientific understanding of molecular mechanisms and biotic-abiotic interactions is required. Synthetic random heteropolymers (RHPs) are rationally designable chaperones that can modulate biotic-abiotic interfaces during both the production and degradation of plastics. RHPs are also a platform technology that, beyond biohybrid materials, can also independently recapitulate protein-like functions.Here, we elucidated the molecular-scale feedback loop between enzyme-catalyzed plastic degradation and molecular transport through an evolving, hierarchical, semi- crystalline plastic matrix. Modulating the enzyme-polymer interface resulted in polyester degrading enzymes that were thermostable in over 200 °C polymer melts, enabling industrially scalable biohybrid plastic production. To accelerate the design and optimization of RHPs as either protein chaperones or mimics, we built the RHPapp: a RAFT kinetic heteropolymerization simulator that feeds into a biocheminformatic sequence analysis framework. In silico generation of accurate heteropolymer sequences in lieu of sequencing technologies allows us to leverage the advances made in bioinformatics and artificial intelligence to lay a foundation for the burgeoning field of macromolecular cheminformatics.