Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids.

ABSTRACT: Polymer-protein hybrids are intriguing materials that can bolster protein stability in non-native environments, thereby enhancing their utility in diverse medicinal, commercial, and industrial applications. One stabilization strategy involves designing synthetic random copolymers with compositions attuned to the protein surface, but rational design is complicated by the vast chemical and composition space. Here, a strategy is reported to design protein-stabilizing copolymers based on active machine learning, facilitated by automated material synthesis and characterization platforms. The versatility and robustness of the approach is demonstrated by the successful identification of copolymers that preserve, or even enhance, the activity of three chemically distinct enzymes following exposure

SUBMITTER: Tamasi MJ 

PROVIDER: S-EPMC9339531 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature