A unified pipeline for discovering previously unknown enzyme activities

Abstract

Abstract Enzymes catalyze diverse chemical transformations and offer a sustainable approach to both breaking and making chemical bonds. However, finding an enzyme capable of performing a specific chemical reaction remains a challenge. We developed a new framework, Enzyme-toolkit (Enzyme-tk), that integrates 23 open-source tools to enable the discovery of enzymes that have activity toward a specific target reaction. Additionally, we introduce two new methods to facilitate enzyme discovery: (1) Func-e, an ML tool that searches large databases for enzymes that potentially catalyze a specific chemical transformation and (2) Oligopoolio, a gene assembly approach that reduces the cost of accessing protein sequences and thus the barrier to their experimental validation. We applied Enzyme-tk to find enzymes for chemical degradation of two man-made pollutants, di-(2-ethylhexyl) phthalate (DEHP) and triphenyl phosphate (TPP). We demonstrate that new, previously unannotated enzymes with favorable characteristics, such as high thermostability, can be identified using Enzyme-tk for reactions that are dissimilar to the training set.