Identification of novel metagenomic lipases through integrated structural and sequence-based analysis

Enzymes, as key biocatalysts, are essential for advancing sustainable green technologies across diverse industrial sectors. The discovery of novel enzymes is essential for expanding their applications. In this study, we identified new lipases using an integrated screening strategy. This approach combines both structural and sequence-based methods on a large-scale metagenomic database. This strategy enabled the identification of new lipases with low sequence identity to known reference proteins. Our approach, therefore, circumvents the limitations of traditional sequence-only methods, which often fail to identify functionally similar enzymes with low sequence similarity. We first used Foldseek, a state-of-the-art structural homology search tool, to rapidly screen the database for proteins with structures similar to widely used lipases. This was followed by a rigorous sequence similarity filtering against public protein databases, yielding 711 putative novel lipases. We selected and experimentally validated three candidates, confirming their lipase activity. Further biochemical characterization revealed their notable properties including thermostability with optimal activity at 50-55 °C, and distinct alkaline activity profiles, maximal at pH of 8.0-9.0. Their unique properties, including high activity at elevated temperatures and alkaline pH, suggest potential for applications in detergent formulations, bioremediation, and industrial biocatalysis. Beyond identifying these promising enzymes, this study demonstrates the power of a combined structural and sequence-based approach for finding novel biocatalysts. This methodological innovation has broad implications for future enzyme discovery from metagenomic resources.