Enzyme-Guided Classification of Fungal Eremophilane Biosynthetic Gene Clusters Provides a Predictive Framework for Structural Diversity

Abstract

Elucidating how oxidative tailoring enzymes generate structural diversity in natural products remains a major challenge, because their functions are difficult to predict directly from sequence information. Fungal eremophilanes (EMPs), which share a conserved bicyclic core yet exhibit extensive oxidative diversification, provide an ideal model system to address this problem. Here, we establish a systematic framework linking biosynthetic gene cluster (BGC) to EMP chemical diversity by integrating bioinformatics and chemoinformatics analyses. Analysis of 371 BGCs identified six groups defined by combination of key modification enzymes, which rationalize the major structural features of 195 reported EMPs. This framework enables prediction of core scaffolds and major oxidative modifications, thereby constraining the accessible chemical space of EMPs. It also facilitates structure-guided identification of candidate BGCs, including atypical or divergent clusters that are not readily identified by sequence similarity alone. Experimental validation of a predicted peribysin biosynthetic gene cluster further supported the predictive capability of this framework. Together, these results demonstrate that oxidative diversification in EMP biosynthesis follows a limited and interpretable set of transformation patterns and establish a generalizable strategy for constraining terpenoid chemical space from genomic information.