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Preprint · bioRxiv · August 22, 2026

Sequence-Derived Representations versus Pfam-Domain Content for Biosynthetic Gene Cluster Retrieval

Rustambek Urokov, Asifullah Khan, Farkhod Eshboev, Dovud Asadov, Sejuti Rahman, Dilafruz Kushokova

Sejuti Rahman
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Abstract

Abstract Retrieving BGCs related to those of a known producer can be regarded as a representation-learning objective. We hypothesize that ESM-2 sequence-derived representations of BGCs can improve retrieval beyond the Pfam-domain content metric. Our toolkit is the following: group-disjoint train, validation, and test assignments, validation-frozen model selection, five seeds, and family-level paired inference. Of 6,953 atlas BGCs from 182 deduplicated Streptomyces griseus genome accessions, 5,325 silver-labeled BGCs are split into 98 training, 21 validation, and 21 test reference groups. Of the test reference groups, 16 are eligible for retrieval diagnostics. Pfam Jaccard scored Recall@50 of 0.8788, while Pfam-augmented BGC-SetNet scored 0.8472. The combination of ESM and Pfam-augmented BGC-SetNet scored 0.8769. A weighted Pfam Jaccard obtained a slightly higher score of 0.8789, which has a negligible difference compared to unweighted Pfam Jaccard. Our results do not support the claim that sequence-derived representations can recover alternative biosynthetic pathways on this benchmark. Instead, explicit Pfam remains the major signal for this objective. Our results define the curation and pathway-level validation processes that are necessary for a more robust biological test.

Microbial Natural Products and BiosynthesisGenomics and Phylogenetic StudiesComputational Drug Discovery Methodsbiosynthetic gene clustersStreptomyces griseusrepresentation learning

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