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bioRxiv · 10.1101/2025.06.21.660876

Bioinformatic Mining of Novel Lipopeptides Enabled by Daptomycin Cs Domain and Structural Modeling

Zhu, H.
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Abstract

Amidst the escalating crisis of antibiotic resistance, lipopeptides have emerged as promising therapeutic candidates due to their unique amphipathic structures. In this study, we developed a systematic bioinformatic platform using the condensation starter (Cs) domain of daptomycin as a molecular probe. Sequence similarity network (SSN) analysis identified 613 potential lipopeptide biosynthetic gene clusters (BGCs), with 432 (70.5%) originating from Streptomyces species. Subsequent integration of antiSMASH boundary prediction and evolutionary analysis prioritized 33 candidate BGCs harboring multiple post-modification modules. Five novel BGC types were ultimately selected based on Cs domain homology (<40% identity) and modification complexity. AlphaFold3 modeling revealed that WP_386473946.1 possess distinctive loop architecture, an expanded catalytic cavity, and a unique Asp60-Ala90 structural unit. Crucially, glycine residues adjacent to the conserved HHxxDG motif in the active pocket provide key targets for substrate recognition and rational engineering. This work delivers structure-guided genomic resources and molecular blueprints for accelerated discovery of antidrug-resistant lipopeptides.

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Zhu, H.. 2025-06-26. Bioinformatic Mining of Novel Lipopeptides Enabled by Daptomycin Cs Domain and Structural Modeling. https://doi.org/10.1101/2025.06.21.660876

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