Structure-based similarity network accelerates the discovery of lysins as oral microbiome modulators targeting periodontal pathogens

Yao, F.; He, J.; Nyaruaba, R.; Chen, F.; Zhou, J.; Yang, H.; Wei, H.; Li, Y.

doi:10.64898/2026.04.11.717860

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bioRxiv · 10.64898/2026.04.11.717860

Structure-based similarity network accelerates the discovery of lysins as oral microbiome modulators targeting periodontal pathogens

Yao, F.·He, J.·Nyaruaba, R.·Chen, F.·Zhou, J.·Yang, H.·Wei, H.·Li, Y.

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Abstract

Microorganisms significantly influence human health, and dysbiosis of the oral microbiome plays a critical role in the development and progression of both oral and systemic diseases. This highlights the urgent need for novel therapeutics targeting specific pathogens. Here, we presented a structure-based pipeline to efficiently identify potential phage-derived periodontal lysins (LysPds) from nearly one million proteins. We predicted the structures of candidate lysins using AlphaFold2 and developed an innovative structure-based similarity network to classify them into distinct clusters, each with unique functional properties. A systematic characterization of 16 representative LysPds from 11 superfamilies revealed that over 90% demonstrated potent antibacterial activity against key periodontal pathogens. Among these, LysPd078 was identified as a promising preclinical drug candidate, effectively reconfiguring microbiome communities while demonstrating significant efficacy and safety in mouse models of periodontitis and calvarial infection. Our findings highlight the effectiveness of structure-based similarity networks in exploring vast protein spaces and underscore the potential of LysPd078 as a targeted modulating agent for the oral microbiome.

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Yao, F., He, J., Nyaruaba, R., Chen, F., Zhou, J., Yang, H., Wei, H., Li, Y.. 2026-04-13. Structure-based similarity network accelerates the discovery of lysins as oral microbiome modulators targeting periodontal pathogens. https://doi.org/10.64898/2026.04.11.717860

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