Computational insights into the natural phage endolysin linker landscape.

Phage endolysins are increasingly investigated as novel protein-based antibiotics, offering solutions to the antibiotic resistance crisis. Endolysins targeting Gram-positive bacteria come in a variety of modular architectures, combining domains that bind the bacterial cell wall or enzymatically degrade it. While much research has focused on either understanding this multidomain architecture or leveraging it to create custom engineered lysins, far less is known about the oligopeptide linkers connecting their domains. Nevertheless, several engineering studies have observed a remarkable influence of the linker on lysin activity. In this work, we computationally investigated a broad set of Gram-positive endolysin linkers to bridge this knowledge gap. Relying on AlphaFold2-generated protein structural models, we collected 1072 linker sequences by finely delineating the domain limits using the SPAED tool, and described these through sixteen physicochemical and structural properties. Initial data exploration showed that endolysin linkers are highly diverse and feature similar amino acid compositions as previously described, general protein linkers. Subsequently, data mining and interpretable machine learning approaches were adopted to uncover the relationships between linkers and their endolysin domain architectures, as well as the associated phage host genus. These analyses revealed that such relationships do exist and are multidimensional in nature. Therefore, our findings provide evidence that the evolutionary pressure put on phages to adapt their lysis system to ever-changing environments and host requirements is not limited to the endolysin domains, but extends to the linkers connecting them. For instance, certain domain architectures were consistently associated with longer linkers, while others were highly stable. In summary, this work presents the first in-depth exploration of phage endolysin linkers, shedding light on their phage host- or domain architecture-specific design rules, and offering new perspectives for engineering endolysins as novel antimicrobials.