PhagePickr: A bacteria-centric computational tool for designing resistance-aware phage cocktails

PhagePickr designs resistance-aware phage cocktails for ESKAPE pathogens by selecting phages using bacterial surface receptor similarity and prioritizing genomic diversity to reduce cross-resistance risk.

• Why it matters: Antibiotic resistance increases the need for phage therapy, but bacterial evolution toward phage resistance limits effectiveness. Existing cocktail-design tools do not explicitly account for resistance evolution driven by variable bacterial receptors.
• What they did: The pipeline uses receptor annotations with a nearest-neighbor algorithm to find phenotypically similar hosts and multiple sequence alignments to enforce genomic diversity in the final cocktail. It was evaluated on ESKAPE pathogens and two understudied bacterial species.
• The result: Cocktails generated with receptor similarity and phage genomic divergence included lytic phages with confirmed therapeutic potential and novel candidates from similar species, and the approach can scale as databases update.

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