Advancing yaws diagnosis through point of care diagnostics: A peptide-centric design approach

Abstract

Yaws, a chronic Neglected Tropical Disease (NTD) caused by Treponema pallidum subsp. pertenue, causes severe skin ulcers and bone damage if untreated, primarily affecting marginalized communities. Current diagnostics, like serology and microscopy, are impractical in endemic regions due to their reliance on lab infrastructure and trained personnel. To overcome this, we developed the first strain-specific, multi-epitope peptide-based diagnostic targeting unique T. p. pertenue genes (*tprA-L, arp, tp92*), enabling point-of-care detection. Using combinatorial bioinformatics (VaxiJen, ABCpred, IEDB) and structural validation, we predicted immunogenic B- and T-cell epitopes from 15 conserved genes (tprA–L, arp, tp92, recQ, mcp1–4) across six T. p. pertenue strains (SamoaD, CDC_2, Gauthier, Ghana_051, CDC_2575, LMNP). Twelve high-affinity peptides were identified with strong antigenicity and stability. Candidates were evaluated for solubility, codon optimization, and structural stability, followed by molecular docking to confirm binding affinity with human antibodies. Results showed exceptional binding characteristics (e.g., -364.74 kcal/mol for Tp92), surpassing prior treponemal biomarkers, with high confidence scores (>0.9). Our multi-target approach achieved 94.2% specificity and 88.5% sensitivity in silico, effectively distinguishing T. p. pertenue from related pathogens. This study provides a scalable, low-cost framework for field-deployable diagnostics, aligning with WHO’s 2030 eradication goals by enabling early detection in resource-limited settings. By merging computational design with translational feasibility, our work advances tropical disease diagnostics and offers a template for other NTDs with similar challenges.