Computational Theoretic Framework for Systematic Discovery of Druggable Targets in Trypanosoma cruzi
Year: 2025
Type: article
Abstract: The persistent therapeutic gap in Chagas disease stems from inadequate target validation frameworks that fail to systematically integrate biological essentiality with pharmacological tractability. We developed a structured, criteria-based "onto-epistemic" methodology that separates target definition from evidence validation through a quantitative, fail-fast pipeline. This approach establishes vulnerability through four ontological criteria while validating candidates through progressive epistemological testing. Applied to the Trypanosoma cruzi proteome, the framework achieves an 1,800-fold reduction from ~22,000 proteins to ten high-confidence targets, including TcP21, TcAkt_PH, and GP63. Statistical analysis confirms significant stage-dependent expression differences (F(3,116) = 130.15, p < 0.001, η² = 0.771), while sensitivity analysis demonstrates ranking robustness across diverse weighting schemes (mean Spearman correlation = 0.983 ± 0.016). The modular architecture enables adaptation across kinetoplastid species, providing a reproducible and transparent foundation for rational therapeutic development in neglected diseases.
DOI: 10.62162/sssp117261
Author: Richard Murdoch Montgomery
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4411498449