ArticleJournal of computer-aided molecular design2026
QSAR, molecular dynamics, and biological evaluation of novel myeloperoxidase inhibitors via ligand-based pharmacophore modeling as potential anticancer agents.
Article in Journal of computer-aided molecular design, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors.
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Abstract
Myeloperoxidase (MPO) has shown promise as a therapeutic target due to its critical role in inflammatory mechanisms and cancer progression. Despite extensive research on MPO inhibitors, the lack of integrated computational-experimental workflows constrains the efficient identification and validation of biologically relevant candidates. Hence, in this study, a ligand-based pharmacophore model of MPO inhibitors was developed to identify crucial molecular features required for inhibition. A quantitative structure-activity relationship (QSAR) model was built using the Genetic Function Approximation (GFA) algorithm, and the model statistics were found to be statistically significant (R
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