Mechanism-First Phytochemical Therapeutics: Integrating Target Prediction, Pathway Enrichment, Phenotypic Effects, and Disease Network Biology

Download PDF

Phytochemical therapeutics occupy a difficult translational space because structurally diverse natural compounds often generate broad biological signals before their mechanisms are clearly established. Target prediction, pathway enrichment, phenotypic screening, and disease-network analysis each contribute useful mechanistic clues, but none can independently justify a therapeutic claim. This article develops an original mechanism-first framework for phytochemical therapeutics that prioritizes construction of testable mechanistic hypotheses before claims of efficacy, safety, or clinical relevance. The framework synthesizes four central evidence domains: predicted or associated targets, enriched or annotated pathways, observed phenotypic effects, and disease-network biology. It proposes that these evidence streams should be interpreted through contextual checks, uncertainty mapping, contradiction visibility, and validation-readiness assessment. The principal contribution is a qualitative mechanistic architecture that distinguishes predicted targets from target engagement, pathway enrichment from pathway modulation, phenotypic response from mechanism, and disease-network association from causal disease biology. The framework is intended to help researchers move from isolated computational or phenotypic outputs toward validation-ready therapeutic hypotheses, while remaining explicitly conceptual rather than experimentally validated.