Rebuilding SAR from Fragmented Natural Product Evidence across Chemical Series, Assay Systems, Targets, and Contexts

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Structure–activity relationships are usually interpreted within deliberately constructed chemical series measured under reasonably controlled conditions. Natural-product evidence rarely has this architecture. Parent metabolites, congeners, biosynthetic variants, degradation products, semisynthetic derivatives, and mechanistic probes may instead be distributed across different publications, databases, laboratories, assay formats, target constructs, and endpoint definitions. An apparently sparse SAR may therefore represent a fragmented evidence problem in which observations cannot be pooled safely before chemical and experimental context are resolved. This article develops an original evidence-integration framework for rebuilding comparable local SAR from such records. The analysis separates chemical identity, scaffold relationship, assay state, target identity, mechanistic endpoint, potency representation, provenance, inactivity evidence, contradiction, and uncertainty rather than collapsing them into a single activity matrix. The central proposal is that structural relatedness and evidential comparability should be evaluated separately: close analogs can provide weak SAR evidence when experimental contexts differ materially, whereas records from different sources may support a defensible local relationship when identity and context are sufficiently aligned. Reconstructed SAR is therefore treated as context-tagged evidence rather than as a universally harmonized potency surface. The framework is intended to support auditable medicinal-chemistry reasoning and more defensible model training. It is not a validated reconstruction algorithm, does not define universal comparability thresholds, and cannot recover missing experimental states. Genuine activity cliffs, uncertain identities, incomplete metadata, context-dependent pharmacology, and missing negative evidence remain substantive boundaries.