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The notion of data transparency is gaining a strong awareness among the scientific community. The availability of raw data is actually regarded as a fundamental way to advance science by promoting both integrity and reproducibility of research outcomes. Particularly, in the field of natural product and chemical research, NMR spectroscopy is a fundamental tool for structural elucidation and quantification (qNMR). As such, the accessibility of original NMR data, i.e., Free Induction Decays (FIDs), fosters transparency in chemical research and optimizes both peer review and reproducibility of reports by offering the fundamental tools to perform efficient structural verification. Although original NMR data are known to contain a wealth of information, they are rarely accessible along with published data. This viewpoint discusses the relevance of the availability of original NMR data as part of good research practices not only to promote structural correctness, but also to enhance traceability and reproducibility of both chemical and biological results.

High-throughput biology has contributed a wealth of data on chemicals, including natural products (NPs). Recently, attention was drawn to certain, predominantly synthetic, compounds that are responsible for disproportionate percentages of hits but are false actives. Spurious bioassay interference led to their designation as pan-assay interference compounds (PAINS). NPs lack comparable scrutiny, which this study aims to rectify. Systematic mining of 80+ years of the phytochemistry and biology literature, using the NAPRALERT database, revealed that only 39 compounds represent the NPs most reported by occurrence, activity, and distinct activity. Over 50% are not explained by phenomena known for synthetic libraries, and all had manifold ascribed bioactivities, designating them as invalid metabolic panaceas (IMPs). Cumulative distributions of ∼200,000 NPs uncovered that NP research follows power-law characteristics typical for behavioral phenomena. Projection into occurrence–bioactivity–effort space produces the hyperbolic black hole of NPs, where IMPs populate the high-effort base.

A recent article by Baell(1) on the problems experienced by medicinal chemists with pan-assay interference compounds (PAINS) and Shoichet’s work(2) on the impact of aggregation occurring in high throughput screening libraries, prompts a consideration of how these and other similar problems are experienced by pharmacognosists with promiscuous invalid metabolites as panaceas (PIMPs). Contrary to the classical definition of secondary metabolites as being species specific (or near specific), several natural products, particularly in the more extensively investigated plant kingdom, are common across species, genera, and even families (e.g. β-sitosterol). In the course of bioactivity-guided fractionation, PIMPs have shown up as major components in active fractions of a wide variety of pharmacological assays, i.e., they have been designated as panaceas. As in the case of PAINS, these assay results are almost invariably invalid and lead enthusiastic young scientists down a garden path. Why does this happen and how can it be avoided? Interestingly, the advances in modern methods of structure determination have exacerbated this problem, because it is possible to determine the structure of a compound when it is quite impure, and residual complexity is characteristic of chromatographic fractionation. That these residuals are often the source of the bioactivity is also frequently overlooked. Classic examples where this has occurred and ways to avoid it will be outlined.