Natural Product Macrocycles Break Conventional Molecular Featurization Through Conformational Complexity, Stereochemical Dependence, and Nonclassical Structure–Activity Relationships

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Macrocycles challenge conventional molecular representation because their relevant properties depend less on a single static structure than on coupled stereochemistry, ring topology, conformational ensembles, intramolecular interactions, and environmental adaptation. This computational perspective examines why standard fingerprints, molecular graphs, and single-conformer descriptors become incomplete for natural-product macrocycles and cyclic peptides. The analysis integrates evidence on conformational sampling, chameleonicity, stereochemical encoding, dynamic polarity, membrane permeability, three-dimensional learning, and macrocyclic structure–activity relationships, while separating established observations from proposed computational implications. The central argument is that representation should be conditioned on the property being predicted and on whether that property is sensitive to molecular state, environment, or long-range ring organization. A proposed macrocycle-specific framework treats constitutional identity, stereochemistry, and ring topology as invariant information, with conformational-ensemble, environment-responsive, and uncertainty information added when mechanistically justified. Representation adequacy should be tested through matched ablations and scaffold-aware validation rather than inferred from model complexity. Principal limitations include the peptide-dominant evidence base, heterogeneous permeability measurements, force-field uncertainty, sparse coverage of nonpeptidic macrocycles, and limited prospective comparisons. This perspective defines a testable computational agenda rather than a validated universal standard, with prospective comparisons needed before any representation strategy can be preferred across macrocycle classes.