| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Studies chemical compounds produced by living organisms, including their structures, biosynthesis, reactivity, and isolation; excludes synthetic analogs unless derived from natural scaffolds. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates from atomic/electronic structure of complex scaffolds to organismal and ecological scales where biosynthetic pathways, regulation, and metabolic networks are relevant. |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Primary/secondary metabolites, polyketides, terpenes, alkaloids, peptides, glycosides, cofactors, biosynthetic enzymes, intermediates, precursors, chiral pool building blocks. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Stereochemical complexity, functional-group density, bioactivity, solubility, oxidation state, hydrogen-bonding patterns, conformational constraints, stability in biological environments. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Terpenoids, polyketides, alkaloids, phenylpropanoids, nonribosomal peptides, ribosomal peptides, carbohydrates, lipids, shikimate-pathway products, mixed biosynthetic hybrids. |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Concentration, pH, temperature, solvent polarity, biosynthetic flux, oxidation state, metabolite pool composition, enzyme availability, stereochemical configuration, conformation. |
| | Parameterization | How variables encode and represent the system’s state. | States encoded via biosynthetic pathways, enzyme–substrate specificity, stereochemical descriptors, isotopic labeling patterns, NMR parameters, MS fragmentation fingerprints, bioactivity metrics. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Idealized biosynthetic logic, step-by-step pathway assumptions, simplified conformational models, neglect of alternative enzyme promiscuity, perfect regio-/stereocontrol, isolated enzyme systems. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Hold in purified enzymatic systems, stable isolates, moderate pH ranges; break down in vivo under competing pathways, regulatory complexity, cofactor limitations, or dynamic metabolite pools. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Natural structures arise from definable biosynthetic logic; functional groups reflect evolutionary optimization; reactivity follows standard organic/biochemical principles. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes stable stereochemical assignments, consistent enzyme selectivity, predictable tailoring reactions, meaningful mapping from genome to metabolome, and reliable structural elucidation. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Requires alignment among biosynthetic logic, structural elucidation data, stereochemical assignments, functional-group patterns, and observed bioactivity. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Demands coherence between biological function, biosynthesis, molecular structure, chemical reactivity, and ecological/evolutionary context. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | UV–Vis absorption, NMR signatures, MS fragmentation patterns, optical rotation, chromatographic behavior, bioactivity profiles, color changes, precipitation, enzyme-mediated transformation. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Limited by low natural abundance, instability of metabolites, weak or overlapping NMR signals, trace-level MS detection, fast degradation in extraction, and low bioactivity signals. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Chemical shift (ppm), m/z, retention time (min), optical rotation (°), concentration (mg/mL or µM), bioactivity values (IC₅₀/EC₅₀), UV absorbance (a.u.), isotopic ratios, pH, temperature. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | NMR, HRMS/MS, GC/LC-MS, UV–Vis, IR, CD, X-ray crystallography, HPLC, SPE cartridges, bioassay platforms, LC–MS/MS metabolomics tools, cryoprobes, MS imaging tools. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Structural identity defined via NMR/MS; purity via chromatographic isolation; stereochemistry via NOE/CD/X-ray; bioactivity via IC₅₀/EC₅₀; biosynthetic origin via isotopic incorporation. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Extraction, solvent partitioning, solid-phase purification, chromatography, fractionation, dereplication workflows, spectral acquisition, bioassay-guided fractionation. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Sequential fraction collection, multi-step purification, high-resolution MS scans, 2D NMR acquisition (COSY, HSQC, HMBC), isotopic labeling studies, repeated bioassay measurements. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Repeated extraction from biological material, replicate fractions, multiple NMR scans, redundant MS injections, biological replicates in bioactivity assays, time-series metabolomics sampling. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | NMR spectra, MS fragmentation trees, UV–Vis traces, IR profiles, chromatograms, bioactivity curves, isotopic labeling patterns, structural elucidation packets, metabolomic feature tables. |
| | Resolution | The granularity or precision with which data is captured. | Determined by NMR field strength, MS mass accuracy, chromatographic efficiency, detector sensitivity, bioassay window, isotopic-resolution capability, and noise floor in low-abundance detection. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Calibration of MS (mass accuracy), NMR referencing, optical rotation zeroing, chromatographic retention calibration, bioassay plate controls, isotopic-standard referencing, purity benchmarks. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Identifying overlapping peaks, co-elution, sample degradation, matrix effects, ion suppression in MS, noise in NMR, biological assay variability, stereochemical misassignment risk, and contamination. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Biosynthetic logic patterns (polyketide assembly rules, terpene cyclization patterns), conserved functional-group motifs, predictable oxidation-state progressions, stereochemical inheritance rules. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Invariant carbon skeletons across biosynthetic families, preserved relative stereochemistry in terpene and polyketide scaffolds, conserved ring-forming logic, stable biosynthetic building blocks. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Enzyme-mediated cyclizations, tailoring reactions (oxidation, methylation, glycosylation), radical SAM transformations, concerted pericyclic-like biosynthetic events, acyl transfer, C–C bond assembly. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Polyketide assembly-line pathways, terpene cyclization cascades, shikimate/phenylpropanoid pathways, nonribosomal peptide assembly, glycosylation sequences, hybrid biosynthetic branch points. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Biosynthetic gene clusters, starter/extension units, chain-elongation logic, tailoring enzymes, chemotaxonomy, scaffold hopping, bioactivity motifs, conserved fold families, macrocyclization. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Natural product families (terpenes, alkaloids, polyketides, peptides, phenolics), pathway types (polyketide synthases, terpene synthases, NRPS/PKS hybrids), structural classes (macrocycles, steroids). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Isotopic labeling equations, kinetic isotope-effect expressions, biosynthetic flux equations, rate equations for enzyme steps, equilibrium relationships in tailoring reactions. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Biosynthetic pathway models, enzyme active-site models, genome-to-metabolome prediction models, stereochemical mapping models, computational docking/QM/MM models for enzyme–substrate interactions. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Idealized linear biosynthetic logic, perfect substrate channeling, rigid scaffolds, single-conformation binding, simplified oxidation patterns, truncated active-site simulations. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Break down with enzyme promiscuity, cryptic pathways, multiple stereochemical outcomes, structural flexibility, environmental variation, mixed biosynthetic hybrid pathways, or radical rearrangements. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Integration of biosynthesis, structure, and bioactivity; unified logic connecting genomic information to chemical scaffolds; cross-family biosynthetic rules; structure–function–biosynthesis triads. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Connects to biochemistry, chemical biology, medicinal chemistry, ecology, evolutionary biology, metabolomics, computational biosynthesis, and natural products drug discovery. |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Controlling extraction conditions, solvent systems, pH, temperature, enzyme activity, biosynthetic precursor feeding, fermentation conditions, and light/oxygen exposure to test structural or biosynthetic hypotheses. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Monitoring natural metabolite accumulation, spontaneous oxidation/reduction, degradation, ecological biosynthetic variation, gene-expression-dependent metabolite shifts without imposed perturbation. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Comparing predicted structures with NMR/MS data, testing biosynthetic hypotheses through isotopic labeling, validating pathway steps using enzyme assays, verifying activity–structure correlations. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Repeating extractions, chromatographic separations, bioactivity assays, NMR/MS scans, isotopic labeling experiments, fermentation runs, and enzymatic assays across independent batches and labs. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Extracting structural assignments from spectral data, deriving stereochemistry from NOE/CD/X-ray, estimating biosynthetic flux from isotopic incorporation, fitting dose–response or binding curves. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Evaluating competing structural proposals, biosynthetic pathway models, sequence–structure predictions, catalytic mechanisms, and metabolic network models based on predictive accuracy and consistency. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying spectral overlap, co-elution, sample degradation, ion suppression, matrix effects, enzyme instability, false positives in bioassays, and misassignments in stereochemistry or connectivity. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Using blinded structure interpretation, randomized fraction testing, standardized extraction protocols, consistent bioassay conditions, strict environmental controls, and reproducible purification workflows. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Independent structural re-assignment, cross-lab confirmation of bioactivity, critique of biosynthetic logic, verification of isotopic-labeling interpretation, and third-party spectral review. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating structural assignments, revising biosynthetic pathways, reclassifying metabolite families, correcting stereochemical models, and redefining structure–activity relationships when new data contradict prior conclusions. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full disclosure of extraction conditions, purification steps, bioassay methods, spectral-processing protocols, isotopic-labeling procedures, computational assumptions, and data-handling workflows. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Honest reporting of rarity, bioactivity levels, unsuccessful isolations, ambiguous spectra, environmental collection data, and maintaining ethical sourcing of biological materials. |