| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Studies how enzymes catalyze biochemical reactions: mechanisms, kinetics, specificity, regulation, and structure–function relationships; excludes purely structural biology without catalytic context or metabolic pathway mapping without mechanistic focus. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates from atomic/electronic scales (transition states, catalytic residues, metal cofactors) to molecular (enzyme–substrate complexes), cellular (regulation), and organismal scales (metabolic integration). |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Enzymes, substrates, products, cofactors (NAD⁺, FAD, metal ions), transition states, intermediates, catalytic residues, regulatory molecules, allosteric sites, isoenzymes, enzyme–inhibitor complexes. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Catalytic efficiency (kcat/Km), binding affinity, turnover rate, specificity, allosteric responsiveness, thermodynamic stability, protonation states, redox states, conformational dynamics. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Enzyme classes (oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases), regulatory enzymes, multi-enzyme complexes, catalytic mechanisms (acid–base, covalent, metal-ion catalysis, etc.). |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Substrate concentration, enzyme concentration, pH, temperature, ionic strength, redox state, ligand concentration, conformational ensemble, catalytic-site protonation, cofactor availability. |
| | Parameterization | How variables encode and represent the system’s state. | States encoded via Michaelis–Menten parameters (Km, Vmax, kcat), inhibition constants (Ki), cooperativity coefficients (nH), activation energies, reaction-coordinate profiles, allosteric models, free-energy surfaces. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Steady-state approximation, rapid-equilibrium assumptions, two-state conformational models, single binding site, isolated reaction step, ideal reversible binding, no enzyme degradation, negligible substrate depletion. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Valid under controlled conditions (constant enzyme, moderate substrate), simple mechanisms; break down in multi-step reactions, strong allostery, cooperativity, high substrate turnover, enzyme instability, or complex cellular environments. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Enzymes lower activation barriers through defined mechanisms; binding is selective; catalytic residues act consistently; enzyme function follows kinetic and thermodynamic laws. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes meaningful kinetic parameters, stable active-site architecture, definable transition states, interpretable allosteric responses, and reliable mapping between structure, binding, and catalysis. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Requires coherence among kinetic data, mechanistic proposals, structural models, thermodynamic parameters, binding studies, and catalytic outcomes. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Demands alignment between enzyme structure, kinetics, thermodynamics, regulation, cofactors, and reaction pathways within a unified catalytic framework. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Reaction-rate changes, substrate depletion, product formation, absorbance/fluorescence shifts, heat release (calorimetry), pH changes, binding curves, stopped-flow transients, isotope effects, allosteric switching behaviors. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Limited by signal-to-noise ratio, low enzyme or substrate concentration, slow/fast reaction kinetics outside instrument range, overlapping spectral signals, weak binding, instability, or rapid conformational exchange. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Concentration (M), rate (M/s), velocity (v₀), catalytic constants (kcat, Km), inhibition constants (Ki), fluorescence intensity (a.u.), absorbance (a.u.), ΔH/ΔCp (cal/mol), pH, time (ms–min). |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Spectrophotometers, fluorimeters, stopped-flow kinetics instruments, ITC/DSC calorimeters, NMR, MS for product quantification, HPLC/UPLC, plate readers, microfluidic kinetic platforms, single-molecule FRET/force spectroscopy. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Reaction rate defined as slope of product/substrate vs time; Km and Vmax defined by Michaelis–Menten kinetics; kcat as turnover rate per enzyme molecule; inhibition types defined via Lineweaver–Burk/Eadie–Hofstee plots; allostery defined by changes in cooperativity parameters. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Enzyme assays, substrate titration, inhibitor titration, buffer optimization, pH/temperature scans, mixing and quenching protocols, steady-state vs pre-steady-state workflows, kinetic fitting procedures, isotope-labeling protocols. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Time-course sampling, continuous spectroscopic monitoring, rapid-mix experiments, temperature/pH-dependent runs, replicate kinetic traces, calorimetric scans, MS/HPLC product quantification, global fitting of kinetic traces. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Replicate enzyme assays, multiple substrate concentrations, repeated inhibitor dosing, triplicate kinetics runs, parallel tubes/plate wells, randomization of sample order, multi-timepoint sampling for transient kinetics. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Kinetic curves, steady-state plots (Michaelis–Menten, LB, EH), binding curves, calorimetric isotherms, isotopic-exchange plots, fluorescence time series, NMR/MS product distributions, single-molecule trajectories. |
| | Resolution | The granularity or precision with which data is captured. | Determined by detector precision, mixing dead-time, temporal sampling interval, wavelength selection, temperature stability, noise level, instrument bandwidth, and accuracy of concentration preparation. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Calibration of spectrophotometers, fluorimeters, calorimetric baselines, pH meters, MS/HPLC quantitation standards, pipette/balance calibration, enzyme concentration determination, extinction-coefficient verification. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Noise, baseline drift, enzyme instability, substrate degradation, pipetting error, temperature fluctuation, inner-filter effects, pathlength variation, incorrect kinetic model fitting, and non-ideal mixing artifacts. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Michaelis–Menten relationships, specificity rules, Brønsted–Evans–Polanyi correlations, catalytic triad logic, induced-fit and conformational-selection patterns, allosteric sigmoidal behavior, transition-state stabilization patterns. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Conserved catalytic residues, invariant reaction-coordinate motifs across enzyme families, conserved metal-binding geometries, stable active-site architecture, invariant catalytic mechanisms in homologous enzymes. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Acid–base catalysis, covalent catalysis, metal-ion catalysis, proximity/orientation effects, electrostatic stabilization, transition-state stabilization, conformational gating, cooperative activation/inhibition. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Substrate binding → conformational change → transition-state formation → product release → active-site reset; multi-step catalytic cycles; allosteric signaling pathways; covalent intermediate cycles; processive catalysis sequences. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Km, kcat, kcat/Km, catalytic proficiency, transition state (TS), reaction coordinate, induced fit, conformational selection, TS analogue, cooperativity, allostery, inhibition types, turnover number, activation energy, energy landscape. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Mechanistic enzyme classes (acid–base, metal-ion, covalent, general catalysis), EC classifications (1–6), inhibition classes (competitive/noncompetitive/uncompetitive/mixed), regulatory enzyme types (allosteric, covalent-modification, feedback-controlled). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Michaelis–Menten equation, Lineweaver–Burk, Eadie–Hofstee, Briggs–Haldane formalism, inhibition equations (competitive, mixed, etc.), Hill equation, Arrhenius/transition-state theory equations, free-energy relationships. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Enzyme–substrate binding models (lock–key, induced-fit, conformational selection), catalytic cycle models, TS stabilization models, energy-landscape models, kinetic models (steady-state, pre–steady-state), allosteric models (MWC/KNF). |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Perfect two-state folding, single binding site, isolated transition state, strict steady-state behavior, no off-pathway intermediates, no cooperativity, rigid enzyme scaffolds, no product inhibition. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Break down in highly cooperative enzymes, multi-step mechanisms, processive enzymes, mechanistically promiscuous enzymes, strong substrate depletion, complex cellular environments, and conformationally heterogeneous systems. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Integration of structural biochemistry, kinetics, thermodynamics, and regulation into one catalytic framework; unification of TS theory with conformational dynamics; linking enzyme structure → mechanism → regulation → physiology. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Intersects with structural biology, molecular biology, metabolism, medicinal chemistry (enzyme inhibitors), biophysics, evolution, chemical biology, and systems biology (flux through enzymatic networks). |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Controlling substrate/enzyme concentrations, pH, temperature, ionic strength, cofactors, inhibitors, mixing dead-time, and reaction environment to measure catalytic rates, mechanisms, and regulation with precision. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Monitoring spontaneous activity decay, passive conformational drift, autoxidation, background hydrolysis, slow allosteric transitions, or natural substrate depletion without deliberate perturbation. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Comparing predicted kinetic constants, inhibition patterns, catalytic mechanisms, conformational models, isotope effects, and TS predictions with experimental kinetic, binding, and structural data. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Repeating kinetic assays, titration series, inhibitor screens, temperature/pH scans, transient-kinetic runs, calorimetric scans, and MS/HPLC product quantification across replicates and batches. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Calculating Km, Vmax, kcat, Ki, Hill coefficients, activation energies, confidence intervals, uncertainty in rate constants, model fit statistics, and significance of cooperativity or inhibition signals. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Evaluating Michaelis–Menten vs Briggs–Haldane, competitive vs mixed inhibition, two-state vs multi-state conformational models, TS-analogue predictions, and kinetic vs structural-mechanistic models. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying enzyme instability, substrate degradation, background reactions, pipetting errors, temperature drift, optical inner-filter effects, misfit to kinetic equations, and instrument noise in time-resolved data. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Randomizing assay order, using blinded sample labels, performing blank and control assays, validating enzyme concentration, standardizing buffers, minimizing operator bias in selecting kinetic models. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Independent review of kinetic fits, inhibition classifications, mechanistic models, transient-kinetic interpretations, isotope-effect claims, and calorimetric/structural support for proposed mechanisms. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Revising mechanistic schemes, redefining catalytic steps, updating conformational models, adjusting kinetic assumptions, refining TS models, and incorporating contradictory evidence into new catalytic frameworks. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full disclosure of assay conditions, enzyme purity, kinetic-fitting methods, raw traces, structural assumptions, replicates, statistical treatment, limitations, and potential sources of ambiguity. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Honest reporting of uncertainties, ambiguous kinetic regimes, enzyme instability, failed inhibition screens, negative results, reproducibility limits, and adherence to biochemical-safety and data-integrity standards. |