The Pre-Fit Mechanism
Linking Consciousness, Enzyme Catalysis, and Quantum Measurement
Sungchul Ji, Ph.D. (with ChatGPT assistance)
Emeritus Professor of Theoretical Cell Biology
Ernest Mario School of Pharmacy,
Rutgers University, Piscataway, NJ
1. Introduction
Science often advances by finding unexpected connections between seemingly unrelated domains.
In 2012, I proposed the pre-fit model of enzyme catalysis [1] — a departure from the traditional “induced fit” view [2] — which emphasized that functional matches between molecules occur not by deformation, but when fluctuating pre-existing conformations happen to align perfectly.
More than a decade later, this same principle appears to echo in the physics of quantum measurement and in the dynamics of neural networks during the emergence of consciousness. In this article, I will show how the pre-fit mechanism [1] can act as a bridge linking chemistry, physics, and mind.
2. The Pre-Fit Model in Enzyme Catalysis
In classical biochemistry, the induced fit model of Daniel Koshland (1958) describes enzymes as flexible molecules that reshape themselves to bind substrates [2].
The pre-fit model [1] I proposed in 2012 flips this script:
Enzymes exist in a vast ensemble of conformations due to Brownian motion.
The correct shape for catalysis already exists among these fluctuations.
When a substrate encounters this “pre-fit” conformation, catalysis occurs instantly.
This subtle shift removes the need for a structural “induction” and instead emphasizes dynamic coincidence [3] — the meeting of the right substrate with the right pre-existing enzyme shape.
3. Quantum Measurement as a Pre-Fit Process
The quantum world is also a realm of possibilities. A quantum system exists as a superposition of states, and a measuring device can interact with it in many possible ways.
In a pre-fit perspective:
The measuring apparatus samples an ensemble of possible interaction states (like enzyme conformations).
A “measurement” occurs when one of these apparatus states aligns perfectly with the quantum state, collapsing the wavefunction.
The act of measurement, then, is not about forcing change, but about matching — just as in enzyme catalysis.
4. Neural Networks and Conscio-genesis
The human brain exhibits continuous spontaneous neural activity [4] — random or patterned firings that occur even without sensory input. The default mode network (DMN) is one such example of organized resting-state activity.
In a pre-fit view of conscio-genesis (the emergence of consciousness):
Neural circuits explore a wide range of configurations.
When sensory input or internal signals align with one of these pre-existing configurations, large-scale integration occurs.
This alignment could correspond to the moment of conscious experience — a neural “measurement” of internal and external reality.
5. The Structural Isomorphism
The table below shows the mapping between the three domains:
6. Overcoming the Timescale Objection: The Generalized Franck–Condon Principle
One of the most persistent objections to linking quantum processes to brain function is the timescale mismatch:
Quantum coherence in biological systems typically lasts only ~10⁻¹⁰ seconds.
Neural processes, by contrast, operate on the scale of ~10⁻⁶ seconds — about 10,000 times slower.
How could processes so vastly separated in time possibly interact?
The answer lies in a principle I formulated in 1991 [7], known as the Generalized Franck–Condon Principle, or the Principle of Slow and Fast Processes:
Whenever an observable process, P, results from the coupling of two processes, one slow (S) and the other fast (F), with F proceeding faster than S by a factor of at least 10², the slow process must precede the fast process.
In enzymology, this means that conformational changes in enzymes (slow) occur before the quantum-chemical steps of bond rearrangement (fast). The pre-fit model naturally incorporates this principle:
The slow process = enzyme finding the right pre-fit conformation (10⁻⁶ s scale)
The fast process = quantum-chemical step of catalysis (10⁻¹⁰ s scale)
By analogy, in the brain:
The slow process = neural network reaching the right pre-fit configuration
The fast process = quantum event that triggers or stabilizes a conscious episode
This principle thus provides a mechanistic pathway for quantum processes to influence neural activity without violating timescale constraints.
7. Origin of the Pre-Fit Concept
The pre-fit model of enzyme catalysis was first introduced in my 2012 book [1], Molecular Theory of the Living Cell (Springer, pp. 209–214), as "The Kinetics of Ligand–Protein Interactions: The Pre-Fit Mechanism Based on the Generalized Franck–Condon Principle."
Its roots trace back to my 1991 [7] formulation of the Principle of Slow and Fast Processes in Molecular Theories of Cell Life and Death (Rutgers University Press, pp. 52–54), itself inspired by spectroscopy, where transitions occur without nuclear reorganization when vibrational states already match [5].
8. Why This Matters
If the pre-fit mechanism is truly universal, it could mean that:
Consciousness emerges via the same underlying dynamic principle as enzyme catalysis and quantum measurement.
The Principle of Slow and Fast Processes explains how quantum events can couple to neural processes despite huge timescale differences.
This may be a general law of self-organization in nature [6], reappearing from the subatomic to the mental scale.
9. Closing thought
Nature may not reinvent the wheel at every scale — instead, it may reuse the same elegant principles, from the chemistry of life to the physics of measurement to the biology of mind. The pre-fit bridge, grounded in the Principle of Slow and Fast Processes [7], could be one of those rare principles, whispering the same story in three scientific languages.
Conscio-genesis is a form of thermodynamic work that requires free energy dissipation. Enzyme catalysis is the only way free energy can be generated from chemical reactions, supplying free energy to living systems, thus making the pre-fit enzyme catalysis mechanism a necessary condition for conscio-genesis, or for connecting mind and matter [8].
References:
[1] Ji, S. (2012). The “Pre-fit” Mechanism Based on the Generalized Franck-Condon Principle. In: Molecular Theory of the Living Cell: Concepts, Molecular Mechanisms, and Biomedical Applications. Springer, New York. Pp. 209-214.
[2] Koshland, D. E., Jr. (1958). Application of a Theory of Enzyme Specificity to Protein Synthesis, Proc. Nat. Acad. Sci. USA 44, 98-104.
[3] Ji, S. (2012). Enzymes as Coincidence Detectors. Op. cit Pp. 220-222.
[4] Default Mode Network. https://en.wikipedia.org/wiki/Default_mode_network
[5] Franck-Condon principle. https://en.wikipedia.org/wiki/Franck%E2%80%93Condon_principle
[6] Self-organization. https://en.wikipedia.org/wiki/Self-organization
[7] Ji, S. (1991). Principle of Slow and Fast Processes. In: Molecular Theories of Cell Life and Death (S. Ji, ed.), The Rutgers University Press, New Brunswick, pp. 52-54.
[8] Ji, S. (2018). The Cell Language Theory: Connecting Mind and Matter. World Scientific Publishing, New Jersey.
Top of FormBottom of Form
Interesting connection. Did I correctly understand that all these processes are random and the meeting of an ideal configuration with the corresponding receptor would be due to chance? Thus the emergence of consciousness is also a random occurrence? Looking at the fractal construction of nature it is difficult for me to think of consciousness randomly popping up. I'd rather consider consciousness as an underlying field of coherence, favoring the meet and match process in metabolism.