What Is Life? - Molecular Theory of the Living Cell - page 569

Table 16.2 Active and passive phase transitions in physics and biology. N ¼ Avogadro number

Physics Biology

1. System Physical Biological (e.g., cells)

2. Homogeneity Homogeneous Heterogeneous

3. Observables
averaged over n

n~N n N

<<

4. Examples Freezing of water to ice Enzyme catalysis

Magnetization Activated metabolic pathways

Liquid crystals Lifting of weights powered by

ATP hydrolysis

5. Intensive variable Temperature Information density (?)

Pressure
Mass density
6. Order parameter Translational degree of freedom Patterns of distributions of RNA
trajectories (see Figs. 12.1 and
12.2 a )

Magnetization

7. Correlation Spatial Temporal

8. Mode Passive (i.e., approach

to equilibrium)

Active (i.e., driven away from
equilibrium by chemical reactions)

9. Key variables Gibbs free energy Gibbs free energy and genetic

information (see Sect. 4.3 )

10. Mechanisms Self-assembly (equilibrium

structures or equilibrons )

Self-organization (dissipative
structures or dissipatons )

its transient state of orderly motions required by the catalytic act, paid for by the
free energy of the reaction it catalyzes. Hence, we can consider enzymic catalysis as
an example of a phase transition where the correlations among events (in contrast
to structures) occur not only along the spatial dimensions as in physics but also
along the time dimensions . In other words, the essence of enzymic catalysis may be
the “freezing out” of the transient, thermally activated conformations of the enzyme
needed for catalysis for the time durations much longer than are allowed for by the
second law of thermodynamics by utilizing conformational energy (or conformons)
stored in enzymes. This is why we can view catalysis as an “active” form of phase
transition in contrast to the traditional phase transitions studied in physics which are
viewed here as “passive” phase transitions. The fundamental difference between
passive and active phase transitions may be that physical phase transitions are
driven by free energy (a function of energy and entropy), whereas biological phase
transitions are driven by both free energy and genetic information resulting from
the selection inherent in biological evolution, thus justifying the neologism, “info-
statistical mechanics” discussed in Sect. 4.9 .
The intensive variables in the physics of critical phenomena, that is, passive phase
transitions , are temperature, mass density, and pressure. The intensive variable for
active phase transitions is proposed here to be the biological (or genetic) information
encoded in the structures of biopolymers that allows biopolymers to undergo long-
range interactions mediated by stereospecific ligands (e.g., see the garage-door mech-
anism described in Table 11.12 ) . The order parameter in passive phase transitions
captures the order-disorder properties of intermolecular interactions. In contrast,