Subcellular Systems - Molecular Theory of the Living Cell - page 290

In April 2004, I had the privilege of attending a lecture on protein folding given
by P. Wolynes at Rutgers. After his lecture, it occurred to me that the folding funnel
theory as now formulated might lack a “biological dimension,” because the theory
seems to be based on the fundamental assumption that protein folding is driven by
the tendency of proteins to minimize Gibbs free energy (cf., the “principle of
minimal frustrations” [Bryngelson and Wolynes 1987]) in contrast to the alternative
possibility that proteins in living cells have been selected by evolution not based on
free energy minimization but rather based on their biological functions , regardless
of their free energy levels. Their biological functions in turn would depend on their
three-dimensional molecular shapes (Ji and Ciobanu 2003). When I asked Dr.
Wolynes whether it would be possible to expand his two-dimensional folding
funnel diagram (similar to the one shown in Fig. 11.1 , wherein the y -axis encodes
energy, E, and the x -axis encodes entropy, S) by erecting a z -axis perpendicular to
the xy -plane to encode genetic information, I, the effects of biological evolution on
protein folds, he did neither object nor explicitly endorse the idea. However, he
did acknowledge the importance of taking into account biological evolution in
theorizing about protein folding. Such an extension of the protein folding funnel
model would bring protein folding processes within the purview of what was
referred to as the info-statistical mechanics defined in Sect. 4.9 .
The “folding funnel” model is also called “energy landscape” model. One way to
incorporate biological evolution (and hence the genetic information) into the
energy landscape theory of protein folding may be to identify the topology (i.e.,
surface shape) of the energy landscape as the extra dimension for encoding the
effects of biological evolution. Although no proof is yet available, it seems that
there may be a good correlation between the degree of the bumpiness or frustrations
(Bryngelson and Wolynes 1987) of the energy landscape and the genetic informa-
tion encoded in amino acid sequence of proteins, if the bumpiness somehow
contributed to the fitness of the cell under given environmental condition and
thus affected the I value (see below). The bumpier the surface of the energy
landscape of a protein, the higher would be its information content of the Shannon
type (Klir 1993). Thus, the notion of “bumpy folding funnel” may embody the
following three elements
1. E, energy encoded in the depth of the funnel
2. S, entropy encoded in its width
3. I, genetic information encoded in the “bumpiness” or “ruggedness” of the funnel
surface
The protein folding theory incorporating these three elements, E, S, and I, as
described here may be referred to as the “information-energy landscape” theory of
protein folding (“entropy” being included as a part of “energy,” an abbreviation for
“free energy”) to contrast with the now widely accepted “energy landscape” theory
of protein folding. It is my opinion that the “energy landscape theory” of protein
folding is a physical theory and not a biological one, since there is no role (or room)
for genetic information and, hence, biological evolution in it. To transform the
energy landscape theory into a biological theory, it may be necessary to combine it