Aggregation, Protein
to achieve the native conformation of a
protein in a given environment is con-
tained in its amino acid sequence.’’ The
thermodynamic control of protein folding
was considered to be a corollary of the An-
Fnsen postulate, meaning that the native
structure is at a minimum of the Gibbs
free energy. This statement was discussed
by Levinthal in a consideration of the short
time required for the folding process
as well as
in vivo
a random search of the native conforma-
tion among all possible ones would require
an astronomic time and is therefore unre-
alistic. Thus, it is clear that evolution has
found an effective solution to this com-
binatorial problem. This is referred to as
the Levinthal paradox and has dominated
discussions for the last three decades.
In order to understand how the polypep-
tide chain could overcome the Levinthal
paradox, different folding models were
proposed and submitted to experimental
tests. Kinetic studies were carried out to
follow the folding pathway. A considerable
number of experiments were performed
to detect and characterize the folding in-
termediates. A stepwise sequential and
hierarchical folding process in which sev-
eral stretches of structure are formed and
assembled at different levels following a
unique route was supported by a major-
ity of scientists for many years. According
to this view, misfolded species could be
formed from folding intermediates leading
to the formation of aggregates in a kinetic
competition with the correct folding.
Progressively, with the development of
computers, theoretical studies have ap-
proached the folding problem, using sim-
pliFed models to take into account the
computational limitations in simulations
of the folding from the random coil to
the native structure. Different methods
were developed using either lattice models
or molecular dynamics simulations. In
the lattice model, the polypeptide chain
is represented as a string of beads on
a two-dimensional square lattice or on a
three-dimensional cubic lattice. The in-
teractions between residues (the beads)
provide the energy function for Monte
Carlo simulations. In such simpliFed mod-
els, the essential features of proteins, that
is, the heterogeneous character (hydropho-
bic or polar) of the interactions and the
existence of long-range interactions, were
included to explore the general character-
istics of the possible folds. Lattice models
were Frst applied to protein folding by Go
and coworkers while simple exact models
were initiated by Dill and his group, and
have been used by several theoreticians.
±rom the lattice simulations, insights into
possible folding scenarios have been ob-
tained, providing a basis for exploring the
general characteristics of folding for real
proteins. The exploration of such models
supplies useful information that can be
submitted to experimental tests.
The so-called ‘‘new view’’ has evolved
during the past 10 years from both experi-
ment and theory with the use of simpliFed
models. It is illustrated by the metaphor
of the folding funnel introduced in 1995
by Wolynes and coworkers. The model is
represented in terms of an energy land-
scape and describes the thermodynamic
and kinetic behavior of the transformation
of an ensemble of unfolded molecules to
a predominantly native state as illustrated
in ±ig. 1. According to this model, there
are several micropathways, each individ-
ual polypeptide chain following its own
route. Toward the bottom of the funnel,
the number of protein conformations de-
steeper the slope, the faster the folding.
As written by Wolynes et al., ‘‘To fold,
a protein navigates with remarkable ease
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