  Protein conformational transitions, which are essential for function, may be
driven either by entropy or enthalpy when molecular systems comprising solute
and solvent molecules are the focus. Revealing thermodynamic origin of a given
molecular process is an important but difficult task, and general principles
governing protein conformational distributions remain elusive. Here we
demonstrate that when protein molecules are taken as thermodynamic systems and
solvents being treated as the environment, conformational entropy is an
excellent proxy for free energy and is sufficient to explain protein
conformational distributions. Specifically, by defining each unique combination
of side chain torsional state as a conformer, the population distribution (or
free energy) on an arbitrarily given order parameter is approximately a linear
function of conformational entropy. Additionally, span of various microscopic
potential energy terms is observed to be highly correlated with both
conformational entropy and free energy. Presently widely utilized free energy
proxies, including minimum potential energy, average potential energy terms by
themselves or in combination with vibrational entropy\cite, are found to
correlate with free energy rather poorly. Therefore, our findings provide a
fundamentally new theoretical base for development of significantly more
reliable and efficient next generation computational tools, where the number of
available conformers,rather than poential energy of microscopic configurations,
is the central focus. We anticipate that many related research fields,
including structure based drug design and discovery, protein design, docking
and prediction of general intermolecular interactions involving proteins, are
expected to benefit greatly.
