Lattice Protein Folding with Two and Four-Body Statistical Potentials
The cooperative folding of proteins implies a description by multibody
potentials. Such multibody potentials can be generalized from common
two-body statistical potentials through a relation to probability
distributions of residue clusters via the Boltzmann condition. In this
exploratory study, we compare a four-body statistical potential, defined
by the Delaunay tessellation of protein structures, to the
Miyazawa-Jernigan (MJ) potential for protein structure prediction using a
lattice chain growth algorithm. We use the four-body potential as a
discriminatory function for conformational ensembles generated with the MJ
potential and examine performance on a set of 22 proteins of 30 to 76
residues in length. We find that the four-body potential yields comparable
results to the two-body MJ potential, namely, an average coordinate
root-mean-square deviation (cRMSD) value of 8 A for the lowest energy
configurations of all-alpha proteins, and somewhat poorer cRMSD values
for other protein classes. For both two and four-body potentials,
superpositions of some predicted and native structures show a rough
overall agreement. Formulating the four-body potential using larger
datasets and direct, but costly, generation of conformational ensembles
with multibody potentials may offer further improvements.
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