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Mutational
experiments show how changes in the hydrophobic cores of proteins affect
their stabilities. We estimate these effects computationally, using four-body
likelihood potentials obtained by Simplicial Neighborhood Analysis of
Protein Packing (SNAPP). In this procedure, the volume of a known protein
structure is tiled with tetrahedra having the center of mass of one amino
acid side chain at each vertex. Log-likelihoods are computed for the 8855
possible tetrahedra with equivalent compositions from structural data
bases and amino acid frequencies. The sum of these four-body potentials
for tetrahedra present in a given protein yields the SNAPP score. Mutations
change this sum by changing the compositions of tetrahedra containing
the mutated residue and the related potentials. Linear correlation coefficients
between experimental stability changes and the corresponding changes in
the SNAPP score for hydrophobic core mutations in five different proteins
range from 0.70 to 0.94. Accurate predictions for the effects of hydrophobic
core mutations can therefore be obtained by virtual mutagenesis, based
on changes to the total SNAPP likelihood potential. Significantly, slopes
of the relation between DeltaG and DeltaSNAPP for different proteins are
statistically distinct. Comparable mutations of hydrophobic core residues
that imply the same change in stability therefore actually induce different
experimental values for DeltaG_unfold. This phenomenon results from systematic,
protein-specific effects, which can be estimated directly, using the average
SNAPP score per residue, which is readily derived from the analysis itself.
Slopes of the correlations are therefore inversely related to the mean
contribution of hydrophobic bonding to stability, providing a key for
scaling likelihood potentials to experimental values and estimating the
relative entropic contributions to stability in different proteins. This
result enhances the predictive value of statistical potentials and supports
previous suggestions that comparable mutations in different proteins may
lead to different DeltaGs because of differences in their
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