TY - JOUR
T1 - Structure-based statistical thermodynamic analysis of T4 lysozyme mutants
T2 - Structural mapping of cooperative interactions
AU - Hilser, Vincent J.
AU - Townsend, Benjamin D.
AU - Freire, Ernesto
N1 - Funding Information:
* Corresponding author. Tel. (410) 516-7743; fax (410) 516-6469; e-mail bcc@biocal2.bio.jhu.edu. ’ Supported by grants from the National Institutes of Health (RR04328 and GM51362).
PY - 1997/2/28
Y1 - 1997/2/28
N2 - The recent development of a structural parameterization of the energetics of protein folding has permitted the incorporation of the functions that describe the enthalpy, entropy and heat capacity changes, i.e. the individual components of the Gibbs energy, into a statistical thermodynamic formalism that describes the distribution of conformational states under equilibrium conditions. The goal of this approach is to construct with the computer a large ensemble of conformational states, and then to derive the most probable population distribution, i.e. the distribution of states that best accounts for a wide array of experimental observables. This analysis has been applied to four different mutants of T4 lysozyme (S44A, S44G, V131A, V131G). It is shown that the structural parameterization predicts well the stability of the protein and the effects of the mutations. The entire set of folding constants per residue has been calculated for the four mutants. In all cases, the effect of the mutations propagates beyond the mutation site itself through sequence and three-dimensional space. This phenomenon occurs despite the fact that the mutations are at solvent-exposed locations and do not directly affect other interactions in the protein. These results suggest that single amino acid mutations at solvent-exposed locations, or other locations that cause a minimal perturbation, can be used to identify the extent of cooperative interactions. The magnitude and extent of these effects and the accuracy of the algorithm can be tested by means of NMR-detected hydrogen exchange.
AB - The recent development of a structural parameterization of the energetics of protein folding has permitted the incorporation of the functions that describe the enthalpy, entropy and heat capacity changes, i.e. the individual components of the Gibbs energy, into a statistical thermodynamic formalism that describes the distribution of conformational states under equilibrium conditions. The goal of this approach is to construct with the computer a large ensemble of conformational states, and then to derive the most probable population distribution, i.e. the distribution of states that best accounts for a wide array of experimental observables. This analysis has been applied to four different mutants of T4 lysozyme (S44A, S44G, V131A, V131G). It is shown that the structural parameterization predicts well the stability of the protein and the effects of the mutations. The entire set of folding constants per residue has been calculated for the four mutants. In all cases, the effect of the mutations propagates beyond the mutation site itself through sequence and three-dimensional space. This phenomenon occurs despite the fact that the mutations are at solvent-exposed locations and do not directly affect other interactions in the protein. These results suggest that single amino acid mutations at solvent-exposed locations, or other locations that cause a minimal perturbation, can be used to identify the extent of cooperative interactions. The magnitude and extent of these effects and the accuracy of the algorithm can be tested by means of NMR-detected hydrogen exchange.
KW - Cooperative interactions
KW - Structural mapping
KW - Structure-based statistical thermodynamic analysis
KW - T4 lysozyme mutants
UR - http://www.scopus.com/inward/record.url?scp=0030993784&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0030993784&partnerID=8YFLogxK
U2 - 10.1016/S0301-4622(96)02220-X
DO - 10.1016/S0301-4622(96)02220-X
M3 - Article
C2 - 9127939
AN - SCOPUS:0030993784
SN - 0301-4622
VL - 64
SP - 69
EP - 79
JO - Biophysical Chemistry
JF - Biophysical Chemistry
IS - 1-3
ER -