Uses of enthalpy-entropy compensation in protein research

Cooperative systems of proteins and small molecules form most of biology but are so weakly linked that conventional mass-law formalism requiring exact stoichiometry is inapplicable. The weaknesses cannot be eliminated but using selected families of reactions useful fragmentation of those quantities is often possible. Extra-thermodynamic treatments based on linear-free-energy relationships (LFE) are developed to utilize enthalpy, entropy and volume information not otherwise reliable Linkage systems build around mesophilic proteins are well suited to enforced marriage of linear equations and scaled molecule detail because the ratio of substructure sizes on which folded stability depends is independent of total number of amino-acid residues. Conformational changes in physiological function usually no greater than 0.5 A closely scale to linear thermodynamic changes. The formalisms for use of LFE and compensation relationships are modified to eliminate complications that have previously arisen from incorrect inclusion of the thermal parts of enthalpy and entropy changes in free energy changes. The results are used to remove current confusion about the basis of folded stability in proteins and to minimize the quantitative errors arising from classical treatments of denaturation data. The enthalpy to entropy ratio given by the slope of a compensation plot (its 'compensation temperature') is used to characterize protein construction and function so as to extract machine descriptions of protein linkage systems. In this way the 'fragile' nature of the free-energy surfaces of the myoglobin proteins and the 'strong' character of those surfaces of most other mesophiles can be deduced very simply from the Debye-Waller factors obtained in diffraction studies. The major evolutionary achievement in making proteins big is their crystallike phase behavior. That makes entropy exactly as important as enthalpy so the scalar quantities of small-molecule chemistry can be replaced by the vector quantities that appear necessary to make biology possible.