A convenient model for estimating the total entropy (ΣS i ) of atmospheric gases based on physical action is proposed. This realistic approach is fully consistent with statistical mechanics, but uses the properties of translational, rotational and vibrational action to partition the entropy. When all sources of action are computed as appropriate non-linear functions, the total input of thermal energy (ΣS i T) required to sustain a chemical system at specific temperatures (T) and pressures (p) can be estimated, yielding results in close agreement with published experimental third law values. Thermodynamic properties of gases including enthalpy, Gibbs energy and Helmholtz energy can be easily calculated from simple molecular and physical properties. We propose that these values for entropy are employed both chemically for reactions and physically for computing atmospheric profiles, the latter based on steady state heat flow equilibrating thermodynamics with gravity. We also predict that this application of action thermodynamics may soon provide superior understanding of reaction rate theory, morphogenesis and emergent or selforganising properties of many natural or evolving systems.

An indirect competitive enzyme-linked immunosorbent assay (icELISA) for 12 phenylurea herbicides (PUHs) was established with the half-maximum inhibition concentration (IC(50)) of 1.7-920.7 μg L(-1). A method of computer-aided molecular modeling was established in quantitative structure-activity relationship (QSAR) studies to obtain a deeper insight into the PUHs' antibody interactions on how and which molecular properties of the analytes quantitatively affect the antibody recognition. A two-dimensional (2D)-QSAR model based on the Hansch equation and a hologram QSAR (HQSAR) model were constructed, and both showed highly predictive abilities with cross-validation q(2) values of 0.820 and 0.752, respectively. It was revealed that the most important impact factor of the antibody recognition was the PUHs' hydrophobicity (log P), which provided a quadratic correlation to the antibody recognition. Hapten-carrier linking groups were less exposed to antibodies during immunization; thus, groups of the analytes in the same position were generally considered to be less contributive to antibody recognition during immunoassay. But the results of substructure-level analysis showed that these groups played an important role in the antigen-antibody interaction. In addition, the frontier-orbital energy parameter E(LUMO) was also demonstrated as a related determinant for this reaction. In short, the result demonstrated that the hydrophobicity and the lowest unoccupied molecular orbital energy (E(LUMO)) of PUH molecules were mainly responsible for antibody recognition.

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Most immunoassays for determination of small molecules are still designed on the basis of the "trial and error" method, due to the lack of understanding of antibody recognition. In the present study, we developed a heterologous indirect competitive enzyme-linked immunosorbent assay for determination of triazine herbicides, with limits of detection for 11 triazines ranging from 0.05 to 29.4 μg/L. Mechanisms of the antigen-antibody interaction were studied by computer-aided molecular modeling (CAMM)-based quantitative structure-activity relationship analyses. Co-effects of the analytes' substructural hydrophobic, electrostatic, and steric fields on antibody recognition were further revealed. Hydrophobicity of the antigens was demonstrated to have the most important impact. Even less exposed substituents provided hydrophobic force to the antigen-antibody interaction. Dislocated orientation of analyte functional groups could lead to steric hindrance and hydrophobic misleading of antibody recognition. This may happen even when the antigens contained the same substituent as the hapten. Frontier orbital energies also affect the reaction significantly. This study highlights of the power of CAMM-based analyses, providing insights into antibody recognition of small molecules.

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