Energy-related descriptors

Platts, J. A., Butina, D Abraham, M. H., Hersey, A. Estimation of molecular linear free energy relation descriptors using a group contribution approach. /. Chem. Inf. Comput. Sci. 1999, 39, 835-845. 

Platts, J.A., Butina, D., Abraham, M.H. and Hersey, A. (1999). Estimation of Molecular Linear Free Energy Relation Descriptors Using a Group Contribution Approach. J.Chem.Inf.Com-putScL, 39, 835-845. 

QUANTUM-CHEMICAL MOLECULAR DESCRIPTORS 2.1. Energy-Related Descriptors... 

In Table 6.8, atom type-specific subset correlations of AMI, PM3, PM5, and HF with B3LYP are shown for frontier orbital energies and related descriptors, for parameters based on the charge distribution, and for the PPSA and PNSA descriptors. In contrast to Table 6.4 and Table 6.7, however, now all compounds providing a zero descriptor value by definition (e.g., PPSA-1Z = 0 if, for a given method, the compound has no positively charged heavy atom) were included for generating the statistics. 

Fig. 2. Computation of Volsurf descriptors (Cruciani et al. 2000a) derived from GRID molecular interaction fields. For any molecule, interactions with GRID water and dry probes at different energy levels are used for contouring. Those levels serve to compute vectors of 72 volume, size, and surface related descriptors.

Recently, Riviere and Brooks (2007) published a method to improve the prediction of dermal absorption of compounds dosed in complex chemical mixtures. The method predicts dermal absorption or penetration of topically applied compounds by developing quantitative structure-property relationship (QSPR) models based on linear free energy relations (LFERs). The QSPR equations are used to describe individual compound penetration based on the molecular descriptors for the compound, and these are modified by a mixture factor (MF), which accounts for the physical-chemical properties of the vehicle and mixture components. Principal components analysis is used to calculate the MF based on percentage composition of the vehicle and mixture components and physical-chemical properties. 

The relationship between individual components appears to indicate that the first and second SaSA dimensions can be related to the first and third ALMOND dimensions, with an emphasis on the first component. The first SaSA component is dominated by size-related descriptors, e.g., the total number of heavy atoms, MW, CMR, and polarizability. These properties explain approximately 60% of the first ALMOND component, suggesting that large internode distances and high internode interaction energies dominate this component. The third ALMOND component has a weaker relationship (25%) to hydrophobicity descriptors such as CLOGP, ELogP, nonpolar surface area, and the number of nonpolar atoms [123]. Only the fourth ALMOND component appears to be related (under 25%) with hydrogen-bond-related, e.g., HYBOT descriptors, whereas the second, fifth, and sixth ALMOND... 

SP is some free energy related solute property such as a distribution constant, retention factor, specific retention volume, relative adjusted retention time, or retention index value. Although when retention index values are used the system constants (lowercase letters in italics) will be different from models obtained with the other dependent variables. Retention index values, therefore, should not be used to determine system properties but can be used to estimate descriptor values. The remainder of the equations is made up of product terms called system constants (r, s, a, b, I, m) and solute descriptors (R2,7t2, Stt2, Sp2 log Vx). Each product term represents a contribution from a defined intermolecular interaction to the solute property. The contribution from cavity formation and dispersion interactions are strongly correlated with solute size and cannot be separated if a volume term, such as the characteristic volume [Vx in Eq. (1.6) or V in Eq. (1.6a)] is used as a descriptor. The transfer of a solute between two condensed phases will occur with little change in the contribution from dispersion interactions and the absence of a specific term in Eq. (1.6) to represent dispersion interactions is not a serious problem. For transfer of a solute from the gas phase to a condensed phase this... 

In this chapter, we introduce a novel system coefficient approach developed in our research center. The system coefficient approach uses a set of probe compoimds to measure the molecular interaction strengths of a skin/chemical mixture system. A linear free-energy relationship (LEER, a thermodynamic principle) is used to dissect the complicated molecular interactions in the absorption system into basic molecular interaction forces, which can be parameterized and used to predict a free-energy-related property of the system, such as partition coefficients or permeability. In the system coefficient approach, a chemical mixture is treated as a medium composed of the major components and other minor or trace components. A set of system coefficients represents the relative molecular interaction strengths of the chemical mixture, and a set of solute descriptors represents the molecular interaction strengths of a chemical. A free-energy-related specific property is interactively correlated to the system coefficients of the chemical mixture and the solute descriptors of the chemicals, which can be used to provide quantitative predictions... 

Consistent with earlier, single-descriptor linear analyses of protein folding [12,13,50], the primary determinants of the folding rate are measures that characterize the native structure that is, proteins with more sequentially local interactions tend to fold faster. As discussed below, the equilibrium structure and the kinetics are connected by the fact that the structure of the transition state resembles that of the native state in many small proteins [50]. Thus, the kinetics and the underlying thermodynamics of the reaction are affected in a similar way, in accord with linear free energy relations. 

This quantity is found to be related to the local polarization energy and is complementary to the MEP at the same point in space, making it a potentially very useful descriptor. Reported studies on local ionization potentials have been based on HF ab-initio calculations. However, they could equally well use semi-empirical methods, especially because these are parameterized to give accurate Koopmans theorem ionization potentials. 

The link between UpophiUcity and point charges is given by intermolecular electrostatic interactions (Sections 12.1.1.2, 12.1.3 and 12.1.4 address this topic) and ionization constants. The mathematical relationships between Upophilicity descriptors and pKjS are discussed in detail in Chapter 3 by Alex Avdeef. Here, we recall how pKj values are related to the molecular electron flow by taking the difference between the pfCj of aromatic and aUphatic amines as an example. The pfCa of a basic compound depends on the equilibrium shown in Fig. 12.2(A). A chemical effect produces the stabilization or destabiUzation of one of the two forms, the free energy difference (AG) decreases or increases and, consequently. 

The (nonlocal) polarizabilities are important DFT reactivity descriptors. But, how are polarizabilities related to chemistry As stated above, an essential ingredient of the free energy surface is the potential energy surface and, in particular, its gradients. In a classical description of the nuclei, they determine the many possible atomic trajectories. Thanks to Feynman, one knows a very elegant and exact formulation of the force between the atoms namely [22,23]... 

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