Lipophilicity CoMFA

Molecular lipophilicity potential (MLP) has been developed as a tool in 3D-QSAR, for the visualization of lipophilicity distribution on a molecular surface and as an additional field in CoMFA studies [49]. MLP can also be used to estimate conformation-dependent log P values. 

More recently, with the significant increases in computer power even on desktop PCs, methods for directly matching 3-D features of molecules have become more prevalent. Features here generally refer to various types of molecular fields, some such as electron density ( steric ) and electrostatic-potential fields are derived from fundamental physics (30,31) while others such as lipophilic potential fields (32) are constructed in an ad hoc manner. Molecular fields are typically represented as continuous functions. Discrete fields have also been used (33) albeit somewhat less frequently except in the case of the many CoMFA-based studies (34). 

In addition to the steric and electrostatic descriptors, it was proposed to use other 3D molecular fields characterized by the sampling over the rectangular grid - in particular, the hydrophobic field/molecular lipophilic potential (MLP), ° hydrogen bonding and quantum-chemical parameters, e.g., orbital densities.Descriptor selection techniques are often recommended to enhance the stability, predictivity and interpretability of the CoMFA models. ... 

Masuda, T., Nakamura, K., Jikihara, T., Kasuya, E, Igarashi, K., Fukui, M., Takagi, T. and Fuji-wara, H. (1996). 3D Quantitative Structure-Activity Relationships for Hydrophobic Interactions. Comparative Molecular Field Analysis (CoMFA) Including Molecular Lipophilicity Potentials as Applied to the Glycine Conjugation of Aromatic as well as Aliphatic Carboxylic Acids. Quant.Struct.-Act.Relat., 15,194-200. 

Carrupt P-A, Gaillard P, Billois F, Weber P, Testa B, Meyer C, et al. The molecular lipophilicity potential (MLP) A new tool for logP calculations and docking, and in comparative molecular field analysis (CoMFA). In Pliska V, Testa B, van de Waterbeemd H, editors, Lipophilicity in drug action and toxicology. Weinheim VCH, 1996. p. 195-217. 

Comparative molecular field analysis (CoMFA) including molecular lipophilicity potentials as applied to the glycine conjugation of aromatic as well as aliphatic carboxylic adds. Quant. Struct. Act. Relat., 15, 194-200. 

In this chapter only QSAR methods which use physicochemical or structural features of molecules will be discussed, while in Chapter 25 3D-QSAR approaches will be presented. These so-called 3D-QSAR techniques, e.g. CoMFA, use the basic statistical principles, such as partial least squares (PLS), of QSAR methods, but in addition use the three-dimensional characteristics of a molecule specifically related to electronic, steric and lipophilic field effects. In these methods the molecular superposition believed relevant to binding to the target is crucial. 

Carrupt, P.A., Gaillard, P., Billois, F., Weber, P., Testa, B., Meyer, C. and Perez, S. (1995) The Molecular lipophilicity potential (MLP) a new tool for logP calculation and docking, and in comparative molecular field analysis (CoMFA). In Pliska, V., Testa, B. and van de Waterbeemd, H. (eds). Lipophilicity in Drug Action and Toxicology, pp. 195-215. VCH, Weinheim. 

The use of additional (or other) fields than the default steric and electronic fields of the original CoMFA method, together with PLS analysis or GOLPE, is quite common as a valuable extension of the CoMFA program, but it also constitutes an alternative to the relatively expensive commercial software. A combination of shape, lipophilic, steric, and electrostatic potentials in comparative analyses was termed comparative molecular potential analysis (CoMPA) [1014],... 

The CoMFA methodology was also used to describe nonlinear lipophilicity-activity relationships, c.g. the inhibitory activities of quaternary alkylbenzyl-dimethylammonium compounds vs. Clostridium welchii (eqs. 206—208) [1025], other antibacterial and hemolytic activities [1026, 1027], and toxic activities of alkanes in mice (eqs. 209-211) [1026] the results of classical QSAR studies (eqs. 206, 207, 209, and 210) [23, 440] were compared with the corresponding CoMFA results (eqs. 208 and 211) [1025-1027] only homologous series of compounds were investigated. 

However, despite the simplicity of the analyses and the good correlations obtained in these studies, a ligand interaction-based model like the CoMFA method should not be used to model nonlinear effects arising from transport and distribution no reasonable results can be expected for sets of compounds which are no homologous series. Better and theoretically more consistent alternatives would be the addition of suitably weighted log P values to the CoMFA table, the use of lipophilicity similarity matrices (chapter 9.4), or the correlation with log P values in the classical manner, applying either the parabolic or the bilinear model. 

In addition to the similarity indices described above, other similarity indices may be defined and used in QSAR studies. A simple lipophilidty similarity index aij = — log Pi — log PjI (log Pi, logPj = logarithms of the partition coefficients of molecules i and j) can be applied to describe nonlinear lipophilicity-activity relationships of any type by the corresponding lipophilidty similarity matrices [1013]. For different data sets excellent results were obtained (Table 31), not only in homologous series (as in CoMFA studies [1025 — 1027]) but also in heterogeneous sets of compounds, where 3D QSAR approaches must fail. A selection procedure based on genetic algorithms was developed for fast and efficient variable elimination in the PLS analyses [1013]. Also in these examples the similarity matrices produced improved Tpress values in fewer components after elimination of variables which did not contribute to prediction (Table 31). 

While such lipophilidty similarity matrices do not consider the 3D structures of the molecules, they seem to be appropriate for the incorporation of nonlinear lipophilicity-activity relationships in 3D QSAR analyses, e.g. in CoMFA studies. At least from a theoretical point of view lipophiUcity similarity matrices should be preferred when the nonlinear lipophilicity-activity relationship does not result from binding but from transport and distribution of the drugs in the biological system, which most often is the case. 

Generally, the open-chain neonicotinoids are less lipophilic than the corresponding neonicotinoids with a ring structure (Chapters 29.2.2 and 29.2.3). Based on CoMFA results, a binding model for imidacloprid (11) has been described. 

Here S is the solvent-accessible surface area for atom /, a, is the hydrophobic atom constant for atom /, and R , = e, where r is the distance between atom i and grid point t. In addition to supplementing standard CoMFA fields, HINT has been demonstrated to effectively model experimentally determined log P values in cases where CLOGP values fail. A different fragment-based, distance-dependent method to estimate lipophilicity, the molecular lipophilic potential (MLP), has been recently shown to be useful in docking and as a third field in CoMFA studies. 

Because lipophilicity is so frequently correlated with potency in traditional QSAR applications, much attention has been paid to this property in CoMFA as well. Hydrophobic interactions are well described by an H2O molecular field computed by means of a combination of steric and hydrogen bond potential functions.9. i7o goth experimental octanol/water log P values and binding data also correlated with log P are well explained. These results are understood by recalling that log P is correlated with a combination of volume or surface area and hydrogen bonding ability. Because these individual properties are accounted by the steric and hydrogen bond or electrostatic potential functions, the hydrophobic effect is also accounted for. 

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