Lipophilicity similarity indices

Meyer anchor sphere volume -> size descriptors Meyer-Richards similarity index -v similarity/diversity Meyer visual descriptor of globularHy -> shape descriptors Meylan-Howard hydrophobic model -> lipophilicity descriptors Mezey 3D shape analysis... 

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). 

The second method to be discussed, MSA, was introduced in 1980. It explicitly assumes that the shapes of the molecules provide information about the shape of the receptor cavity.Pairwise similarities and dissimilarities are calculated between a reference structure and the other compounds of the data set. Typically, biological potency is correlated with one shape index plus conventional QSAR descriptors for lipophilicity and electronic effects. 

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