Ghose/Crippen descriptors

Ghose-Crippen descriptors lipophilicity descriptors (0 Ghose-Crippen hydrophobic atomic constants)... 

Ghose-Crippen descriptors were successfully used also to model —> molar refractivity [Ghose and Crippen, 1987] and solvation free energies [Viswanadhan, Ghose et al, 1999] by —> group contribution methods. 

Figure 12.2 The compound sets from which the hERG (filled triangles) and the BBB (open circles) in-silico filters were derived are compared by principal components analysis, and one structure of each set is depicted. Ghose and Crippen descriptors were calculated for all the molecules, and after autoscaling, the compounds were projected onto the scores plot of the first two components [74],...

Based on this in-house dataset, an in-silico prediction model [27] (three-layered neural network, Ghose and Crippen [28,29] descriptors) was constructed to evaluate the frequent hitter potential before compound libraries are purchased or synthesized. This model was validated with a dataset of the above-mentioned promiscuous ligands published by McGovern et al. [26], in which 25 out of 31 compounds were correctly recognized. 

Lipophilicity descriptors, in particular, the atomic lipophilicity contribution La in Ghose and Crippen s system, taking into account the environment of an atom, and group lipophilicity Lg defined as a sum of contributions for a non-hydrogen atom and attached hydrogens. 

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