Alignment-Free 3D Descriptors VolSurf

Each drag molecule is characterized by its potential hydrogen bonding, polar and hydrophobic interactions, starting from its three-dimensional structure, but without the necessity to bring different molecules into an 

Volsurf descriptors were also successfully used to build a classification model for predicting blood-brain barrier (BBB) permeability for drug-like molecules 

Other important applications include the generation of a model to predict thermodynamic water solubility (Cruciani et al. 2003). This model is based on consistent solubility data from literature plus additional measurements for 970 compounds. Its quality allows to differentiate between very poorly/poorly/medium/ highly and very highly soluble molecules while exact rankings within individual classes are not possible. However, given the different factors influencing experimental thermodynamic solubility data, it is not likely that significantly improved models for this key property in pharmaceutical sciences can be derived. 

The suitability of these descriptors for database mining was investigated in a comparative analysis (Cruciani et al. 2002). While 2D descriptors like Unity 

Another modification of the VolSurf approach to analyze molecular interaction fields was described by Pastor et al. (2000). The same information previously been used to compute VolSurf descriptors now served to compute GRIND descriptors. In contrast to VolSurf, these descriptors capture information about pharmacophoric groups and their distances within individual molecules. These descriptors represent favorable interaction energy regions where groups 

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