Creating Feature Trees from Molecules

A Feature Tree represents a molecule by a tree structure. The tree should capture the major building blocks of the molecule in addition to their overall arrangement. Detailed information of less importance for protein binding such as the molecular graph should be neglected. In this way, not only is the complexity of the compar- 

Finally, the Feature Tree nodes are marked with labels describing the shape and chemical properties of the building block. In principle, every kind of descriptor can be used as a label provided that the descriptor is additive over the building blocks. In our Feature Tree implementation, we normally work with a shape 

Similarities between a shape descriptor and a chemistry descriptor may be combined to calculate the final similarity sim(m) for a match m of nodes representing two building blocks. 

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Once a Feature Tree can be created from a molecule, the question arises of how to compare two Feature Trees. Using Eq. (1), we are able to compare two individual Feature Tree nodes. Owing to the additivity of the features stored at a node, we can also compare two sets of Feature Tree nodes. This is done by adding the features over all nodes within a set and applying Eq. (1) again. Obviously, we can also compare two complete Feature Trees in this way we just add all features in the two trees and apply Eq. (1). We call such a comparison level-0, because no division of the tree into pieces has been performed. Level-0 comparisons closely resemble the way linear descriptors work. If we assume for a moment that all components of a linear descriptor are additive and can be computed for each building block individually (such as the volume descriptor), adding the feature values over all Feature Tree nodes will create the linear descriptor. 

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