Feature Trees (short FTrees) is a highly efficient software tool for pharmacophore-style similarity searching, facilitating virtual HTS. The Feature Tree descriptor captures a molecule's overall topology and its pharmacophore properties. The similarity of two such descriptors is based on an alignment (shown above by the color-coding of related functional groups).
Through it's fuzziness, the ability to detect novel molecular scaffolds is one of several strengths of FTrees.
The picture above shows two PAF antagonists that structurally do not look alike. Even a very experienced medicinal chemist would probably not have picked the molecule on the right, based on the information of the molecule on the left. Comparing the feature tree representation however, the similarity is striking. Look at the colors of the individual nodes, where same color shares similar properties, then you will understand how FTrees aligns these molecules, and why it considers these two as similar.
FTrees has been reported to be highly successful in numerous projects by various customers in
The first thing about the results obtained with FTrees from a chemist's point of view is that the molecules are aligned. This means the chemist can understand why the molecules are awarded a certain similarity. Also, the fuzzyness of the descriptor makes it ideal for finding scaffold hops.
Millions of compounds represent no problem to FTrees. In fact, there is no limit on the input size. FTrees is perfect for carrying out data reduction of large datasets. Based on one or more queries, you can use FTrees to filter the dataset down to a size more manageable for more compute-intensive screening methods — such as docking.
FTrees runs multi-threaded using all CPUs on your computer. On a typical PC with 8 cores screening 107 molecules takes less than 15 minutes. Searching in chemical spaces — using the Fragment-Space module is yet faster. Literally billions of molecules can be searched in 5 minutes. Fast enough?
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