I'm not really sure what you mean by tversky searching in substructure mode.

Fingerprinting methods do not guarantee the presence of an exact substructure.  
You can think of tversky asking what percentage of me is in you and that 
percentage doesn't have to be a substructure.  However they are correlated in 
that a good screening fingerprint can throw out molecules that will never be a 
substructure match.  You still have to check the substructure match however.

Using a screen fingerprint to filter out true negatives, I generally go from 
5-10k substructure matches/sec to around 500-600k/sec in real world searches.  
I'm happy to provide an example of this if you need it.

I hope this helps.

----
Brian Kelley

> On Dec 12, 2016, at 11:29 AM, Axel Rudling <axru6...@gmail.com> wrote:
> 
> Hello all,
> 
> Currently I'm doing a project with Tversky searching in substructure mode and 
> use smiles for creating fingerprints.
> 
> For most molecules I get the correct result but there are some molecules 
> where I get an overflow of falsely predicted substructure molecules. In 
> brief, I get a large amount of compounds as a result from the substructure 
> search that are not actually substructures of the query compound. I'm not 
> certain of why but it might have to do with the FP representation as these 
> molecules have a very unusual curricular structure ex.:
> 
> C1C[NH2+]CCC[NH2+]CCCNCCC[NH2+]C1
> 
> 
> I use 2048-bit ECFP4 fingerprints.
> 
> tverskySim = DataStructs.TverskySimilarity(ffp1,ffp2,1.0,0.0)
> 
> Does anyone have an idea?
> 
> 
> 
> best
> 
> Axel
> 
> 
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