Thank Nils for pointing both algorithms to the list. Interestingly Greg is
putting together scaffold tree algorithm in this PR
https://github.com/rdkit/rdkit/pull/2911 so anyone could try it in the
nearest future, hopefully 2020 release.
Pozdrawiam, | Best regards,
Maciek Wójcikowski
The function takes two Explicit or Sparse bit vectors. Could you elaborate
on what you mean that it accept smarts only? PatternFingerprints will work
with SMARTS too.
It is always more effective to have the SMARTS as explicit as possible,
since if you have all alternative atoms, the FP cannot
Hi Alexis,
if you go down that route and calculate artifical skeletons, you could
also go all the way and use an algorithm like HierS [1] or the scaffold
tree [2] to perform a recursive fragmentation of your queries and
molecules into their various rings and ring systems. If a query contains
a
Hi Maciek, thanks for your response. I did try that function too, but it
also takes smiles only (not smarts). I think the solution of Gregori is
very interesting: I am going to transform all smiles and smarts into their
single-bonded-carbon-based skeleton and will store the pattern fingerprint
of
Alexis,
I believe that `DataStructs.AllProbeBitsMatch(query_fp,mol_fp)` is the
function you are looking for here. More advanced usage and code snippets
you can find on RDKit blog post that Greg has put together here:
https://rdkit.blogspot.com/2013/11/fingerprint-based-substructure.html
Best,
Hi Alexis,
Knowing what you want to achieve, I would take the problem the other way
around. Instead of matching your many fragments to your input structure, I
would rather apply the same transformation(s) you apply to your fragments to
your input structure.
I know that you replace all
Dear Rdkiters,
I am interested in doing substructure searches between many thousands
structures and many thousands of fragments, as quickly as possible, with
reasonable accuracy (> 0.95)...
I did read Greg's excellent post on that subject:
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