On Dec 2, 2016, at 10:12 PM, George Papadatos wrote:
> If Alexis wants to search for valid SMILES strings representing typical
> organic molecules among text of plain English words, would it not be safe to
> assume that any word containing more than 4 'C' or 'c' characters would only
> be a SMILES string?
Maybe. It depends on the text. That's the problem with any sort of text
extraction.
If it contains entries like:
The combination of phenol (c1ccccc1O) and ....
or
The SMILES for phenol is c1ccccc1O.
then my code will extract the 'c1ccccc1O', even though the whitespace delimited
words of "(c1ccccc1O)" and "c1ccccc1O." cause RDKit to complain with a parse
error.
I implemented your heuristic as:
def find_possible_smiles(text):
return [(0, 0, term) for term in text.split() if term.count("C") +
term.count("c") >= 4]
Here are some of the matches:
/Users/dalke/talks/ICCS_2014_paper.txt:0:0 'CACTVS-specific'
/Users/dalke/talks/ICCS_2014_paper.txt:0:0 'CC12CCC3C(CCC4=CC(O)CCC34C)C1CCC2'
/Users/dalke/talks/ICCS_2014_paper2.txt:0:0
'[http://www.dalkescientific.com/writings/diary/archive/2005/03/02/faster_fingerprint_substructure_tests.html]'
/Users/dalke/talks/Sheffield2013.txt:0:0 '"C1=CC=CC=C1"'
/Users/dalke/talks/Sheffield2013.txt:0:0 '"c1ccccc1",'
/Users/dalke/talks/bugs.txt:0:0
'http://localhost:8080/files?responder=%3Cscript%3Ealert%28%22hi!%22%29%3C/script%3E'
/Users/dalke/talks/garfield.txt:0:0
'http://www.chemheritage.org/discover/collections/oral-histories/details/henderson-madeline-m.aspx'
You can see it grabbed as trailing comma for a SMILES, as well as a bunch of
URLs. Those could, of course, be easily post-filtered. But why not use a regexp?
Of course, another level on top of this would be de-hypenation.
This is a well trod path, but not an easy one.
BTW, I tested how many missed structures there might be using your heuristic:
>>> sum(1 for line in open("/Users/dalke/databases/pubchem.smi") if
>>> line.count("C") >= 4)
68228954
% wc -l /Users/dalke/databases/pubchem.smi
68413797 /Users/dalke/databases/pubchem.smi
I inverted the logic, so that's
68413797-68228954 = 184843 = 0.3%
Andrew
da...@dalkescientific.com
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