Due to the nature of SCCP, which are just based on chlorination of
n-alkanes (so just linear), enumerating them via a more limited method than
the interesting linked preprint is also possible.
This can be done exhaustively on the string level
a given carbon in the chain will have either 0 or 1 or 2 chlorines (and in
all examples given just 0 or 1). Either cap (terminal carbon) of the
molecule can also have a third chlorine (so trichloromethyl cap). N alkanes
are linear so our SMILES only needs branching for Cl, which due to having a
valence of 1 is terminal.
therefore the following script can be used to generate them exhaustively
and even filter them for chlorine ratio without ever having to convert to a
mol
```
import rdkit
from rdkit import Chem
import itertools as it
allsmi=[]
maxvalence=2
def cl_ratio(Cl,C):
return Cl*35.5/(C*12+Cl*35.5+C*2-Cl+2) #ratio of chlorine vs total MW
for chainlength in [10,11,12,13]:
combinations = (list(i) for i in
it.product(list(range(maxvalence+1)),repeat=chainlength) if
tuple(reversed(i)) >= tuple(i)) #filter out mirror image molecules
for comb in combinations:
curr_smi = ""
for cl_count in comb:
curr_smi+="C" # increase chain with one carbon
for i in range(cl_count):
curr_smi+="(Cl)" # chlorinate as needed
if 0.4<=cl_ratio(sum(comb),chainlength)<=0.7:
allsmi.append(curr_smi) #add if it has the correct ratio of Cl
to MW
if maxvalence>1: # check for molecules that have a trichloromethyl
terminal cap
if comb[0]==2:
if 0.4<=cl_ratio(sum(comb)+1,chainlength)<=0.7:
allsmi.append("(Cl)"+curr_smi)
if comb[-1]==2:
if 0.4<=cl_ratio(sum(comb)+2,chainlength)<=0.7:
allsmi.append(curr_smi+"(Cl)")
else:
if comb[-1]==2:
if 0.4<=cl_ratio(sum(comb)+1,chainlength)<=0.7:
allsmi.append(curr_smi+"(Cl)")
with open('CSSP.smi', 'w') as f:
for smi in allsmi:
f.write("%s\n" % smi)
```
it takes about 5 seconds to run on a desktop and the output is a smi file
with 437001 smiles strings. In case you want to have max 1 Chlorine per
carbon the solution is a bit easier and faster. In the above script you can
change max valence to 1, outputting ~7K molecules.
best wishes
On Wed, Dec 8, 2021 at 11:29 AM Gyro Funch <gyromagne...@gmail.com> wrote:
> Thank you very much for the pointer. I will investigate.
>
> Kind regards,
> Gyro
>
> On 2021-12-08 11:15 AM, Jan Halborg Jensen wrote:
>
> This package might do the trick:
> https://doi.org/10.26434/chemrxiv-2021-gt5lb
>
> On 8 Dec 2021, at 11.02, Gyro Funch <gyromagne...@gmail.com> wrote:
>
> [You don't often get email from gyromagne...@gmail.com. Learn why this is
> important at http://aka.ms/LearnAboutSenderIdentification.]
>
> Hello,
>
> I am not a chemist, but have been using RDKit to generate descriptors
> and fingerprints for molecules with known SMILES. It is a very useful
> package!
>
> I have a problem on which I hope someone can provide some guidance.
>
> My work is in the area of toxicology and I am interested in generating
> SMILES for molecules referred to as 'short chain chlorinated paraffins'
> (SCCP).
>
> A general definition that is sometimes used is that an SCCP is given by
> the molecular formula
>
> C_{x} H_{2x-y+2} Cl_{y}
>
> where
>
> x = 10-13
> y = 3-12
>
> and the average chlorine content ranges from 40-70% by mass.
>
> -----
>
> Can anyone provide guidance on how to generate the list of SMILES
> corresponding to the above rules?
>
> Thank you very much for your help!
>
> Kind regards,
> gyro
>
>
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