Deoxofluorination of carboxylic acid #organic_chemistry

Now I moved from medchem team to comp.chem team but still have interest against organic chemistry.

Today I found interesting article in JOC.

The article describes about method for synthesizing of trifluoro BB with SF4.
https://pubs.acs.org/doi/10.1021/acs.joc.9b02596

The elegant work was published from researcher of ENAMINE.

As you know enamine has huge amount of unique building blocks for Drug Discovery. Several years ago I had opportunity to visit Enamine. It was well organized and there are many high skilled researchers.

OK, back to the article.

The author found suitable reaction condition for converting aliphatic carboxylic acid to trifluoro methyl group.

And the important thing is that the reaction proceed mild condition (55 degree), keep substrate stereo chemistry, wide functional group tolerance with good yield.

The key point is that small amount of water addition. In the revious method, liquid HF was used for reaction solvent. HF is highly toxic so it is not suitable solvent for common labo work I think.

Of course SF4 is also toxic reagent. To handle the reagent, it is required safety facility.

However in Scheme 4 shows that wide range of applicability of the reaction condition.

And from experimental section, the reaction can conduct gram scale.

It is very useful for medicinal chemistry I think. New building block synthesis is very exiting work for me.

RDKit based CATS Descriptor #RDKit #Chemoinformatics

Chemically Advanced Template Search (CATS) is developed by Prof. Gisbert Schneider. CATS descriptor is ligand pharmacophore based fuzzy descriptor. So it is suitable for Scaffold hopping of virtual screening. Last week, I attended his lecture and had interest the descriptor again. Fortunately I could find some implementation of the CATS2D descriptor in github repo.

Arthuc’s work (original work is Rajarshi Guha) is nice because the code is written with python and rdkit is used in chemical engine.

I modified the work and made package for CATS2D descriptor calculation with RDKit.

Let’s see an example for distance calculation. At first import packages for calculation.

from rdkit import Chem
from rdkit.Chem import DataStructs
from rdkit.Chem import AllChem
from scipy.spatial.distance import euclidean
from cats2d.rd_cats2d import CATS2D
import numpy as np

from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw

Then load two test molecules. These molecules are well known drugs.

mol1 = Chem.MolFromSmiles('CCCC1=NN(C2=C1N=C(NC2=O)C3=C(C=CC(=C3)S(=O)(=O)N4CCN(CC4)C)OCC)C')
mol2 = Chem.MolFromSmiles('CCCC1=NC(=C2N1N=C(NC2=O)C3=C(C=CC(=C3)S(=O)(=O)N4CCN(CC4)CC)OCC)C')

OK let’s calculate distance of these molecules with Morgan FP and CASTS2D descriptors. CATS2D descriptor is not bit fingerprint, so I used eucdean distance. Surprisingly Tanimoto distance (1.0 – Tanimoto similarity) is very low even if these molecules looks similar.

fp1 = AllChem.GetMorganFingerprintAsBitVect(mol1, 2)
fp2 = AllChem.GetMorganFingerprintAsBitVect(mol2, 2)
dist = 1.0 - DataStructs.TanimotoSimilarity(fp1, fp2)
print(dist)
> 0.41025641025641024

On the other hand, cats2d descriptor based distance is 0.0. It indicates that the two molecules are almost same based on their pharmacophore features.

cats = CATS2D()
cats1 = cats.getCATs2D(mol1)
cats2 = cats.getCATs2D(mol2)
euclidean(cats1, cats2)
> 0.0

Also the package can provide information of pharmacophore.

print(cats.getPcoreGroups(mol1))
>
['', ['L'], '', '', ['A'], '', '', '', ['A'], '', ['D'], '', ['A'], '', '', '', '', '', '', '', ['A'], ['A'], ['A'], '', '', ['A'], '', '', '', ['A'], '', '', '']

print(cats.getPcoreGroups(mol2))
>
['', ['L'], '', '', ['A'], '', '', '', ['A'], '', ['D'], '', ['A'], '', '', '', '', '', '', '', ['A'], ['A'], ['A'], '', '', ['A'], '', '', '', '', ['A'], '', '', '']

Scaffold hopping is very useful strategy of drug discovery for not only improving compound properties but also expanding IP space.

I would like to improve the package because the package is still under development.

Any comments a/o suggestions are greatly appreciated.

My code can be found following URL.
https://github.com/iwatobipen/CATS2D

Thanks for developing and sharing CATS2D descriptor implementation!