I am not a chemist, I come from a computer science background. I am involved in a cheminformatics project. I have a list of molecules in SMILES format, which I want to extract sub-structures from.
I found some interesting sub-structures that I want to look for in a given molecule in the paper https://www.mdpi.com/1420-3049/21/1/75 published in 2015.
In the abstract it is mentioned that: We first uncovered three important criteria closely related to drug-likeness, namely:
(1) the best numbers of aromatic and non-aromatic rings are 2 and 1, respectively;
(2) the best functional groups of candidate drugs are usually -OH, -COOR and -COOH in turn, but not -CONHOH, -SH, -CHO and -SO3H. In addition, the -F functional group is beneficial to CNS drugs, and -NH2 functional group is beneficial to anti-infective drugs and anti-cancer drugs;
(3) the best R-value intervals of candidate drugs are in the range of 0.05–0.50 (preferably 0.10–0.35), and R-value of the candidate CNS drugs should be as small as possible in this interval
also, Acyclic groups as mentioned in this paper (figure 4), https://bmcchem.biomedcentral.com/articles/10.1186/s13065-021-00737-2
My question is, is there a method in RDKit (or other Python libraries) that extracts these criteria from smiles?