So far I've been unsuccessful in finding an open source tool that will convert a large number (>100k) of SMILES strings to a chemical structure. Is this really only solved by commercial applications? I would not mind converting through a number of intermediate formats. Ideally I'd do it with R, but that is the least of my worries. It's also neither for personal nor academic use.
For example, the following code will give you a neat SVG file of the molecule benzene:
obabel -:"c1ccccc1" -O benzen.svg
If you experience problems using it, you are welcome to ask more specifically.
Alternatively, you can use a web-query from the national cancer institute. It is easily accessible by the following code
Another open source solution, where you can directly export the structure into a molecular editor is Avogadro. (It uses Open Babel though.)
Depending on the actual problem, however, there might already be more advanced routines.
In addition to the other good answers, I'd recommend
rdkit, an open-source, freely available software for chemoinformatics. Most people use
rdkit via its Python interface.
Here are some
- The code base is available in GitHub, here.
- The license is quite permissive; you don't need to worry about what type of work (commercial, personal, or academic) you are doing.
- The Python API makes using
rdkiteasy, but all the core functions are written C++, making it fast and efficient. The Python API provides access to these functions in Python, making it flexible and easy to learn. If you happen to be fluent in C++, a C++ API is available.
- It does a whole lot more than convert SMILES to structures; see some examples here.
Here is one way to convert a SMILES to a structure in rdkit.
from rdkit import Chem from rdkit.Chem import Draw import matplotlib.pyplot as plt %matplotlib inline penicillin_g_smiles = 'CC1([C@@H](N2[C@H](S1)[C@@H](C2=O)NC(=O)Cc3ccccc3)C(=O)O)C' penicillin_g = Chem.MolFromSmiles(penicillin_g_smiles) Draw.MolToMPL(penicillin_g, size=(200, 200))
For those who want to convert a few SMILES strings to images, you can also use the CDK 1.5-based Depict utility from John May (www.simolecule.com/cdkdepict/, GitHub). It provides various options and outputs Scalable Vector Graphics (which can be easily converted into other formats).
For example, caffeine with title: https://www.simolecule.com/cdkdepict/depict/bow/svg?smi=CN1C%3DNC2%3DC1C(%3DO)N(C(%3DO)N2C)C%20caffeine&abbr=on&hdisp=bridgehead&showtitle=true&zoom=1.6&annotate=none
However, since you probably prefer a pure R-based solution, please do have a look at the rcdk package.
I'm surprised that you've had difficulty finding a toolkit - is it that the licence must be MIT or as permissive? I guess that you will be using this in software you are making, rather than a one-off data conversion?
For example, OpenBabel (C++), Chemistry Development Kit (Java), etc - in addition, the CDK can interface with R - would seem to suit your needs?
In Python you could try pysmiles.
Starting from the SMILES description you should be able to create a NetworkX graph object with code along the lines of
from pysmiles import read_smiles import networkx as nx smiles = 'C1CC[13CH2]CC1C1CCCCC1' mol = read_smiles(smiles)