[PYTHON] Building an environment for displaying organic compounds using RDKit

Introduction

Nice to meet you. I am a university student doing chemical synthesis in an organic laboratory. In recent years, Machine Learning and Deep Learning have been actively carried out in various fields, but chemists also have fields such as Cheminformatics, but they are not so popular.

Therefore, since there are few books and articles on environment construction, as the title suggests, the environment construction method for displaying organic compounds using a Python module called RDKit is also described here as a memorandum.

Environment at hand

macbook pro 2016 macOS Catalina 10.15.4

What is RDKit

RDKit is an open source tool useful for chemoinfomatics RDKit official website

Millions of compound information (e.g. 2D / 3D information and physical property values) can be used free of charge.

Environment construction procedure

1. Install Anaconda

Anaconda is a platform that handles many Python packages for data science.

I haven't done it because I already installed it, but I think you can refer to the following articles.

Install the Python environment with Anaconda

2. Install RDKit with Anaconda

In Anaconda, the conda command is used to manage packages and build a virtual environment.

The procedure of RDKit official website is very polite, so follow the recommended method.

conda create -c rdkit -n my-rdkit-env rdkit

Enter

Proceed ([y]/n)?

Etc. will be displayed, so continue with y. Then many modules will be installed automatically.

conda activate my-rdkit-env

You can enter the disguise environment called my-rdkit-env by typing. If successful

(my-rdkit-env)PC name:user$ 

It should be displayed in the terminal as. If you run into problems here

cd [anaconda folder]/bin  #[anaconda folder]Is the location where anaconda is installed
source activate my-rdkit-env

Please try. When getting out of the virtual environment

conda deactivate

Just type.

Next, install the modules often used in RDKit under the virtual environment.

conda install numpy matplotlib
conda install pubchempy
conda install cmake cairo pillow eigen pkg-config
conda install boost-cpp boost py-boost

Up to this point, the minimum environment construction required to use RDKit has been completed. Next time (probably continuing), we will actually use the environment constructed this time to display the compounds.

in conclusion

Building an environment is the most difficult, isn't it? I wonder how many times I've been frustrated by building the environment ... This time the official website was very good, so it went smoothly.

Then someday.

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