ZINC22:Fine Tranching with RDKit using Heavy Atom Count and LogP: Difference between revisions
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Written by Jennifer Young on April 14, 2020 | Written by Jennifer Young on April 14, 2020 | ||
=Introduction= | =Introduction https://github.com/docking-org/ZINC21-Tools= | ||
These scripts perform fine tranching with RDKit to compute the heavy atom count and logP for each molecule and put it in a bucket of the form HxxPyyy for positive valued logp (i.e. 0 < logp) and HxxMyyy for negative valued logp (i.e. logp < 0). | These scripts perform fine tranching with RDKit to compute the heavy atom count and logP for each molecule and put it in a bucket of the form HxxPyyy for positive valued logp (i.e. 0 < logp) and HxxMyyy for negative valued logp (i.e. logp < 0). | ||
Revision as of 22:29, 17 April 2020
Written by Jennifer Young on April 14, 2020
Introduction https://github.com/docking-org/ZINC21-Tools
These scripts perform fine tranching with RDKit to compute the heavy atom count and logP for each molecule and put it in a bucket of the form HxxPyyy for positive valued logp (i.e. 0 < logp) and HxxMyyy for negative valued logp (i.e. logp < 0).
See github repo https://github.com/docking-org/ZINC21-Tools
How to run
(If you are using our cluster) Source conda environment for RDKit
If you are using our cluster, there is already a conda environment with RDKit available and you just need to source it using the following command. You need to use bash.
bash
source /mnt/nfs/home/devtest/anaconda3/bin/activate my-rdkit-env
If you need to create a conda environment, follow the instructions at https://rdkit.org/docs/Install.html
Read the section : How to install RDKit with Conda. Once you do
conda activate my-rdkit-env
conda install -c conda-forge tqdm
You are ready to run the Python script.
Run Python script with the desired arguments
The input smiles file should have the following 2 columns
- smiles
- ID
python rdkit_hlogp_batch_mp.py <smiles>
The output file will be a file with the name <smiles_file>_hlogp and will have the following 3 columns
- original smiles
- original ID
- HxxPyyy HxxMyyy