DeepRA: A Novel Deep Learning-Read-Across Framework and Its Application in Non-Sugar Sweeteners Mutagenicity Prediction
Tarapong Srisongkram(tarasri@kku.ac.th)
Division of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Khon Kaen University, THAILAND.
Read full paper published in Computers in Biology and Medicine
DeepRA model was trained to classifiy mutagenicity properties of chemicals.
Please find the full instruction in the DeepRA_tutorial.ipynb
It works best in Google colab via this link: DeepRA_tutorial.ipynb
Before using this software, please change the data in this file: dulcin.csv with you prediction molecule.
!pip install rdkit
!pip install mordred
!git clone https://github.com/taraponglab/deepra.git
%cd deepra
!git fetch
!git pull
%ls
from joblib import load
scaler_mord = load('mordred_scaler.joblib')
model_mord = load('CNN-Mordred.joblib')
model_rdkit = load('CNN-RDKIT.joblib')
model_ecfp = load('CNN-ECFP.joblib')
model_ad = load('AD_nn.joblib')
deepra = load('DeepRA-Mordred.joblib')
import pandas as pd
df = pd.read_csv('dulcin.csv', index_col = 'Name')
df
You will get this result from the last cell
Name DeepRA-Mordred class AD_status
dulcin 0.997393 1 within_AD
DeepRA-Mordred = Possibility of mutagenicity (if DeepRA-Mordred < 0.5 then it is non-mutagen, if > 0.5 then it is mutagen)
class = Mutagenicity class where 1 = mutagen and 0 = non-mutagen
AD_status = Prediction is within or outside AD
DeepRA version 1.0
Srisongkram T. DeepRA: A novel deep learning-read-across framework and its application in non-sugar sweeteners mutagenicity prediction. Comput Biol Med. 2024 Jun 12;178:108731. doi: 10.1016/j.compbiomed.2024.108731.
Copyright (c) [2024] [Dr.Tarapong Srisongram]
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.