Bioinformatics Project from Scratch - Drug Discovery Part 5 (Compare Models)

This is Part 5 in a multi-part video series on Bioinformatics Project from scratch. In this video, I will show you how to quickly build and compare several regression models (quantitative structure-activity relationship or QSAR) of the Acetylcholinesterase inhibitors using the lazypredict library in Python.

- Recap of Part 1, I have shown you how to collect original dataset in biology that you can use in your Data Science Project. Particularly, I have demonstrated how to download and pre-process the biological activity data from the ChEMBL database. The dataset is comprised of compounds (molecules) that have been biologically tested for their activity towards target organism/protein of interest.
- Recap of Part 2, I have shown you how to calculate Lipinski descriptors (molecular descriptors proposed by Christopher Lipinski for predicting their likelihood of being drug-like molecules) and performing Exploratory Data Analysis on these Lipinski descriptors. Particularly, the EDA are based on making simple box plots and scatter plots to discern differences of the active and inactive sets of compounds.
- Recap of Part 3, I have made some changes to the target protein to be Acetylcholinesterase as it provides a larger dataset to work with. We have already computed the molecular descriptors using the PADEL-Descriptor software and prepare the dataset (X and Y dataframes) that will be used in this video for Model Building.
- Recap of Part 4, I have show you how to use the computed molecular descriptors from Part 3 (as the X variables) to build a regression model for predicting the pIC50 values (the Y variable).

⭕ Jupyter notebook (Acetylcholinesterase inhibitors)
Part 1
https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_1_Acetylcholinesterase_Bioactivity_Data_Concised.ipynb
Part 2
https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_2_Acetylcholinesterase_Exploratory_Data_Analysis.ipynb
Part 3
https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_3_Acetylcholinesterase_Descriptor_Dataset_Preparation.ipynb
Part 4
https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_4_Acetylcholinesterase_Regression_Random_Forest.ipynb
Part 5 https://github.com/dataprofessor/code/blob/master/python/CDD_ML_Part_5_Acetylcholinesterase_Compare_Regressors.ipynb

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