About

caismd_qsar_2024 provides material for the CAiSMD 2024 Hands-on Session: Exploring Antimalarial Drug Discovery Through Cheminformatics and QSAR modeling.

An introduction to the tutorial is provided in the .pdf document.

Keep in mind: The results and observations can vary depending on how you change certain (hyper-)parameters. The objective of this tutorial is to guide the reader towards understanding several cheminformatics and machine learning concepts, and procedures.

Installation

The tutorial is provided through a series of notebooks in the data/ folder. It is recommended to install an IDE that can incorportate Jupyter notebook extensions, such vas VSCode.

1. Create and activate a new conda environment (Preferrably with Python version 3.9)

   • Run conda create -n caismd_qsar_2024 python=3.9.
   • Run conda activate caismd_qsar_2024 .

2. Install packages with pip

   • Run pip install mordred rdkit-pypi novana pandas umap-learn matplotlib seaborn
   • Run pip install scikit-learn optuna lightgbm shap
   • Run pip install ipywidgets ipykernel

3. In order to view and interact with the Jupyer notebook, it is important to regiuster the kernel that run the created conda environment

   • Run python -m ipykernel install --user --name=caismd_qsar_2024

Repository Structure

caismd_qsar_2024/

• data/ Contains the original records from the PubChem assay. Additional files will be added here, during preprocessing.
• figs/ Figures will be saved here.
• lib/ Contains the code for several modules with various utility functions.
• models/ The models will be saved here.
• notebooks/ Contains the interactive notebooks with instructions and explainations.

Prerequisites

The following prerequisites are recommended to the reader. However, the basic understanding of chemistry is not a must.

• Basic understanding of chemistry concepts.
• Basic understanding of statistical analysis or machine learning concepts.
• Familiarity with molecular structures and chemical descriptors.
• Comfortable working with data.
• Some experience with (Python) programming or a willingness to learn basic programming concepts