Table of Contents

Update 03_2019: forked and tried to translate to english. Corrections are welcome.

Update 01_2020: updating the information to mimic original.

• AsciiDoc Syntax Quick Reference

01 Introduction

• What is RDKit?

• Target audience

• About the code in this book

• Acknowledgments

• bonus

• License

02 Create an environment for chemoinformatics

• About Anaconda

• How to install Anaconda

• Build virtual environment and install packages

• Description of the installed package

• More about Conda

03 Basics of Python programming

• Python basics

• Use it conveniently with the Jupyter notebook

• Machine learning with Python

04 Public database for chemoinformatics

• ChEMBL

• PubChem

• Search for desired information with ChEMBL

• Other useful databases

05 Handling Structural Information with RDKit

• What is SMILES?

• Let’s draw the structure

• How to handle multiple compounds at once?

• Try hetero shuffling

06 Evaluating the similarity of compounds

• What does it mean that compounds are similar?

• Calculate similarity

• Virtual screening

• Clustering

• Structure Based Drug Design (SBDD)

07 Evaluation of similarity using graph structure

• Classification by major skeleton (MCS)

• Matched Molecular Pair and Matched Molecular Series

• Visualize MMP networks using Cytoscape

08 I want to have many compounds at once

• Chemical Spaceとは

• Mapping using tSNE

09 Basics of Quantitative Structure-Activity Relationship (QSAR)

• Consider the cause of the effect (Classification problem)

• Predict the efficacy of drugs (regression problem)

• Model applicability (applicability domain)

10 Introduction to Deep-Learning

• About TensorFlow and Keras

• Google colab

• Let’s install

11 Structure-activity relationship using deep-learning

• Predictive model construction using DNN

• Devising a descriptor (neural fingerprint)

12 Let the computer think about chemical structure

• Preparation

• Illustration

13 Conclusion

• Final remarks and further reading

License

This document is copyright © 2019 by @fmkz___ and @iwatobipen

This document is Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License.