Resources (work in progress)

Group guide

Learning Resources

A curated collection of external resources, tutorials, and tools that we recommend for learning about computational chemistry, machine learning, and chemical informatics.

Education

Educational materials, courses, and tutorials to get you started

• DeepChem Tutorials - Machine learning for drug discovery tutorials

• ML4MolEng Problem Sets - Problem sets for the MIT ML4MolEng course

• dl-chem-101 - Deep learning for chemistry educational repository

• AI4Chem - A course on AI for chemistry by the LIAC team at EPFL

Blogs

Regular updates and insights from experts

• Greg Landrum’s RDKit Blog - Insights and tutorials on RDKit and cheminformatics

• Pat Walters’ Practical Cheminformatics - Practical cheminformatics tutorials and insights

• Derek Lowe’s In the Pipeline - Commentary on drug discovery and pharmaceutical industry

Github

Research Hub

• AI4MolConformation - List of molecules ( small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

• GenAI4Mol - List of Molecular and Material design (molecular conformation generation) using Generative AI and Deep Learning

• GenAI4Protein - List of papers about Protein Design using Deep Learning

Tools

Interactive tools and utilities

• SMARTSPlus - Interactive SMARTS pattern matching tool

Software

Open-source software packages

• RDKit - Open source toolkit for cheminformatics

• OpenRetro - An open source library for benchmarking one-step retrosynthesis

• Open Reaction Database (ORD) - Open-access schema and infrastructure for structuring and sharing organic reaction data

Publications

Academic journals and research platforms

• Distill Publications - Clear explanations of machine learning concepts

Books

Comprehensive textbooks and reference materials

• Andrew White’s Book - Deep Learning for Molecules and Materials