awesome-small-molecule-ml
A curated collection of papers, datasets, tools, and resources for applying machine learning to small-molecule drug discovery.
What is awesome-small-molecule-ml?
Awesome Small Molecule Machine Learning is a curated, community-maintained list of resources focused on applying machine learning techniques to the discovery and development of small-molecule drugs. It aggregates academic papers, datasets, software frameworks, and expert blogs to provide a comprehensive starting point for researchers in computational chemistry and AI-driven drug design. The project aims to organize the rapidly growing body of knowledge in this interdisciplinary field.
Computational chemists, medicinal chemists, bioinformaticians, and machine learning researchers working on or entering the field of AI for drug discovery. It is particularly valuable for graduate students, postdocs, and industry professionals seeking a structured overview of state-of-the-art tools and literature.
Developers and researchers choose this resource because it saves significant time in literature review and tool discovery by providing a vetted, well-organized, and continuously updated aggregation. Its community-driven nature ensures it reflects practical, impactful work and includes direct links to code and data, unlike static academic lists.
Overview
A curated list of resources for machine learning for small-molecule drug discovery
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