awesome-ai4drug-papers
github.com/beastlyprime/awesome-ai4drug-papers ↗A collection of AI for Drug Design related papers and corresponding code sources (in progress).
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MoleculeGeneProtein
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me molecule generation resources from awesome-ai4drug-papers"
Installation instructions →What's inside
Molecule
- A 3D Generative Model for Structure-Based Drug DesignMolecule Generation
- Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave FunctionsProperty Prediction
- Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular DesignMolecule Generation
- An Autoregressive Flow Model for 3D Molecular Geometry Generation from ScratchMolecule Generation
- A Program to Build E(N)-Equivariant Steerable CNNsRepresentation Learning
- Chemical-Reaction-Aware Molecule Representation LearningRepresentation Learning
Protein
- Co-evolution Transformer for Protein Contact PredictionContact Prediction / Docking
- Geometric Transformers for Protein Interface Contact PredictionContact Prediction / Docking
- Independent SE(3)-Equivariant Models for End-to-End Rigid Protein DockingContact Prediction / Docking
- Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-designDesign
- Language models enable zero-shot prediction of the effects of mutations on protein functionFunction Prediction
- Maximum n-times Coverage for Vaccine DesignDesign
Showing a sample of 41 resources. View the full list on GitHub →