Our Slack community wanted to hear about AI-driven drug discovery, and we listened. Abraham Heifets from Atomwise joins us for a fascinating deep dive into the intersection of deep learning models and molecule binding. He describes how these methods work and how they are beginning to help create drugs for “undruggable” diseases!

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Featuring:

• Abe Heifets – Twitter
• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

• Atomwise
• Atomwise Receives a $2.3M Grant to Develop New Therapies for Drug Resistant Malaria and Tuberculosis
• Atomwise Partners with Global Research Teams to Pursue Broad-Spectrum Treatments Against COVID-19 and Future Coronavirus Outbreaks
• World robotic soccer
• Philadelphia chromosome
• Alphafold
• Canavan disease example:
  • Paper: “Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural Network”
• AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery
• [“Memorizing yesterday’s stock price” example](Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization)

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