Deep learning technology for drug discovery

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 – X
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

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)

Something missing or broken? PRs welcome!

Creators & Guests

Host

Chris Benson

Host

Daniel Whitenack

Guest

Abe Heifets

What is Practical AI?

Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).

The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!