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What if Therapeutic-Grade Biotech Was Used for Environmental Remediation with Pranam Chatterjee
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Imagine proteins engineered to seek out and bind toxic heavy metals, cleaning up contaminated sites and potentially treating metal poisoning in humans.
In this episode, Duke University professor and entrepreneur Pranam Chatterjee shares how his has developed two impressive AI tools transforming this field: MetaLATTE, which predicts whether proteins will bind specific metals, and the upcoming MetaLORIAN, which generates custom peptides designed to target particular metals like cadmium, lead, or copper. These technologies represent a significant advancement over traditional remediation approaches, potentially offering more precise, selective methods for environmental cleanup.
What makes this work particularly exciting is its dual potential—the same protein engineering techniques could address environmental pollution while simultaneously developing therapies for human metal poisoning. From brownfield remediation to industrial metal recycling and medical applications, these programmable proteins could offer unprecedented flexibility in how we tackle toxic metal contamination.
Visit chatterjeelab.com or huggingface.com/chatterjeelab to explore these tools yourself and see firsthand how AI-driven protein engineering is revolutionizing environmental remediation.
Chapters
1. What if Therapeutic-Grade Biotech Was Used for Environmental Remediation with Pranam Chatterjee (00:00:00)
2. Heavy Metals: Environment & Health Problem (00:00:04)
3. Introduction to Climate Biotech Podcast (00:00:33)
4. Pranam's Background in Religion & Science (00:01:19)
5. The CRISPR Revolution & Protein Engineering (00:04:58)
6. From Postdoc to Startup Success (00:10:51)
7. The Chatterjee Lab's Focus on Metal Binding (00:15:20)
8. Metal Latte & Metalorian: AI for Metal Binding (00:24:56)
9. Applications & Stakeholders for Metal Removal (00:31:03)
10. Challenges of Technology Translation & Commercialization (00:39:02)
11. Rapid-Fire Questions & Closing Thoughts (00:43:25)
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