Protein biology has always been grounded in the relationship between structure and function but how we determine structure has changed dramatically. While it’s still common to crystallize a protein for X-ray diffraction and then back calculate its structure, supercomputing-powered, AI-driven tools have revolutionized approaches to getting a protein structure and engineer proteins for uses such as biocatalysis. Amazing right, but how? By using wet lab data to train and then compute, protein structure based on their sequence alone, which is why talking with this episode’s guest is so interesting.
In this episode, Dr. Ahir Pushpanath, Enzyme Technology Innovation Lead at Basecamp Research, explains his passion for gaming as the reason he got interested in this unique computational approach to chemical catalysis. He takes us through the field’s fascinating history, recent breakthroughs, and their immense potential. You’ll hear about the intersection of his personal mission to provoke a bio-revolution with his company’s mission to combine nature and AI.
Today at Basecamp Research, Ahir and his team are working to remove global bias from protein-specific AI training sets by collecting samples and data from diverse locations, but their primary focus is to understand the why of protein evolution. Ultimately, they hope to someday be able to help make a protein for every conceivable function by incorporating environmental pressure aspects into their sequence/structure/function AI models.
Related episodes:
Other episodes on catalysis:
- S3:E2 Making impossible molecules
- S2:E1 Chemistry: a modern American dream
- S2: E3 Rethinking catalysis
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