How AlphaFold transformed my classroom into a research lab

I first heard about AlphaFold, not in a lab, but in my high school Advanced Placement biology classroom. Colorful pipe cleaners, beads and half-finished 3D kits cluttered the desks, remnants of our best attempt to mimic the complexity of protein folding.

AlphaFold2

Structural comparison of normal CFTR and ∆F508 mutant as predicted by AlphaFold2.

My students grasped that protein shape dictates function, but the real, atomic-level structures felt out of reach. Then I discovered AlphaFold’s free online database. With a few clicks, we could enter a protein sequence, like insulin or the cystic fibrosis protein CFTR, and view a highly accurate 3D structure within minutes. Watching my students spin these models on screen felt like stepping into the future of science education.

For decades, protein folding research meant years of work using costly X-ray crystallography or cryogenic-electron microscopy. AlphaFold changed that. Trained on millions of known structures, it predicts a protein’s shape from sequence alone — letting my students explore complex structures with nothing more than an internet connection.

Our first “aha” moment came during our cystic fibrosis unit. Students compared the normal cystic fibrosis transmembrane conductance regulator, or CFTR, structure to the ∆F508 mutant, the most common disease-causing variant. They saw how a single missing amino acid disrupted folding, and their eyes lit up as they were watching, in 3D, how a tiny molecular error causes devastating disease.

That mishappen protein disrupts salt and water balance in the lung leading to thick mucus, chronic infections and breathing difficulties. For many, it was the first time they could visually connect a DNA mutation to the molecular mechanics of illness.

Courtesy of Sarmistha Ghosh

South Mecklenburg High School Advanced Placement biology students, Reese Briggs, Ella Canty, Katherine LiBrizzi and Kennady Benton, examine microcentrifuge tubes in a blue-light transilluminator with their teacher, Sarmistha Ghosh, in the Kirill Afonin lab at the University of North Carolina at Charlotte.

AlphaFold became more than a research tool; it was a bridge letting students see the intersection of genetics, chemistry and health. Their questions grew bolder: Could artificial intelligence, or AI, predict how a CRISPR/Cas9 edit alters folding? Could it guide drug design? Suddenly, our classroom felt less like a lecture hall and more like a research lab.

AlphaFold changed my view of AI. No longer a black box in distant computational labs, it became part of my teaching toolkit. It put real research in my students’ hands.

AI didn’t replace the bench; it gave it meaning. It showed my students why proteins fold, why misfolding matters and how modern tools can tackle age-old questions. Now they see AI not as hype, but as a tool that can help improve lives when used wisely.

The challenge is ensuring it enhances, not eclipses, the curiosity and creativity that make us human. AlphaFold showed me that AI can spark a lifelong love for science in the next generation.