Proteins may be small and unassuming, but these molecules are essential for a variety of biological functions in all living organisms, including digestion, immune response and even intracellular communication. Consisting of long chains of smaller organic compounds called amino acids, the different functions of various proteins are determined by the way they fold up in three-dimensional space. Not surprisingly, the folded structures of these protein chains can get immensely complex, and scientists have yet to fully figure out the mysteries behind how and why certain proteins fold the way they do, and how diseases like Alzheimer's might be caused when they misfold. While using modern technologies like cryo-electron microscopes, nuclear magnetic resonance and X-ray crystallography can help us understand protein folding a little better, it's an unfortunately time-consuming and costly process. Accurately predicting the folded structures of proteins could be the key to unlocking many medical mysteries, and thanks to recent developments in integrating artificial intelligence in the field of computational biology, that slow process may very well be accelerated -- allowing us to discover or even design new and useful proteins.