Biological systems are stunningly complex, and the complexity extends down to the single protein level.
Proteins are made up of a string of amino acids, which then fold up into structures that determine their function. Many Nobel Prizes have been awarded for determining protein structures, most recently the 2013 Nobel Prize in Chemistry for computer analysis of protein structure. Why is it important to determine protein structure? Because protein structure informs protein function, and when we understand protein function within the context of protein structure, we can begin work on structure-based drug design to cure disease.
We have biochemical methods available to determine protein structure, including x-ray crystallography, nuclear magnetic resonance (NMR) and cryo-electron microscopy (cryo-EM). These methods are accurate but difficult and time- and resource-intensive. It would be much simpler to just look at the amino acid sequence of a protein – which is readily available – and then predict the structure of the protein using an algorithm, but unfortunately this has proven to be very difficult. But now we have artificial intelligence (AI), and Google’s AI offshoot DeepMind has recently made substantial progress in predicting protein structure from an amino acid sequence. This is a discovery that could revolutionize molecular biology, structural biology, bioengineering, and drug design all at once. Is it time for another Nobel Prize for protein structure?
*Edit: this was posted a day too early: watch the video!*
