Nobel Prize–Inspired de novo Protein Design with Wolfram Language
When I read a recent New York Times article on AI, I didn’t think I would be following the footsteps of a Nobel laureate, but I soon discovered that I could do just that with Wolfram Language.
The Nobel Prize in Chemistry for 2024 was awarded for computational protein design and protein structure prediction, which have been active areas of research for several decades. The early work was built upon a foundation of physics and chemistry, attempting to model the folding of the chain of amino acid residues comprising a protein into a three-dimensional structure using conformational analysis and energetics. More recently, AI methods have been brought to bear on the problem, making use of deep neural networks (DNNs) and large language models (LLMs) such as trRosetta, AlphaFold and ESMFold. The work of David Baker, one of the laureates, was recently showcased in a New York Times article.