AI HAS GOTTEN something of a bad rap in recent years, but the Covid-19 pandemic illustrates how AI can do a world of good in the race to find a vaccine. AI is playing two important supporting roles in this quest: suggesting components of a vaccine by understanding viral protein structures, and helping medical researchers scour tens of thousands of relevant research papers at an unprecedented pace. Over the last few weeks, teams at the Allen Institute for AI, Google DeepMind, and elsewhere have created AI tools, shared data sets and research results, and shared them freely with the global scientific community.

Vaccines imitate an infection, causing the body to produce defensive white-blood cells and antigens. There are three main types of vaccines: whole-pathogen vaccines, like those for the flu or MMR, use killed or weakened pathogens to elicit an immune response; subunit vaccines, (e.g., pertussis, shingles) use only part of the germ, such as a protein; and nucleic acid vaccines inject genetic material of the pathogen into human cells to stimulate an immune response. The latter is the type of vaccine targeting Covid-19 that began trials this week in the United States. AI is useful in accelerating the development of subunit and nucleic acid vaccines.

An essential part of viruses, proteins are made up of a sequence of amino acids that determine its unique 3D shape. Understanding a protein’s structure is essential to understanding how it works. Once the shape is understood, scientists can develop drugs that work with the protein’s unique shape. But it would take longer than the age of the known universe to examine all possible shapes of a protein before finding its unique 3D structure. Enter AI.

Read the full article in Wired.