‘Alpha’

Inspired by Google Deep Mind's AlphaFold database.

Researching and referencing protein folds as contemporary art is a reoccurring narrative in my practice. Solving the protein folding problem has proved to be a crucial topic of our era, not only because it can revolutionise our understanding of biology, but also in how open-access databases have influenced the way we consume AI predicted information. Google DeepMind's deep learning AlphaFold has made a significant stride in predicting protein structures accurately, and this is the source that I’ve been using for a number of years to re-present protein folds as contemporary art.

This project can be seen as a metaphor for the intersection of science, technology and human understanding, exploring how complex processes influence life and innovation, by re-creating protein structures as paintings and sculptures.

This project continues to move through different stages of development, with an initial period of research followed by digital drawings taking reference directly from AlphaFold. Now the project is moving into experiments with 3D printed prototypes and the sourcing of sustainable materials to achieve net zero artist goals.

One of the main reasons why I’ve been so engaged with protein folds, beyond the groundbreaking ability to predict them, is how protein can be extracted from food waste and used as bio fuel or non-human food.