AlphaFold2: A versatile tool to predict the appearance of functional adaptations in evolution: Profilin interactions in uncultured Asgard archaea

The release of AlphaFold2 (AF2), a deep-learning-aided, open-source protein structure prediction program, from DeepMind, opened a new era of molecular biology. The astonishing improvement in the accuracy of the structure predictions provides the opportunity to characterize protein systems from uncultured Asgard archaea, key organisms in evolutionary biology. Despite the accumulation in metagenomics-derived Asgard archaea eukaryotic-like protein sequences, limited structural and biochemical information have restricted the insight in their potential functions. In this review, we focus on profilin, an actin-dynamics regulating protein, which in eukaryotes, modulates actin polymerization through (1) direct actin interaction, (2) polyproline binding, and (3) phospholipid binding. We assess AF2-predicted profilin structures in their potential abilities to participate in these activities. We demonstrate that AF2 is a powerful new tool for understanding the emergence of biological functional traits in evolution.