Image credit: Jerelle A. Joseph (CC BY 4.0)
Our cells contain tens of thousands of different proteins that carry out essential activities to keep us alive. Some of these proteins have long, flexible regions where many of the same amino acid building blocks are repeated in the sequence. These ‘prion-like low-complexity domains’ (known as PLDs for short) aid in organising cellular processes by helping to form concentrated droplets of proteins within cells, known as biomolecular condensates.
Mutations in PLDs can make these condensates unstable, potentially leading to harmful protein clumps, or aggregates, that are linked to neurodegenerative diseases. However, the exact impact of specific PLD mutations on health and disease remains an open question.
To investigate this, Maristany et al. used a highly accurate computational model to simulate how 140 different PLD mutations from six proteins affected condensate stability. This analysis showed that specific types of mutations, especially of amino acids with certain properties, have predictable effects on PLD condensate behaviour. The changes in stability followed consistent scaling laws across all six proteins tested, and the data and framework generated from this simulation could help to predict condensate formation in other proteins.
The findings of Maristany et al. help to explain how PLDs regulate biomolecular condensates and how their dysregulation might lead to disease. The predictive scaling laws could one day help researchers to design therapies that restore biomolecular condensate stability in neurodegenerative disorders. However, further research is needed to test whether these predictive models apply in more complex living cells and animals.
