Biology subjects

Richardson, G.

Publications and source records attributed to Richardson, G..

2 recordsLinked to original sources

bioRxiv2025

Activation of pro-survival autophagy by a small molecule promoting p62 oligomerisation

Autophagy is a critical mechanism of cellular quality control, orchestrated by selective autophagy receptor (SAR) proteins. Pharmacologically enhancing the cargo-targeting capacity of SARs presents an attractive but underexplored strategy for the precise therapeutic activation of autophagy. Here, we characterise SQ-1, a small-molecule activator of autophagy that targets the prototypical SAR protein p62/SQSTM1 (sequestosome-1). We show that SQ-1 sensitises p62 to oxidation and promotes its disulphide-mediated oligomerisation in response to mitochondrial reactive oxygen species (ROS). This ROS-dependent activation of p62-mediated selective autophagy enhances the clearance of ROS-generating mitochondria and restores cell viability in models of Niemann-Pick type C1 (NPC1) disease, which is marked by impaired autophagic flux. In summary, the unique mode of action of SQ-1 enables self-regulated autophagy activation, offering a potential therapeutic strategy for lysosomal storage disorders and a broader spectrum of age-related diseases characterised by defective autophagy.

cell biology↗

bioRxiv2024

PIRATE: Plundering AlphaFold Predictions to Automate Protein Engineering

An important characteristic for many proteins is the presence of flexible loops or linkers known as intrinsically disordered regions. One downside to many of the state-of-the-art disorder prediction approaches is that they require significant computational time for each inference. Here, we introduce three novel surrogate models trained on AlphaFold2 predictions that rapidly encode local, regional, and global structural properties directly from primary sequence. We combined the outputs from these surrogate models, in an approach we term PIRATE, and show that this approach approximates the performance of AlphaFold2 for disorder prediction. Additionally, we show that PIRATE is much more sensitive to the effects of point mutants on disorder at distal sites than many current disorder prediction methods. Furthermore, we show that in the context of a greedy exploration algorithm, PIRATEs ability to evaluate differences between point mutants makes it ideal for automating disorder-related protein engineering tasks.

biochemistry↗