Back

A Topological Switch Enables Misfolding of the Cystic Fibrosis Transmembrane Conductance Regulator

Daniel Scholl; Maud Sigoillot; Marie Overtus; Rafael Colomer Martinez; Chloé Martens; Yiting Wang; Els Pardon; Toon Laeremans; Abel Garcia-Pino; Jan Steyaert; David Noel Sheppard; Jelle Hendrix; Cédric Govaerts

2020-07-10 biochemistry
10.1101/2020.07.09.195099 bioRxiv
Show abstract

Cystic Fibrosis (CF) is a common lethal genetic disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) anion channel. Misfolding and degradation of CFTR are the hallmarks of the predominant mutation, F508del, located in the first nucleotide binding domain (NBD1). While the mutation is known to affect the thermal stability of NBD1 and assembly of CFTR domains, the molecular events that lead to misfolding of F508del-CFTR remain elusive. Here, we demonstrate that NBD1 of CFTR can adopt an alternative conformation that departs from the canonical NBD fold previously observed for CFTR and other ATP-binding cassette (ABC) transporter proteins. Crystallography studies reveal that this conformation involves a topological reorganization of the {beta}-subdomain of NBD1. This alternative state is adopted by wild-type CFTR in cells and enhances channel activity. Single-molecule fluorescence resonance energy transfer microscopy shows that the equilibrium between the conformations is regulated by ATP binding. Under destabilizing conditions, however, this conformational flexibility enables unfolding of the {beta}-subdomain. Our data indicate that in wild-type CFTR switching to this topologically-swapped conformation of NBD1 regulates channel function, but, in the presence of the F508del mutation, it allows domain misfolding and subsequent protein degradation. Our work provides a framework to design conformation-specific therapeutics to prevent noxious transitions.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.