Cystic Fibrosis Transmembrane Conductance Regulator

Cystic Fibrosis (CF) is a lung and multi-organ disease caused by over 1000 identified patient mutations that destabilize the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR), an epithelial anion channel protein. CFTR is composed of two transmembrane domains (TMD1/2), two nucleotide binding domains (NBD1/2 - which each contain sub-domains), and an unstructured regulatory domain1. Mutations cause CFTR to misfold and become degraded by the cell. Thus, the CF patient phenotype lacks anion equilibrium in the lung epithelia leading to hindered mucus transport. Subsequent mucus build-up becomes prone to infection, resulting in pneumonia and death.

The most common CF patient mutation ΔF508 CFTR (present in 90% of patients) remains thermodynamically unstable2,3. The current paradigm for CF treatment involves stabilizing ΔF508 CFTR with small molecules called pharmacological chaperones4. Pharmacological chaperones stabilize distinct CFTR domains5 or domain interfaces6 and lead to proper CFTR folding2,7,8. However, the first CFTR pharmacological chaperones were discovered through phenotypic screens and their molecular mechanisms remain unclear. Furthermore, rare CFTR misfolding variants such as G85E and N1303K remain untreatable with current therapies. Understanding the structural basis of CFTR drugs will lead to improved therapies for patients.

To determine the underlying molecular mechanism of CF treatments, we built ΔF508 CFTR models in silico with Rosetta, docked CF pharmacological chaperones to the structures using Rosetta Ligand9, and benchmarked methods for sampling CFTR conformational space by comparing our simulation results to published experimental data. VX-809 confers stability to CFTR primarily by binding deep in a transmembrane region pocket and stabilizing contacting residues10. We plan to use these models for computational drug design for untreatable variants. We work with experimental collaborators in the Plate Lab at Vanderbilt ( and the Schlebach Lab at Indiana University ( to complement our modeling approaches, train data, and test emerging CF drugs in live cells.