RT Journal Article
SR Electronic
T1 Comprehensive mapping of Cystic Fibrosis mutations to CFTR protein identifies mutation clusters and molecular docking predicts corrector binding site
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 242073
DO 10.1101/242073
A1 Steven V. Molinski
A1 Vijay M. Shahani
A1 Adithya S. Subramanian
A1 Stephen S. MacKinnon
A1 Geoffrey Woollard
A1 Marcon Laforet
A1 Onofrio Laselva
A1 Leonard D. Morayniss
A1 Christine E. Bear
A1 Andreas Windemuth
YR 2018
UL http://biorxiv.org/content/early/2018/01/02/242073.abstract
AB Background Cystic Fibrosis (CF) is caused by mutations in the CFTR gene, of which over 2000 have been reported to date. Mutations have yet to be analyzed in aggregate to assess their distribution across the tertiary structure of the CFTR protein, an approach that could provide valuable insights into the structure-function relationship of CFTR. In addition, the binding site of Class I correctors (VX-809, VX-661, C18) is not well understood.Methods Exonic CFTR mutations and mutant allele frequencies described in three curated databases (ABCMdb, CFTR1 and CFTR2, comprising >130,000 data points) were mapped to two different structural models: a homology model of full-length CFTR protein in the open-channel state, and a cryo-electron microscopy core-structure of CFTR in the closed-channel state. Immunoblotting confirmed the approximate binding site of Class I correctors, and molecular docking generated binding poses for their complex with the cryo-electron microscopy structure.Results Residue positions of six high-frequency mutant CFTR alleles were found to spatially co-localize in CFTR protein, and a significant cluster was identified at the NBD1:ICL4 interdomain interface. Further, Class I correctors VX-809, VX-661 and C18 were shown to act via a similar mechanism in vitro, and a putative multi-domain corrector binding site near residues F374-L375 was predicted in silico.Conclusions Our results confirm the significance of interdomain interfaces as susceptible to disruptive mutation, and identify a putative corrector binding site. The structural pharmacogenomics approach of mapping mutation databases to protein models shows promise for facilitating drug discovery and personalized medicine for monogenetic diseases.