Windemuth, A. | bioRxiv Science

bioRxiv2021

Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

The COVID-19 pandemic has led to an urgent need for the identification of new antiviral drug therapies that can be rapidly deployed to treat patients with this disease. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of COVID-19. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cellbased experimental assessment reveals several clinically-relevant repurposing drug candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.

cell biology↗

bioRxiv2018

Comprehensive mapping of Cystic Fibrosis mutations to CFTR protein identifies mutation clusters and molecular docking predicts corrector binding site

BackgroundCystic 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.\n\nMethodsExonic 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.\n\nResultsResidue 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.\n\nConclusionsOur 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.

biochemistry↗