@article{
author = "Radošević, Draginja and Senćanski, Milan V. and Perović, Vladimir R. and Veljković, Nevena V. and Prljić, Jelena and Veljković, Veljko and Mantlo, Emily and Bukreyeva, Natalya and Paessler, Slobodan and Glišić, Sanja",
year = "2019",
abstract = "Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture. © 2019 Radosevic, Sencanski, Perovic, Veljkovic, Prljic, Veljkovic, Mantlo, Bukreyeva, Paessler and Glisic.",
journal = "Frontiers in Cellular and Infection Microbiology",
title = "Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors",
volume = "9",
pages = "67",
doi = "10.3389/fcimb.2019.00067"
}
