10.3389/fcimb.2019.00067.s002
Draginja Radosevic
Draginja
Radosevic
Milan Sencanski
Milan
Sencanski
Vladimir Perovic
Vladimir
Perovic
Nevena Veljkovic
Nevena
Veljkovic
Jelena Prljic
Jelena
Prljic
Veljko Veljkovic
Veljko
Veljkovic
Emily Mantlo
Emily
Mantlo
Natalya Bukreyeva
Natalya
Bukreyeva
Slobodan Paessler
Slobodan
Paessler
Sanja Glisic
Sanja
Glisic
Table_2_Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors.XLSX
Frontiers
2019
influenza A
IAV matrix protein 2
drug repurposing
virtual screening
drug resistance
2019-03-26 04:41:51
Dataset
https://frontiersin.figshare.com/articles/dataset/Table_2_Virtual_Screen_for_Repurposing_of_Drugs_for_Candidate_Influenza_a_M2_Ion-Channel_Inhibitors_XLSX/7891580
<p>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.</p>