Molecular modeling and lead design of substituted zanamivir derivatives as potent anti-influenza drugs. Issue 19 (December 2016)

• Record Type: Journal Article
• Authors: Dholakia, Dhwani; Goyal, Sukriti; Jamal, Salma; Singh, Aditi; Das, Asmita; Grover, Abhinav
• Is Part Of: BMC bioinformatics. Volume 17:Issue 19(2016)
• Page Start: 239
• Page End: 249
• Publication Date: 2016-12
• Subjects: Neuraminidase -- H1N1 -- H3N2 -- NA -- Influenza -- QSAR; Bioinformatics -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1186/s12859-016-1374-1
• Languages: English
• ISSNs: 1471-2105

Abstract

Abstract Background Influenza virus spreads infection by two main surface glycoproteins, namely hemagglutinin (HA) and neuraminidase (NA). NA cleaves the sialic acid receptors eventually releasing newly formed virus particles which then invade new cells. Inhibition of NA could limit the replication of virus to one round which is insufficient to cause the disease. Results An experimentally reported series of acylguanidine zanamivir derivatives was used to develop GQSAR model targeting NA in different strains of influenza virus, H1N1 and H3N2. A combinatorial library was developed and their inhibitory activities were predicted using the GQSAR model. Conclusion The top leads were analyzed by docking which revealed the binding modes of these inhibitors in the active site of NA (150-loop). The top compound (AMA) was selected for carrying out molecular dynamics simulations for 15 ns which provided insights into the time dependent dynamics of the designed leads. AMA possessed a docking score of −8.26 Kcal/mol with H1N1 strain and −7.00 Kcal/mol with H3N2 strain. Ligand-bound complexes of both H1N1 and H3N2 were observed to be stable for 11 ns and 7 ns respectively. ADME descriptors were also calculated to study the pharmacokinetic properties of AMA which revealed its drug-like properties.