tetano
Editor, Senior Moderator
Biomed Khim. 2016 Nov;62(6):691-703. doi: 10.18097/PBMC20166206691.
[h=1][Prediction of selective inhibition of neuraminidase from various influenza virus strains by potential inhibitors].[/h] [Article in Russian]
Mikurova AV[SUP]1[/SUP], Rybina AV[SUP]1[/SUP], Skvortsov VS[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] A universal model of inhibition of neuraminidases from various influenza virus strains by a particular has been developed. It is based on known 3D data for neuraminidases from three influenza virus strains (A/Tokyo/3/67, A/tern/Australia/G70C/75, B/Lee/40) and modeling of 3D structure of neuraminidases from other strains (A/PR/8/34 ? A/Aichi/2/68). Using docking and molecular dynamics, we have modeled 235 enzyme-ligand complexes for 89 compounds with known IC50 values. Selection of final variants among three results obtained for each enzyme-ligand pair and calculation of independent variables for generation of linear regression equations was performed using MM-PBSA/MM-GBSA. This resulted in the set of equations individual strains and the equations pooling all the data. Thus using this approach it is possible to predict inhibition for neuraminidase from each the considered strains by a particular inhibitor and to predict the range of its action on neuraminidases from various influenza virus strains.
[h=4]KEYWORDS:[/h] QSAR; computational methods; influenza virus neuraminidase; inhibitors
PMID: 28026814
[PubMed - in process]
[h=1][Prediction of selective inhibition of neuraminidase from various influenza virus strains by potential inhibitors].[/h] [Article in Russian]
Mikurova AV[SUP]1[/SUP], Rybina AV[SUP]1[/SUP], Skvortsov VS[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] A universal model of inhibition of neuraminidases from various influenza virus strains by a particular has been developed. It is based on known 3D data for neuraminidases from three influenza virus strains (A/Tokyo/3/67, A/tern/Australia/G70C/75, B/Lee/40) and modeling of 3D structure of neuraminidases from other strains (A/PR/8/34 ? A/Aichi/2/68). Using docking and molecular dynamics, we have modeled 235 enzyme-ligand complexes for 89 compounds with known IC50 values. Selection of final variants among three results obtained for each enzyme-ligand pair and calculation of independent variables for generation of linear regression equations was performed using MM-PBSA/MM-GBSA. This resulted in the set of equations individual strains and the equations pooling all the data. Thus using this approach it is possible to predict inhibition for neuraminidase from each the considered strains by a particular inhibitor and to predict the range of its action on neuraminidases from various influenza virus strains.
[h=4]KEYWORDS:[/h] QSAR; computational methods; influenza virus neuraminidase; inhibitors
PMID: 28026814
[PubMed - in process]