A Generalized Prediction Model of Inhibition of Neuraminidase of Influenza Virus of Various Strains

Abstract

Preliminary results of construction of an overall model for prediction of IC₅₀ values of inhibitors of neuraminidase from any influenza virus strains are presented. We used MM-PBSA (MM-GBSA) energy terms calculated for the complexes obtained after modeling of 30 variants of neuraminidase structures, subsequent docking and molecular dynamics simulation as independent variables in prediction equations. The structures of known neuraminidase-inhibiting drugs (oseltamivir, zanamivir and peramivir) and a neuraminidase substrate (MUNANA) were used as ligands. Use of calculation parameters of neuraminidase-inhibitor complexes did not result in the correlation equation with acceptable parameters (R² ≤ 0.3). However, if information about binding energy of the substrate used for neuraminidase assay (and IC₅₀ detection) is included the resultant IC₅₀ prediction equations became significant (R² ≥ 0.55). It is concluded that models joining not only various ligands but also numerous variants of the target protein involved in their binding should take into consideration not only the IC₅₀ value as the target parameter but also binding of the neuraminidase substrate used for experimental determination of the IC₅₀ value. In this case the use of modelled proteins is reasonable. The predictive power of such models depends critically on the quality of the modeling of the ligand-protein complexes.