Prediction of inhibition of influenza virus neuraminidase of various strains by using a generalized model constructed using the data on the position of known ligands

Abstract

Several variants of models for predicting the IC50 values of inhibitors of influenza virus neuraminidase are presented for both individual strains and for combinations of data for neuraminidases of several strains. They are based on the use of calculated energy contributions to the amount of change in the free energy of enzyme-inhibitor complexes. In contrast to previous works, aimed at the complex modeling, we added a procedure of comparison of the docking variants with one of the neuraminidase inhibitors, for which the structure of the complexes was determined experimentally. The choice of the comparison structure was made according to the similarity of structures evaluated using the Tanimoto metrics and the limit of the RMSD value for a similar part of the structure was no more than 2 Å. Using this limitation and filtering datasets for a particular strain by the Q2 value obtained in the leave-one-out control procedure it is possible to construct equations for predicting the IC50 value with a Q2 value close to the minimum confidence threshold (0.57 in this work). Taking into consideration that in this version of the prediction, a minimum set of energy contributions is used, which does not provide for expensive calculations of entropy contributions, the result obtained supports the correctness of using a generalized model based on the data on the position of known ligands to predict the inhibition of neuraminidase of the influenza virus of various strains.