Integrated structure-based activity prediction model of benzothiadiazines on various genotypes of HCV NS5b polymerase (1a, 1b and 4) and its application in the discovery of new derivatives

Abstract

This work presents the first structure-based activity prediction model for benzothiadiazines against various genotypes of HCV NS5b polymerase (1a, 1b and 4).The model is a comprehensive workflow of structure-based field template followed by guided docking. The field template was used as a pre-filter and a tool to provide hits in good orientation and position. It was created based on detailed molecular interaction field analysis which includes Topomer CoMFA, grid independent analysis and Superstar. On the other hand, Guided docking was used as a refinement and assessment tool. It was actively directed by two scores: Moldock score as an interaction descriptor (r(2)=0.65) and a template similarity score as a measure for accurate binding-mode compliance. The docking template was based on energy-based pharmacophore analysis. The whole procedure was formulated and tweaked for both screening (ROC of AUC=0.91) and activity prediction (r(2) of 0.8) for the genotype 1a. In order to widen the model scope, linear interaction energy was used as a tool for predicting activities of other genotypes based on the docked ligand poses while mutation binding energy was used to investigate the effect of each amino acid mutation in genotype 4. The model was applied for structure-based fragment hopping by screening a library designed by reaction enumeration. A top scoring hit was used to generate a focused library such that it has lower TPSA than the original class ligands and thus better pharmacokinetic properties. After that, experimental validation was carried out by the synthesis of this library and its biological evaluation which yielded compounds that exhibit EC(50) ranging from 1.86 to 23 μM.