2D QSAR of 3-(Piperidin-1-yl)-5,6,7,8-Tetrahydropyrido[3,4-b] Pyrazine Derivatives With GPCR-6 Inhibitory Activity

Abstract

We aimed to generate a validated QSAR model with a dataset consisting of 77 3-(piperidin-1-yl)-5,6,7,8-tetrahydropyrido[3,4-b] pyrazine derivatives to elucidate the physicochemical properties of compounds essential for GPCR-6 inhibition and to identify novel lead molecules with enhanced human cAMP-dependent protein kinase A binding activity and bioavailability. Lead optimization and in silico approaches were employed in this research work. QSAR model was generated and validated by exploiting the Multiple Linear Regression method. Prioritization of lead-like compounds was accomplished by performing molecular docking, molecular dynamics simulation, bioavailability assessments, and toxicity prediction, and DFT study. Our research work resulted in the generation of a validated QSAR model with higher degree of external predictive ability and significance for GPCR-6 inhibitory activity. In this study, fifteen designed compounds with reasonable pIC50 have been found to have higher molecular binding affinities and better ADMET properties.