A Method for Automated Pharmacophore Model Generation Using Multiple Copy Simultaneous Search

Abstract

Pharmacophores are three‐dimensional arrangements of molecular features required for biological activity that are often used in virtual screening efforts to prioritize ligands for experimental screening. G protein‐coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for ligand discovery and drug development. Ligand‐based pharmacophore models can be constructed to identify structural commonalities between known bioactive ligands for targets including GPCR. However, structure‐based pharmacophores (which only require a resolved or predictive structure for a protein) have gained more attention as the number of publicly available, high‐resolution GPCR structures have increased (113 unique GPCR represented as of November 24, 2021). Thus, the goal of this study was to develop a method of structure‐based pharmacophore model generation applicable to ligand discovery for GPCR with few known ligands. Pharmacophore models have been generated using the active sites of 8 class A GPCR crystal structures via automated feature annotation of 5 randomly selected functional group fragments in an attempt to sample diverse combinations of pharmacophore features to aid in virtual screening efforts. Each of the 5000 generated pharmacophores was then used to search a database containing active and decoy/inactive compounds for 30 class A GPCR and scored using enrichment factor and goodness‐of‐hit metrics to assess performance. As proof‐of‐principle for this method, pharmacophore models were also generated within two dopamine receptor 2 (D2) crystal structures to elucidate novel ligands possessing activity for this receptor. Application of this method to the set of 8 class A GPCR generated pharmacophore models possessing the theoretical maximum enrichment factor value in both resolved structures (8 of 8 cases) and predictive models (7 of 8 cases), implying that generated pharmacophore models will prove useful in the context of virtual screening. Furthermore, application of this protocol to the D2 receptor resulted in the identification of novel candidate ligands whose activity has been confirmed with two in vitroactivity assays.