3D pharmacophore models are three‐dimensional ensembles of chemically defined interactions of a ligand in its bioactive conformation. They represent an elegant way to decipher chemically encoded ligand information and have therefore become a valuable tool in drug design. In this review, we provide an overview on the basic concept of this method and summarize key studies for applying 3D pharmacophore models in virtual screening and mechanistic studies for protein functionality. Moreover, we discuss recent developments in the field. The combination of 3D pharmacophore models with molecular dynamics simulations could be a quantum leap forward since these approaches consider macromolecule–ligand interactions as dynamic and therefore show a physiologically relevant interaction pattern. Other trends include the efficient usage of 3D pharmacophore information in machine learning and artificial intelligence applications or freely accessible web servers for 3D pharmacophore modeling. The recent developments show that 3D pharmacophore modeling is a vibrant field with various applications in drug discovery and beyond.This article is categorized under: Computer and Information Science > Chemoinformatics Computer and Information Science > Computer Algorithms and Programming Molecular and Statistical Mechanics > Molecular Interactions

The human cytochrome P450 (CYP) enzyme CYP4A22 is an orphan CYP with unknown function. Here, through functional expression in fission yeast, we show that CYP4A22 catalyzes fatty acid hydroxylation as well as aliphatic or aromatic hydroxylations of luciferin‐based probe substrates. Mechanistic molecular modeling of CYP4A22 suggests that its ω‐hydroxylation activity is hampered by a more spacious active site compared to CYP4B1. Substrate recognition via side‐chains R96 and R233 is indicated by dynamic three‐dimensional pharmacophores (dynophores) derived from molecular dynamics simulations. CYP4A22 activity is inhibited by three unspecific CYP inhibitors. A comparison of CYP4A22*1 (the reference standard sequence) with CYP4A22‐WT (the most common allele) revealed that for the four substrates tested the WT‐enzyme always had lower activity.