The Heterocycle Isostere Explorer: A Computational Tool for the Discovery of Novel Aromatic Heterocyclic Isosteres

Abstract

Aromatic heterocycles are central to many areas of chemistry and play an important role in medicinal chemistry, where they are frequently used as bioisosteres to modulate molecular properties while preserving potency. Here, we report the heterocycle isostere explorer (HCIE), an easy-to-use, open-source Python tool for identifying heterocyclic bioisosteres from a custom-built virtual library of over 500,000 optionally functionalized aromatic heterocycles. HCIE employs a unique vector-based alignment and ranks candidates using the combined shape and electrostatic similarity. We describe its use in a series of medicinal chemistry case studies and propose novel 5,5-bicyclic molecules as bioisosteres of 2-pyridine, a common motif in FDA-approved drugs. By integrating 3D similarity metrics with physicochemical descriptors, HCIE provides medicinal chemists with a practical and extensible framework for early stage compound design while highlighting underexplored heterocycles whose predicted utility may motivate the development of new synthetic methodologies.