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

## TL;DR

This paper introduces a new computational tool for finding aromatic heterocyclic bioisosteres to aid drug design.

## Contribution

The paper introduces HCIE, a novel open-source tool for identifying heterocyclic bioisosteres using 3D similarity metrics.

## Key findings

- HCIE identifies novel 5,5-bicyclic molecules as bioisosteres of 2-pyridine.
- The tool uses shape and electrostatic similarity to rank heterocyclic candidates.
- HCIE highlights underexplored heterocycles with potential for new synthetic methods.

## 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.