# AI-Driven Design of Miniproteins as Potential Allosteric Modulators

## TL;DR

This paper reviews how AI is used to design miniproteins that can modulate protein function through allosteric sites, offering new opportunities in drug discovery.

## Contribution

The paper provides a comprehensive review of AI-driven methods for designing miniproteins as allosteric modulators, highlighting recent advances and challenges.

## Key findings

- AI enables the identification of allosteric hotspots and design of miniproteins with high affinity for regulatory surfaces.
- Miniproteins offer advantages over small molecules for targeting structurally diverse allosteric pockets.
- AI-driven approaches are expanding the range of potential targets for allosteric modulation, including GPCRs and ion channels.

## Abstract

Allosteric modulation has emerged as a powerful strategy for achieving superior selectivity and safety in drug discovery and protein function regulation. Unlike highly conserved orthosteric sites, allosteric pockets are structurally diverse and less evolutionarily constrained, making them particularly suitable for modulation by designed miniproteins. Miniproteins can provide extended binding interfaces and high affinity for shallow, dynamic, or cryptic regulatory surfaces that are often inaccessible to small molecules. Recent advances in artificial intelligence (AI) are transforming this field through deep learning-based structure prediction and generative modeling. These AI-driven approaches enable the identification of allosteric hotspots, characterization of conformational ensembles, and de novo design of structured miniprotein binders. They are rapidly expanding the landscape for designing selective modulators across diverse allosteric targets, including GPCRs, receptor tyrosine kinases, nuclear receptors, ion channels, and other protein–protein interaction systems. This review summarizes state-of-the-art AI-driven computational methodologies for designing miniproteins as potential allosteric modulators and discusses their current challenges and future opportunities in allosteric drug discovery.