Revolutionizing Drug Discovery: Breakthrough Method Predicts Small Molecule-Protein Interactions at Scale”

A New Avenue for Drug Discovery: Innovative Approach Predicts Large-Scale Interactions between Small Molecules and Proteins
Identifying small molecules that chemically bind to human proteins (known as “ligands”) is a crucial step in drug development. However, the lack of knowledge about these ligands for most human proteins has been a major hurdle in developing new medicines.
In a groundbreaking collaboration between researchers at CeMM and Pfizer, a novel method has been developed and expanded to measure the binding activity of hundreds of small molecules against thousands of human proteins. This large-scale study has unveiled tens of thousands of ligand-protein interactions, offering new avenues for the development of chemical tools and therapeutics.
Published in the journal Science, this research harnesses the power of machine learning and artificial intelligence to predict how small molecules interact with all proteins within living human cells, providing unprecedented insights into drug discovery.
The majority of drugs are small molecules that modulate protein activity, making them indispensable for biological research. However, the lack of known small-molecule binders for over 80% of human proteins has hindered drug development and biological understanding.
To address this gap, researchers at CeMM and Pfizer have scaled up an experimental platform to assess how diverse small molecules interact with all expressed proteins in living cells. This has resulted in a comprehensive catalog of ligand-protein interactions, offering promising starting points for therapeutic development.
Led by CeMM PI Georg Winter, the study demonstrates the development of small-molecule binders targeting cellular transporters, components of cellular degradation machinery, and understudied proteins involved in signal transduction. Additionally, leveraging the vast dataset, machine learning models have been developed to predict interactions between small molecules and proteins in human cells.
Winter highlights the transformative role of artificial intelligence in understanding small-molecule behavior, expressing optimism about the potential of this catalog and associated AI models to accelerate drug discovery.
To facilitate broader access and utilization, all data and models from this collaboration are freely available through a web application, representing a significant step forward in open science.
Dr. Patrick Verhoest, Vice President and Head of Medicine Design at Pfizer, lauds the fruitful partnership between industry and academia, underscoring the collective effort behind this three-year project as a remarkable achievement.

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