This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: A Baylor College of Medicine-led team has developed a strategy that combines the analysis of thousands of proteins with artificial intelligence to accelerate the discovery of small molecules called molecular glues to treat disease. Their approach, published in Nature Communications, has uncovered a new class of molecular glues that could neutralize harmful proteins linked to blood cancers and autoimmune diseases.
The work also shows how AI-based structural modeling can help chemists optimize compounds well before experiments reveal how they work. "Many scientists are increasingly exploring a new way to treat disease: Instead of blocking harmful proteins, they aim to eliminate them entirely. One promising approach uses molecular glues, which act like matchmakers inside cells," said senior and co-corresponding author Dr.
Jin Wang, director of the Center for NextGen Therapeutics and Michael E. DeBakey, M.D., endowed professor in pharmacology and in the Verna and Marrs McLean Department of Biochemistry and Molecular Pharmacology at Baylor. Wang also is a member of Baylor's Dan L Duncan Comprehensive Cancer Center.
"These compounds bring a target protein to the cell's natural protein-disposal machinery, which destroys the target. In this study, our team discovered and optimized a new class of molecular glues that selectively remove a protein called VAV1, an important regulator of immune cell function that has been linked to blood cancers and autoimmune diseases," Wang said. VAV1 is found mainly in immune cells, where it helps transmit signals that activate T cells and other components of the immune system.
However, abnormal VAV1 activity can contribute to diseases such as T-cell lymphomas and chronic inflammatory disorders. While traditional drugs typically inhibit only one function of a protein, targeted protein disposal eliminates the entire protein, potentially providing a more complete therapeutic effect. "To find compounds capable of degrading VAV1, we screened a library of molecules using high-throughput proteomics, a technology that can assess thousands of proteins simultaneously.
This unbiased analysis revealed a series of compounds, including NGT-201-12, that caused VAV1 levels to drop while affecting relatively few other proteins," said first and co-corresponding author Dr. Hanfeng Lin, a postdoctoral researcher in the Wang lab. "Follow-up experiments confirmed that the compounds worked through the cell's natural protein-recycling system and specifically relied on the protein cereblon (CRBN), a key component of the protein-degradation pathway," Lin said.
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