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Updated: Aug 6, 2026
08:31
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
Mapping Non-Homologous Pocket Compatibilities to Identify Hidden Drug-Target Relationships: A Pocket Hopping
Yingying Zhang1,2, Tianbiao Yang2,3,4,5, Buying Niu2,3
1Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui 230026, China.
Journal of Medicinal Chemistry
|July 18, 2026
Summary
Pocket hopping, a new machine learning framework, predicts small molecule-protein interactions by learning binding pocket patterns. This approach identifies novel drug targets and mechanisms, advancing drug discovery for nonhomologous proteins.
Area of Science:
- Computational chemistry
- Machine learning
- Drug discovery
Background:
- Predicting small molecule-protein interactions for nonhomologous proteins is difficult due to lack of sequence, fold, or pocket similarity.
- Shared ligand recognition is often not evident through conventional comparison methods.
Purpose of the Study:
- Introduce pocket hopping, a machine learning framework to predict interactions between small molecules and proteins.
- Identify novel drug targets and understand drug mechanisms by analyzing residue-level interaction patterns in binding pockets.
Main Methods:
- Developed a machine learning framework called pocket hopping.
- Learned residue-level interaction patterns from coligand binding pockets.
- Used shared ligands as supervision for inferring compatibility between nonhomologous pockets for similar chemotypes.
Main Results:
- Pocket hopping identified relationships between nonhomologous pockets missed by traditional methods.
- Successfully identified fedratinib and analogues as helicase WRN inhibitors.
- Discovered abexinostat as a direct ENPP1 binder and inhibitor, impacting cGAMP-STING signaling.
Conclusions:
- Pocket-level compatibility is a valuable complement to existing methods for target identification and hit discovery.
- Pocket hopping demonstrates utility in de novo hit identification and mechanistic interpretation.
- The framework aids in polypharmacology analysis and understanding complex biological interactions.
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