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FDB&FragLinker: A Large Fragment Database for Rapid Ligand Optimization Within Protein-Ligand Complex
Lei Zheng1, Qisheng Zhou2, Tianxiang Fu3
1NYU-ECNU Center for Computational Chemistry, NYU Shanghai, Shanghai 200124, China; Department of Chemistry, New York University, New York, NY 10003, USA.
Journal of Molecular Biology
|March 9, 2026
Summary
Fragment-based drug design is enhanced by FDB&FragLinker, a tool for exploring and reassembling molecular fragments. This covalent docking approach generates high-quality 3D ligand complexes faster than other methods.
Area of Science:
- Computational chemistry
- Drug discovery
- Structural biology
Background:
- Fragment-based drug design is a key strategy for identifying high-quality drug leads.
- Existing methods for molecular modeling and optimization have limitations in speed and structural accuracy.
Purpose of the Study:
- To introduce FDB&FragLinker, an integrated database and covalent optimization tool.
- To enable efficient exploration, modification, and reassembly of molecular fragments for drug design.
Main Methods:
- Utilizing fragments from DrugBank and the ZINC database (800M molecules).
- Implementing a novel 3D complex generation tool based on fragment-level covalent docking.
- Precisely attaching fragments to small molecules at designated connection atoms.
Main Results:
- Generated high-quality 3D protein-optimized ligand complex structures.
- Achieved greater structural fidelity compared to traditional docking methods.
- Demonstrated significantly faster performance than recent diffusion-based generative models.
Conclusions:
- FDB&FragLinker offers a powerful and efficient approach for small molecule optimization and modification.
- The tool is versatile, applicable to PROTACs, small molecule polypeptides, and more.
- FDB&FragLinker is open-source and accessible via a web server and GitHub.
