1. Introduction
- Definition of FBDD: Fragment-Based Drug Discovery (FBDD) is a method in drug discovery that involves identifying small, low-molecular-weight compounds (fragments) that bind to biological targets with low affinity. These fragments serve as starting points for drug development and are optimized to improve binding affinity and selectivity.
- Importance in Drug Discovery: FBDD has become an essential technique, especially for targets that are challenging to drug with traditional high-throughput screening (HTS). FBDD enables the discovery of novel chemical scaffolds and drug candidates for complex and previously undruggable targets.
- Objective: This report discusses the key aspects of FBDD, including fragment libraries, screening techniques, fragment evolution, and case studies demonstrating its success.
2. Principles of Fragment-Based Drug Discovery
- Fragment Libraries: Unlike traditional drug-like molecules, fragments are smaller (150-250 Da) and contain fewer functional groups. This simplicity allows fragments to bind in unique ways to targets.
- Binding Affinity: Fragments typically bind weakly (in the micromolar to millimolar range) but specifically to target sites. These interactions can be optimized into high-affinity drug-like molecules through structure-based design.
- Hit-to-Lead Process: Fragment hits are systematically modified or "grown" into larger molecules with improved potency, specificity, and drug-like properties.
3. FBDD Process
- 1. Library Design and Screening
- 2. Hit Identification and Validation
- 3. Fragment Optimization
- 4. Lead Optimization and Validation
4. Advantages of FBDD
- Broad Target Space: FBDD is effective for targeting complex or "undruggable" proteins like protein-protein interactions (PPIs) or enzymes with shallow binding pockets.
- Efficient Library Size: Due to the small library size, FBDD is often more cost-effective and manageable than traditional HTS, which requires screening large numbers of compounds.
- High Hit Rate: Fragment libraries have high hit rates despite low affinities, as the fragments are smaller and more likely to fit into diverse binding sites on proteins.
- Structure-Based Drug Design (SBDD): FBDD provides structural information early in the process, guiding rational drug design and leading to efficient optimization of binding interactions.
5. Challenges of FBDD
- Low Affinity of Fragments: Fragments typically bind weakly, making their detection challenging without sensitive biophysical methods.
- Optimization Complexity: Fragment hits require extensive optimization to achieve sufficient binding affinity and selectivity.
- High-Quality Protein Production: Structural methods like X-ray crystallography and NMR require high-quality, stable protein samples, which can be resource-intensive.
6. Applications of FBDD
- Drug Discovery for Challenging Targets: FBDD is often employed in discovering drugs for cancer, infectious diseases, and neurodegenerative conditions, where traditional HTS methods have limited success.
- Protein-Protein Interactions (PPIs): FBDD has shown promise in modulating PPIs, which are traditionally difficult to target due to their large and flat interaction surfaces.
- Kinase Inhibitors: FBDD has contributed to the development of selective kinase inhibitors, which are crucial in cancer therapy.
7. Case Studies in FBDD
- 1. Discovery of Vemurafenib (Zelboraf):Target: Mutant BRAF kinase in melanoma.Process: Fragments identified binding pockets, and structure-based optimization was used to develop Vemurafenib, which showed high specificity for the mutant BRAF and was approved for treating melanoma.
- 2. Development of Venetoclax (Venclexta):Target: BCL-2 protein in chronic lymphocytic leukemia.Process: FBDD was used to identify fragments binding to the BCL-2 protein. Optimization led to Venetoclax, a potent BCL-2 inhibitor that selectively induces cancer cell death by blocking the survival pathway.
- 3. Application in Antibiotic Discovery:Target: Beta-lactamase enzymes in resistant bacteria.Process: FBDD identified fragments that bind to the enzyme’s active site. Through fragment linking and growing, potent inhibitors were developed, providing a foundation for antibiotic discovery against resistant pathogens.
8. Future Directions and Innovations in FBDD
- Machine Learning and AI: AI algorithms are being integrated into FBDD to predict binding interactions and optimize fragments more efficiently.
- Automated Screening Platforms: Robotics and automated platforms allow for high-throughput fragment screening, enhancing the pace of discovery.
- Integration with Other Drug Discovery Methods: FBDD is being combined with DNA-encoded libraries, HTS, and computational modeling to expand its reach and effectiveness across drug discovery.
9. Conclusion
- Fragment-Based Drug Discovery has emerged as a powerful approach in modern drug development. It enables the identification of novel small molecules with high potential for drug optimization, especially for challenging targets.
- FBDD’s structure-based approach provides a robust framework for rational drug design, allowing scientists to develop compounds with high specificity and desirable pharmacological properties.
- As advancements in screening technologies, computational methods, and structural biology continue, FBDD is likely to play an increasingly central role in drug discovery and development for a variety of diseases.
References
- Erlanson, D. A., et al. (2016). "Fragment-Based Drug Discovery: Progress, Challenges, and Opportunities." Journal of Medicinal Chemistry, 59(7), 2834-2849.
- Hajduk, P. J., & Greer, J. (2007). "A decade of fragment-based drug design: Strategic advances and lessons learned." Nature Reviews Drug Discovery, 6, 211-219.
- Lamoree, B., & Hubbard, R. E. (2017). "Current perspectives in fragment-based lead discovery (FBLD)." Essays in Biochemistry, 61, 453-464.
