Fragment based drug design: from experimental to computational approaches

Area of Science:

• Drug discovery and medicinal chemistry
• Biophysics and structural biology
• Computational chemistry and cheminformatics

Background:

• Fragment-based drug design (FBDD) is a successful strategy in modern drug discovery, yielding approved drugs and clinical candidates.
• FBDD identifies low-affinity fragments that bind to biological targets, which are then optimized for high affinity and selectivity.
• This approach requires sensitive biophysical techniques like NMR, X-ray crystallography, and SPR for hit identification.

Purpose of the Study:

• To review experimental and computational screening approaches in FBDD.
• To highlight recent successes in discovering potent lead molecules using FBDD.
• To discuss the integration of computational and experimental methods in drug discovery.

Main Methods:

• Experimental fragment screening using biophysical techniques (NMR, X-ray crystallography, SPR).
• Computational methods for fragment library design, virtual screening, and hit optimization.
• Integration of computational and experimental approaches for enhanced drug discovery.

Main Results:

• FBDD has demonstrated success in identifying lead compounds for various drug discovery projects.
• Biophysical techniques provide crucial information for fragment-to-lead optimization.
• Computational methods address limitations of experimental screening, such as low throughput and high costs.

Conclusions:

• FBDD is a powerful strategy for identifying and optimizing drug leads.
• Combining experimental and computational methods enhances the efficiency and scope of FBDD.
• FBDD, particularly with virtual screening, is applicable to challenging targets like protein-protein interactions and membrane proteins.