Balancing target flexibility and target denaturation in computational fragment-based inhibitor discovery

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Structure-based drug design faces challenges in accounting for target flexibility and identifying inhibitor binding "hot spots," particularly for protein-protein interactions.
• Computational fragment-based approaches using molecular dynamics (MD) simulations offer a promising solution but require optimized conditions to balance target flexibility and prevent denaturation.

Purpose of the Study:

• To identify optimal MD conditions for fragment-based drug design that allow for target flexibility while preventing denaturation.
• To validate these conditions using the cytokine IL-2, a protein with cryptic binding sites.

Main Methods:

• Utilized Site Identification by Ligand Competitive Saturation (SILCS), a computational fragment-based approach employing MD simulations.
• Optimized MD conditions to either prevent or identify and exclude trajectories with subtle protein denaturation.
• Employed hydrophobic fragments and acetonitrile as test fragments.

Main Results:

• Identified optimal MD conditions that successfully prevented IL-2 denaturation.
• SILCS with hydrophobic fragments accurately identified two known cryptic binding sites in IL-2.
• Acetonitrile, a water-miscible fragment, failed to identify binding sites and induced target denaturation, highlighting the importance of fragment selection.

Conclusions:

• Optimized MD conditions coupled with SILCS can effectively identify cryptic binding sites in flexible proteins without causing denaturation.
• The choice of molecular fragment is critical; hydrophobic fragments are suitable for identifying binding sites, whereas some water-miscible fragments may induce denaturation.
• This approach advances structure-based drug design for challenging targets like protein-protein interaction interfaces.