HT-SuMD: making molecular dynamics simulations suitable for fragment-based screening. A comparative study with NMR

Area of Science:

• Computational chemistry
• Drug discovery
• Structural biology

Background:

• Fragment-based lead discovery (FBLD) is a key strategy for developing novel therapeutics.
• Bcl-X_L is a crucial oncological target regulating apoptosis via protein-protein interactions.

Purpose of the Study:

• Introduce High-Throughput Supervised Molecular Dynamics (HT-SuMD) for automated fragment screening.
• Prioritize fragments for FBLD campaigns using computational methods.
• Validate HT-SuMD's efficacy against experimental techniques.

Main Methods:

• Applied HT-SuMD to screen fragment libraries against the Bcl-X_L protein target.
• Validated HT-SuMD performance against 100 fragments using NMR-based screening.
• Conducted a larger virtual screening of 300 additional fragments, followed by NMR validation.

Main Results:

• Demonstrated remarkable agreement between HT-SuMD and NMR-based screening for fragment identification.
• Successfully identified and validated multiple Bcl-X_L binders using the HT-SuMD protocol.
• Achieved the largest computational fragment screening to date entirely based on molecular dynamics.

Conclusions:

• HT-SuMD is a valuable computational tool for prioritizing fragments in FBLD.
• The protocol offers an efficient and scalable approach for drug discovery campaigns.
• This study establishes a new benchmark for computational fragment screening using molecular dynamics.