Advancing Drug Discovery through Enhanced Free Energy Calculations.

Area of Science:

• Computational chemistry
• Drug discovery
• Molecular modeling

Background:

• Accurate prediction of protein-ligand binding free energies is crucial for drug discovery.
• Advancements in computing power and simulation methods enable reliable free energy calculations.
• Free energy calculations are increasingly guiding small molecule drug discovery.

Purpose of the Study:

• To outline methodological advances in free energy calculations for drug discovery.
• To demonstrate the accuracy and impact of the FEP+ approach in optimizing drug candidates.
• To discuss the integration and future development of free energy calculations in drug discovery pipelines.

Main Methods:

• Utilized Replica Exchange with Solute Tempering (REST2) enhanced sampling.
• Incorporated REST2 with conventional Free Energy Perturbation (FEP) via FEP/REST.
• Employed the OPLS3 force field and advanced simulation setups within the FEP+ approach.

Main Results:

• FEP+ demonstrated high accuracy in potency prediction (better than 1 kcal/mol), impacting lead optimization.
• Successfully deployed thousands of FEP+ calculations to optimize potency, selectivity, and solubility simultaneously.
• Showcased the approach's power in solving challenging drug design problems and enabling exploration of vast chemical spaces.

Conclusions:

• FEP+ calculations provide robust and accurate results within the classical simulation paradigm.
• Free energy calculations have reached an inflection point, significantly impacting drug discovery.
• Optimized integration of FEP+ into drug discovery workflows maximizes the benefits of computational design for clinical candidates.