NEMAT: An Automated Nonequilibrium Free-Energy Framework for Predicting Ligand Affinity in Membrane Proteins

Area of Science:

• Computational chemistry
• Biophysics
• Pharmacology

Background:

• Accurate quantification of small-molecule protein binding is crucial for drug discovery.
• Computational free-energy methods are powerful but challenged by membrane proteins due to the lipid bilayer's thermodynamic effects.
• Existing methods lack automation for nonequilibrium approaches in membrane protein simulations and decomposition of binding free energy.

Purpose of the Study:

• To develop an automated framework for nonequilibrium alchemical free-energy calculations of membrane proteins.
• To enable the decomposition of binding free energy into membrane-partitioning and protein-specific components.
• To improve the accuracy and interpretability of binding affinity predictions for membrane-embedded targets.

Main Methods:

• Developed Nonequilibrium Membrane Alchemical Transformations (NEMAT), an open-source computational framework.
• Implemented automated nonequilibrium alchemical transformations in various environments: water, membranes, and membrane-embedded proteins.
• Validated NEMAT by comparing its predictions to experimental binding energy trends for P2Y1 ligands.

Main Results:

• NEMAT successfully reproduces experimental binding energy trends for P2Y1 ligands with accuracy comparable to equilibrium methods.
• The framework offers systematic control over simulation parameters, optimizing free-energy estimates.
• NEMAT effectively dissects binding free energy into contributions from the lipid membrane and the protein.

Conclusions:

• NEMAT provides an automated and accurate approach for calculating binding free energies of membrane proteins using nonequilibrium methods.
• The framework's ability to decompose binding energy components enhances mechanistic understanding and supports rational drug design.
• NEMAT represents a significant advancement for computational studies of membrane protein-ligand interactions.