PBSA_E: A PBSA-Based Free Energy Estimator for Protein-Ligand Binding Affinity

Area of Science:

• Computational chemistry
• Molecular modeling
• Drug discovery

Background:

• Accurate estimation of protein-ligand binding affinity is crucial for drug discovery.
• Existing scoring functions have limitations in predicting binding affinities reliably.

Purpose of the Study:

• To develop and validate a new free energy estimator, PBSA_E, for improved protein-ligand binding affinity prediction.
• To compare the accuracy of PBSA_E against established scoring functions.

Main Methods:

• Developed PBSA_E based on molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) descriptors.
• Optimized PBSA_E using experimental data from a training set of 145 protein-ligand complexes.
• Validated the method on two independent test sets (121 and 130 complexes).

Main Results:

• PBSA_E demonstrated higher accuracy in predicting binding affinities compared to GlideXP, GlideSP, and SYBYL_F.
• The method requires a single MM/PBSA calculation per complex, typically from an optimized crystal structure.

Conclusions:

• PBSA_E shows significant potential as a robust tool for reliable protein-ligand binding affinity estimation.
• This advancement can aid in structure-based drug design by providing more accurate predictions.