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

Xiao Liu, Jinfeng Liu, Tong Zhu, Lujia Zhang, Xiao He, John Z.H. Zhang

Research output: Contribution to journalArticlepeer-review


Improving the accuracy of scoring functions for estimating protein-ligand binding affinity is of significant interest as well as practical utility in drug discovery. In this work, PBSA-E, a new free energy estimator based on the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) descriptors, has been developed. This free energy estimator was optimized using high-quality experimental data from a training set consisting of 145 protein-ligand complexes. The method was validated on two separate test sets containing 121 and 130 complexes. Comparison of the binding affinities predicted using the present method with those obtained using three popular scoring functions, i.e., GlideXP, GlideSP, and SYBYL-F, demonstrated that the PBSA-E method is more accurate. This new energy estimator requires a MM/PBSA calculation of the protein-ligand binding energy for a single complex configuration, which is typically obtained by optimizing the crystal structure. The present study shows that PBSA-E has the potential to become a robust tool for more reliable estimation of protein-ligand binding affinity in structure-based drug design.

Original languageEnglish (US)
Pages (from-to)854-861
Number of pages8
JournalJournal of Chemical Information and Modeling
Issue number5
StatePublished - May 23 2016

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • Computer Science Applications
  • Library and Information Sciences


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