Abstract
The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.
Highlights
It is widely accepted that high-level quantum mechanical (QM) methods provide the most detailed and accurate description of molecular structures, dynamics, and functions
We focus on recent developments and applications of the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) method that have been reported since 2014, which was roughly the time when the last major MMPBSA review was published (Genheden and Ryde, 2015)
The MMPBSA method is most often applied to the calculation of binding free energies ( Gbind) of small molecule ligands bound to large biomolecule receptors, large inter-biomolecular recognitions are often reported as reviewed below
Summary
Changhao Wang 1, 2, 3, D’Artagnan Greene 2, Li Xiao 2, 4, Ruxi Qi 2 and Ray Luo 1, 2, 4, 5*. Specialty section: This article was submitted to Molecular Recognition, a section of the journal Frontiers in Molecular Biosciences. The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. We focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method
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