The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

By Samuel Genheden, Ulf Ryde. Expert Opinion on Drug Discovery, 2015

4,764 citations recorded by the source corpus.

Introduction: The molecular mechanics energies combined with the Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor–ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success. Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0937d71328befd3107326f509413c27a9cb1277f

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Citations in the corpus

• Molecular Docking: Shifting Paradigms in Drug Discovery (2019, background): “Indeed, several studies, showing the improvements that the MM-PBSA and MM-GBSA methods, and BEAR provided, both in a posteriori and prospective virtual screenings, have been reported [44,46], demonstrating that the application of these approaches heavily improves docking results.”
• Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods (2016, methodology): “Alternatively, the ∆Gsolv can be computed by the GBSA implicit solvent model, which is faster and often provides a better accuracy, although its results are sensitive to details in the calculations [225] and, its performance in calculating absolute binding free energy is no better than MM-PBSA [222]”
• Recent Developments and Applications of the MMPBSA Method (2018, methodology): “Since the last comprehensive review of MMPBSA applications in 2015 (Genheden and Ryde, 2015), MMPBSA has continued to see its role in pharmaceutical research and development increase.”
• Molecular dynamics simulations and novel drug discovery (2018, methodology): “Conventional MD can be combined with the MM-PBSA and MM-GBSA methods to obtain binding free energy information on small molecules, which is very important for the ranking and selection of small molecules [135].”
• Best Practices for Constructing, Preparing, and Evaluating Protein-Ligand Binding Affinity Benchmarks [Article v1.0] (2021, background): “[48] Therefore, we must balance the increased confidence that simulation-based FE calculations can impact drug discovery, with the need to further understand, test, and overcome limitations of the current methods.”
• Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks [Article v0.2] (2021, background): “[48] Therefore, we must balance the increased confidence that simulation-based FE calculations can impact drug discovery, with the need to further understand, test, and overcome limitations of the current methods.”