Assessing the performance of the MM/PBSA and MM/GBSA methods: II. The accuracy of ranking poses generated from docking
By Tingjun Hou, Junmei Wang, Youyong Li, Wei Wang. Journal of Computational Chemistry, 2010
711 citations recorded by the source corpus.
In molecular docking, it is challenging to develop a scoring function that is accurate to conduct high‐throughput screenings. Most scoring functions implemented in popular docking software packages were developed with many approximations for computational efficiency, which sacrifices the accuracy of prediction. With advanced technology and powerful computational hardware nowadays, it is feasible to use rigorous scoring functions, such as molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) in molecular docking studies. Here, we systematically investigated the performance of MM/PBSA and MM/GBSA to identify the correct binding conformations and predict the binding free energies for 98 protein–ligand complexes. Comparison studies showed that MM/GBSA (69.4%) outperformed MM/PBSA (45.5%) and many popular scoring functions to identify the correct binding conformations. Moreover, we found that molecular dynamics simulations are necessary for some systems to identify the correct binding conformations. Based on our results, we proposed the guideline for MM/GBSA to predict the binding conformations. We then tested the performance of MM/GBSA and MM/PBSA to reproduce the binding free energies of the 98 protein–ligand complexes. The best prediction of MM/GBSA model with internal dielectric constant 2.0, produced a Spearman's correlation coefficient of 0.66, which is better than MM/PBSA (0.49) and almost all scoring functions used in molecular docking. In summary, MM/GBSA performs well for both binding pose predictions and binding free‐energy estimations and is efficient to re‐score the top‐hit poses produced by other less‐accurate scoring functions. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011
Subfields: Computational Theory and Mathematics, Molecular Biology, Organic Chemistry
View Paper: https://www.semanticscholar.org/paper/e6c03e25251d8f05d31fcb4f338dbfaf5cbe25cf
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Citations in the corpus
- The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities (2015, methodology): “The method has been used in a range of settings, including protein design [9], protein--protein interactions [10,11], conformer stability [12,13] and re-scoring [14,15].”
- Latest developments in molecular docking: 2010–2011 in review (2013, methodology): “The MM/GBSA and MM/PBSA were compared in terms of pose and binding af fi nity prediction, [74] using the Wang dataset.”