These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Comparison of the Efficiency of the LIE and MM/GBSA Methods to Calculate Ligand-Binding Energies. Author: Genheden S, Ryde U. Journal: J Chem Theory Comput; 2011 Nov 08; 7(11):3768-78. PubMed ID: 26598269. Abstract: We have evaluated the efficiency of two popular end-point methods to calculate ligand-binding free energies, LIE (linear interaction energy) and MM/GBSA (molecular mechanics with generalized Born surface-area solvation), i.e. the computational effort needed to obtain estimates of a similar precision. As a test case, we use the binding of seven biotin analogues to avidin. The energy terms used by MM/GBSA and LIE exhibit a similar correlation time (∼5 ps), and the equilibration time seems also to be similar, although it varies much between the various ligands. The results show that the LIE method is more effective than MM/GBSA, by a factor of 2-7 for a truncated spherical system with a radius of 26 Å and by a factor of 1.0-2.4 for the full avidin tetramer (radius 47 Å). The reason for this is the cost for the MM/GBSA entropy calculations, which more than compensates for the extra simulation of the free ligand in LIE. On the other hand, LIE requires that the protein is neutralized, whereas MM/GBSA has no such requirements. Our results indicate that both the truncation and neutralization of the proteins may slow the convergence and emphasize small differences in the calculations, e.g., differences between the four subunits in avidin. Moreover, LIE cannot take advantage of the fact that avidin is a tetramer. For this test case, LIE gives poor results with the standard parametrization, but after optimizing the scaling factor of the van der Waals terms, reasonable binding affinities can be obtained, although MM/GBSA still gives a significantly better predictive index and correlation to the experimental affinities.[Abstract] [Full Text] [Related] [New Search]