Comparison of a QM/MM force field and molecular mechanics force fields in simulations of alanine and glycine “dipeptides” (Ace‐Ala‐Nme and Ace‐Gly‐Nme) in water in relation to the problem of modeling the unfolded peptide backbone in solution
- 10 January 2003
- journal article
- research article
- Published by Wiley in Proteins-Structure Function and Bioinformatics
- Vol. 50 (3) , 451-463
- https://doi.org/10.1002/prot.10279
Abstract
We compare the conformational distributions of Ace‐Ala‐Nme and Ace‐Gly‐Nme sampled in long simulations with several molecular mechanics (MM) force fields and with a fast combined quantum mechanics/molecular mechanics (QM/MM) force field, in which the solute's intramolecular energy and forces are calculated with the self‐consistent charge density functional tight binding method (SCCDFTB), and the solvent is represented by either one of the well‐known SPC and TIP3P models. All MM force fields give two main states for Ace‐Ala‐Nme, β and α separated by free energy barriers, but the ratio in which these are sampled varies by a factor of 30, from a high in favor of β of 6 to a low of 1/5. The frequency of transitions between states is particularly low with the amber and charmm force fields, for which the distributions are noticeably narrower, and the energy barriers between states higher. The lower of the two barriers lies between α and β at values of ψ near 0 for all MM simulations except for charmm22. The results of the QM/MM simulations vary less with the choice of MM force field; the ratio β/α varies between 1.5 and 2.2, the easy pass lies at ψ near 0, and transitions between states are more frequent than for amber and charmm, but less frequent than for cedar. For Ace‐Gly‐Nme, all force fields locate a diffuse stable region around ϕ = π and ψ = π, whereas the amber force field gives two additional densely sampled states near ϕ = ±100° and ψ = 0, which are also found with the QM/MM force field. For both solutes, the distribution from the QM/MM simulation shows greater similarity with the distribution in high‐resolution protein structures than is the case for any of the MM simulations. Proteins 2003;50:451–463.Keywords
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