title: Ensemble fits of restrained peptides' conformational equilibria to NMR data. Dependence on force fields: AMBER/8 ff03 versus ECEPP/3.
abstract: Two variants of NMR-based conformational analyses of flexible peptides are compared using two examples meeting the formula Tyr-D-Daa-Phe-Daa-NH₂ (Daa=diamino acid): 1 combining D-Dab² (α,γ-diaminobutyryl) with Lys⁴, and 2 -D-Dap² (α,β-diaminopropionyl) with Orn⁴. The ω-amino groups of D-Daa² and Daa⁴ are coupled with C=O into the urea, restraining 1 and 2 with 16- and 14-membered rings and leading to potent and impotent μ/δ opioid peptides, respectively. To the current task, we took from an earlier work (Filip et al, J. Pept. Sci. 11 (2005) 347-352) the NMR NOE- and J-data in H₂O/D₂O; and the selection of the ensembles of 1 and 2, 822 and 788 conformational families, respectively, obtained by using the EDMC/ECEPP3 method. Here, we generated ensembles of 1 and 2 using AMBER molecular dynamics in explicit water to eventually selected 686 and 761 conformers for 1 and 2, respectively. We did numbers of fits for both types of the conformational ensembles of 1 and 2 to their NOE- and J-data using a common method i.e. maximum entropy approach (Groth et al, J. Biomol. NMR 15 (1999) 315-330). Both types of the well structurally diversified ensembles fit to quite different equilibria in regressions to common experimental NOE- and J-restraints using maximum entropy principle, which is a disappointing message. Intriguing is startlingly small standard deviation in J-couplings: σ(JNHαH) ≈ 0.01 Hz for LES-MD/AMBER ensemble, contrary to σ(JNHαH) = 0.8 - 1.1 Hz for the EDMC/ECEPP ensemble, over the wide range of entropy, i.e. relatively insensitive to it. A similar feature is not the case when comparing σ(NOE) in both methods. Hence, at minute entropy contributions, it follows that J does or does not transpose "overfitted" into the final σ(J) in the AMBER or ECEPP ensemble, respectively. Could this be an effect of softness of the AMBER flexible-valence force field compared to ECEPP rigid-geometry, and its effect on ensemble sampling? We do not know an answer.
authors.affiliation: Faculty of Chemistry, University of Gdańsk, Sobieskiego 18, 80-952 Gdańsk, Poland.
authors.forename: Jerzy
authors.initials: J
authors.lastname: Ciarkowski
authors.forename: Sylwia
authors.initials: S
authors.lastname: Łuczak
authors.forename: Dawid
authors.initials: D
authors.lastname: Jagieła
authors.forename: Emilia
authors.initials: E
authors.lastname: Sikorska
authors.forename: Jacek
authors.initials: J
authors.lastname: Wójcik
authors.forename: Marta
authors.initials: M
authors.lastname: Oleszczuk
authors.forename: Jan
authors.initials: J
authors.lastname: Izdebski
mesh_terms: D003198:Computer Simulation; D019277:Entropy; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D014867:Water / Q000737:chemistry*
chemical_list: D010455:Peptides; D014867:Water