Experimental verification of force fields for molecular dynamics simulations using Gly-Pro-Gly-Gly.
Experimental NMR verification of MD simulations using 12 different force fields (AMBER, CHARMM, GROMOS, and OPLS-AA) and 5 different water models has been undertaken to identify reliable MD protocols for structure and dynamics elucidations of small open chain peptides containing Gly and Pro. A conformationally flexible tetrapeptide Gly-Pro-Gly-Gly was selected for NMR (3)J-coupling, chemical shift, and internuclear distance measurements, followed by their calculations using 2 μs long MD simulations in water. In addition, Ramachandran population maps for Pro-2 and Gly-3 residues of GPGG obtained from MD simulations were used for detailed comparisons with similar maps from the protein data bank (PDB) for large number of Gly and Pro residues in proteins. The MD simulations revealed strong dependence of the populations and geometries of preferred backbone and side chain conformations, as well as the time scales of the peptide torsional transitions on the force field used. On the basis of the analysis of the measured and calculated data, AMBER99SB is identified as the most reliable force field for reproducing NMR measured parameters, which are dependent on the peptide backbone and the Pro side chain geometries and dynamics. Ramachandran maps showing the dependence of conformational populations as a function of backbone ϕ/ψ angles for Pro-2 and Gly-3 residues of GPGG from MD simulations using AMBER99SB, AMBER03, and CHARMM were found to resemble similar maps for Gly and Pro residues from the PDB survey. Three force fields (AMBER99, AMBER99ϕ, and AMBER94) showed the least satisfactory agreement with both the solution NMR and the PDB survey data. The poor performance of these force fields is attributed to their propensity to overstabilize helical peptide backbone conformations at the Pro-2 and Gly-3 residues. On the basis of the similarity of the MD and PDB Ramachandran plots, the following sequence of transitions is suggested for the Gly backbone conformation: α(L) ⇆ β(PR) ⇆ β(S) ⇆ β(P) ⇆ α, where backbone secondary structures α(L) and α are associated with helices and turns, β(P) and β(PR) correspond to the left- and right-handed polyproline II structures and β(S) denotes the fully stretched backbone conformation. Compared to the force field dependence, less significant, but noteworthy, variations in the populations of the peptide backbone conformations were observed. For different solvent models considered, a correlation was noted between the number of torsional transitions in GPGG and the water self-diffusion coefficient on using TIP3P, TIP4P, and TIP5P models. In addition to MD results, we also report DFT derived Karplus relationships for Gly and Pro residues using B972 and B3LYP functionals.
Aliev
Abil E
AE
Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK. a.e.aliev@ucl.ac.uk
Courtier-Murias
Denis
D
D009682:Magnetic Resonance Spectroscopy / Q000592:standards; D056004:Molecular Dynamics Simulation; D009842:Oligopeptides / Q000737:chemistry*; D011392:Proline / Q000031:analogs & derivatives* / Q000737:chemistry; D011487:Protein Conformation; D011789:Quantum Theory; D012015:Reference Standards; D014867:Water / Q000737:chemistry
D009842:Oligopeptides; D014867:Water; C113165:glycyl-prolyl-glycyl-glycine; D011392:Proline