Amino acid side-chain populations in aqueous and saline solution: bis-penicillamine enkephalin

Recent applications of Kirkwood-Buff theory to biological systems

The effect of cosolvents on biomolecular equilibria has traditionally been rationalized using simple binding models. More recently, a renewed interest in the use of Kirkwood-Buff (KB) theory to analyze solution mixtures has provided new information on the effects of osmolytes and denaturants and their interactions with biomolecules. Here we review the status of KB theory as applied to biological systems. In particular, the existing models of denaturation are analyzed in terms of KB theory, and the use of KB theory to interpret computer simulation data for these systems is discussed.

Hydration effects on the electrostatic potential around tuftsin

The electrostatic potential and component dielectric constants from molecular dynamics (MD) trajectories of tuftsin, a tetrapeptide with the amino acid sequence Thr-Lys-Pro-Arg in water and in saline solution are presented. The results obtained from the analysis of the MD trajectories for the total electrostatic potential at points on a grid using the Ewald technique are compared with the solution to the Poisson-Boltzmann (PB) equation. The latter was solved using several sets of dielectric constant parameters. The effects of structural averaging on the PB results were also considered. Solute conformational mobility in simulations gives rise to an electrostatic potential map around the solute dominated by the solute monopole (or lowest order multipole). The detailed spatial variation of the electrostatic potential on the molecular surface brought about by the compounded effects of the distribution of water and ions close to the peptide, solvent mobility, and solute conformational mobility are not qualitatively reproducible from a reparametrization of the input solute and solvent dielectric constants to the PB equation for a single structure or for structurally averaged PB calculations. Nevertheless, by fitting the PB to the MD electrostatic potential surfaces with the dielectric constants as fitting parameters, we found that the values that give the best fit are the values calculated from the MD trajectories. Implications of using such field calculations on the design of tuftsin peptide analogues are discussed.

Comparison of cyclic delta-opioid peptides with non-peptide delta-agonist spiroindanyloxymorphone (SIOM) using the message-address concept: a molecular modeling study

Based upon the message-address concept, this molecular modeling study used the delta-selective agonist spiroindanyloxymorphone (SIOM) as a molecular template for a conformational search and analysis of delta-selective opioid peptides. It was assumed that the tyramine moiety plays the same role for delta-opioid receptor recognition in both peptide and non-peptide ligands. Using 20 reported low-energy conformations of Tyr-cyclo[D-Cys-D-Pen]-OH (JOM-13) for comparison, the geometrical relationship of the two aromatic rings present in SIOM was used for the identification of potential active conformations of JOM-13, from which two delta-receptor-binding models (I and II) were constructed. Models I and II differ from each other in the arrangement of the peptide backbones. To evaluate the two models, a conformational search of two other known delta-selective ligands, [D-Pen2,D-Pen5]enkephalin (DPDPE) and [D-Pen2,L-Pen5]enkephalin (DPLPE) was performed, using the geometrical relationship of the two aromatic rings defined in the two receptor-binding models as a molecular template. Among the conformations generated from the molecular simulation, low-energy conformers of DPDPE and DPLPE conforming to models I and II were identified. Unlike model I, conformers of DPDPE and DPLPE that fit model II contain a cis amide bond in the Gly3 residue.

Prediction of polyelectrolyte polypeptide structures using Monte Carlo conformational search methods with implicit solvation modeling

Many interesting proteins possess defined sequence stretches containing negatively charged amino acids. At present, experimental methods (X-ray crystallography, NMR) have failed to provide structural data for many of these sequence domains. We have applied the dihedral probability grid-Monte Carlo (DPG-MC) conformational search algorithm to a series of N- and C-capped polyelectrolyte peptides, (Glu)20, (Asp)20, (PSer)20, and (PSer-Asp)10, that represent polyanionic regions in a number of important proteins, such as parathymosin, calsequestrin, the sodium channel protein, and the acidic biomineralization proteins. The atomic charges were estimated from charge equilibration and the valence and van der Waals parameters are from DREIDING. Solvation of the carboxylate and phosphate groups was treated using sodium counterions for each charged side chain (one Na+ for COO-; two Na for CO(PO3)-2) plus a distance-dependent (shielded) dielectric constant, epsilon = epsilon 0 R, to simulate solvent water. The structures of these polyelectrolyte polypeptides were obtained by the DPG-MC conformational search with epsilon 0 = 10, followed by calculation of solvation energies for the lowest energy conformers using the protein dipole-Langevin dipole method of Warshel. These calculations predict a correlation between amino acid sequence and global folded conformational minima: 1. Poly-L-Glu20, our structural benchmark, exhibited a preference for right-handed alpha-helix (47% helicity), which approximates experimental observations of 55-60% helicity in solution. 2. For Asp- and PSer-containing sequences, all conformers exhibited a low preference for right-handed alpha-helix formation (< or = 10%), but a significant percentage (approximately 20% or greater) of beta-strand and beta-turn dihedrals were found in all three sequence cases: (1) Aspn forms supercoil conformers, with a 2:1:1 ratio of beta-turn:beta-strand:alpha-helix dihedral angles; (2) PSer20 features a nearly 1:1 ratio of beta-turn:beta-sheet dihedral preferences, with very little preference for alpha-helical structure, and possesses short regions of strand and turn combinations that give rise to a collapsed bend or hairpin structure; (3) (PSer-Asp)10 features a 3:2:1 ratio of beta-sheet:beta-turn:alpha-helix and gives rise to a superturn or C-shaped structure.

De novo prediction of polypeptide conformations using dihedral probability grid Monte Carlo methodology

We tested the dihedral probability grid Monte Carlo (DPG-MC) methodology to determine optimal conformations of polypeptides by applying it to predict the low energy ensemble for two peptides whose solution NMR structures are known: integrin receptor peptide (YGRGDSP, Type II beta-turn) and S3 alpha-helical peptide (YMSEDEL KAAEAAFKRHGPT). DPG-MC involves importance sampling, local random stepping in the vicinity of a current local minima, and Metropolis sampling criteria for acceptance or rejection of new structures. Internal coordinate values are based on side-chain-specific dihedral angle probability distributions (from analysis of high-resolution protein crystal structures). Important features of DPG-MC are: (1) Each DPG-MC step selects the torsion angles (phi, psi, chi) from a discrete grid that are then applied directly to the structure. The torsion angle increments can be taken as S = 60, 30, 15, 10, or 5 degrees, depending on the application. (2) DPG-MC utilizes a temperature-dependent probability function (P) in conjunction with Metropolis sampling to accept or reject new structures. For each peptide, we found close agreement with the known structure for the low energy conformational ensemble located with DPG-MC. This suggests that DPG-MC will be useful for predicting conformations of other polypeptides.