Comprehensive strategy for proton chemical shift prediction: linear prediction with nonlinear corrections.

A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the descriptors are computed from an ensemble of the conformers found by conformational search based on Metropolis Monte Carlo (MMC) simulation; in the 4D model the conformational space was further expanded to the fourth dimension (time) by adding molecular dynamics to the MC conformers. An illustrative case study about the application and interpretation of the 4D prediction for a conformationally flexible structure, scopolamine, is described in detail.

(1) H NMR spectral analysis and conformational behavior of n-alkanes in different chemical environments.

Alkyl chains are common structural units, for example in lipids, and their (1) H NMR spectral parameters offer valuable information about their conformational behavior in solvent environment. Even the spectra of short n-alkanes are complex, which is obviously a reason why their accurate spectral analyses have not been reported before. The present study reports the quantum mechanical analysis of (1) H NMR spectra of n-butane, n-pentane, n-hexane, and n-heptane. The spectral parameters were used to characterize the conformational behavior of n-alkanes. The temperature dependence analysis of coupling constants suggests that the enthalpy difference between the gauche (g) and trans (t) conformations (ΔH(g) ) of n-butane in chloroform is 2.55-2.85 kJ mol(-1) . The difference between the trans-gauche (tg) and all-trans (tt) conformers of n-pentane (ΔH(tg) ) seems to be 0.1-0.2 kJ mol(-1) higher. The coupling constant information shows that the t(n) conformations become more favored with longer chains, although not only for energetic reasons but also partly because the g(+) g(-) arrangements become sterically unfavorable, which decreases the number of favorable g(n) -type conformations. The analysis of the (1) H NMR spectra of n-pentane and n-hexane in solvents representing different chemical environments indicates that polar and spherical dimethyl sulfoxide favors clearly the g conformations, whereas n-hexane-d(14) favors slightly the extended t(n) conformation. In addition to the intrinsic scientific importance for NMR spectral parameter prediction and molecular modeling in solution, the results provide some insights to behavior of hydrocarbon chains and their spectra in different chemical environments.

Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction.

While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein (1)H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6-17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for (1)Hα, (1)HN, (13)Cα, (13)Cß, (13)CO and backbone (15)N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspot.

4D prediction of protein (1)H chemical shifts.

A 4D approach for protein (1)H chemical shift prediction was explored. The 4th dimension is the molecular flexibility, mapped using molecular dynamics simulations. The chemical shifts were predicted with a principal component model based on atom coordinates from a database of 40 protein structures. When compared to the corresponding non-dynamic (3D) model, the 4th dimension improved prediction by 6-7%. The prediction method achieved RMS errors of 0.29 and 0.50 ppm for Halpha and HN shifts, respectively. However, for individual proteins the RMS errors were 0.17-0.34 and 0.34-0.65 ppm for the Halpha and HN shifts, respectively. X-ray structures gave better predictions than the corresponding NMR structures, indicating that chemical shifts contain invaluable information about local structures. The (1)H chemical shift prediction tool 4DSPOT is available from http://www.uku.fi/kemia/4dspot .

Stability and amino acid preferences of type VIII reverse turn: the most common turn in peptides?

Free energies of the alpha(r)beta and betabeta conformations of 14 tetrapeptides, based on the sequence SALN and protein X-ray structures, were calculated using molecular dynamics simulations and MM-PBSA calculations. The alphaalpha conformations of five of the tetrapeptides were also studied. SALN has been earlier shown by molecular dynamics simulations and NMR spectroscopy to have a tendency to form an alpha(r)beta turn. The gas-phase energy of the molecular mechanical force field (CHARMM), the electrostatic and non-polar solvation free energies and solute entropies were used to explain the free energy differences of the alphaalpha, betabeta and alpha(r)beta conformations of the peptides. The alpha(r)beta conformation of SALN and SATN was predicted to be slightly more stable than the extended conformation (betabeta), in agreement with experimental results. The SALN mutants SAIN, SAVN, SATN, SSIN and MSHV, were also predicted to be potential alpha(r)beta turn-forming peptides. We report also revised positional potentials for the type VIII turn, based on a non-homologous set of protein structures. This protein databank analysis confirms the main results of the earlier analyses and reveals several new amino acid residues with a significant positional preference. The results of this work led us to suggest that the alpha(r)beta turn may be the most common turn type in peptides. Such turns may be readily formed in aqueous solution and thereby play important roles in the protein folding process by serving as an initiation point for structure formation.