Role of helix formation for the retention of peptides in reversed-phase high-performance liquid chromatography

Gain of local structure in an amphipathic peptide does not require a specific tertiary framework

In this work, we studied how an amphipathic peptide of the surface of the globular protein thioredoxin, TRX94-108, acquires a native-like structure when it becomes involved in an apolar interaction network. We designed peptide variants where the tendency to form alpha-helical conformation is modulated by replacing each of the leucine amino acid residues by an alanine. The induction of structure caused by sodium dodecyl sulfate (SDS) binding was studied by capillary zone electrophoresis, circular dichroism, DOSY-NMR, and molecular dynamics simulations (MDS). In addition, we analyzed the strength of the interaction between a C18 RP-HPLC matrix and the peptides. The results presented here reveal that (a) critical elements in the sequence of the wild-type peptide stabilize a SDS/peptide supramolecular cluster; (b) the hydrophobic nature of the interaction between SDS molecules and the peptide constrains the ensemble of conformations; (c) nonspecific apolar surfaces are sufficient to stabilize peptide secondary structure. Remarkably, MDS shed light on a contact network formed by a limited number of SDS molecules that serves as a structural scaffold preserving the helical conformation of this module. This mechanism might prevail when a peptide with low helical propensity is involved in structure consolidation. We suggest that folding of peptides sharing this feature does not require a preformed tightly-packed protein core. Thus, the formation of specific tertiary interactions would be the consequence of peptide folding and not its cause. In this scenario, folding might be thought of as a process that includes unspecific rounds of structure stabilization guiding the protein to the native state.

Informatics for peptide retention properties in proteomic LC-MS

Retention times in HPLC yield valuable information for the identification of various analytes and the prediction of peptide retention is useful for the identification of peptides/proteins in LC-MS-based proteomics. Informatics methods such as artificial neural networks and support vector machines capable of solving nonlinear problems made possible the accurate modeling of quantitative structure-retention relationships of peptides (including large polymers) up to 5 kDa to which classical linear models cannot be applied, as well as the proteome-wide prediction of peptide retention. Proteome-wide retention prediction and accurate mass-information facilitate the identification of peptides in complex proteomic samples. In this review, we address recent developments in solid informatics methods and their application to peptide-retention properties in 'bottom-up' shotgun proteomics. We also describe future prospects for the standardization and application of retention times.

Improved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information

We describe an improved artificial neural network (ANN)-based method for predicting peptide retention times in reversed-phase liquid chromatography. In addition to the peptide amino acid composition, this study investigated several other peptide descriptors to improve the predictive capability, such as peptide length, sequence, hydrophobicity and hydrophobic moment, and nearest-neighbor amino acid, as well as peptide predicted structural configurations (i.e., helix, sheet, coil). An ANN architecture that consisted of 1052 input nodes, 24 hidden nodes, and 1 output node was used to fully consider the amino acid residue sequence in each peptide. The network was trained using approximately 345,000 nonredundant peptides identified from a total of 12,059 LC-MS/MS analyses of more than 20 different organisms, and the predictive capability of the model was tested using 1303 confidently identified peptides that were not included in the training set. The model demonstrated an average elution time precision of approximately 1.5% and was able to distinguish among isomeric peptides based upon the inclusion of peptide sequence information. The prediction power represents a significant improvement over our earlier report (Petritis, K.; Kangas, L. J.; Ferguson, P. L.; Anderson, G. A.; Pasa-Tolic, L.; Lipton, M. S.; Auberry, K. J.; Strittmatter, E. F.; Shen, Y.; Zhao, R.; Smith, R. D. Anal. Chem. 2003, 75, 1039-1048) and other previously reported models.

Studies on the Insolubility of a Transmembrane Peptide from Signal Peptide Peptidase

We have undertaken fundamental studies on the solubility properties of a peptide derived from the fourth transmembrane (TM) domain of signal peptide peptidase, a 7-TM intramembrane-cleaving protease. We have found that by disfavoring secondary structure formation we are able to greatly improve the solubility, handling, and purification properties of this peptide. Our findings suggest that preventing secondary structure formation by reversible modification of the polypeptide backbone of hydrophobic transmembrane peptides may be a useful strategy for the total chemical protein synthesis of integral membrane proteins.

Interactions between charged polypeptides and nonionic surfactants

The influence of molecular characteristics on the mutual interaction between peptides and nonionic surfactants has been investigated by studying the effects of surfactants on amphiphilic, random copolymers of alpha-L-amino acids containing lysine residues as the hydrophilic parts. The hydrophobic residues were either phenylalanine or tyrosine. The peptide-surfactant interactions were studied by means of circular dichroism spectroscopy and binding isotherms, as well as by 1D and 2D NMR. The binding of surfactant to the peptides was found to be a cooperative process, appearing at surfactant concentrations just below the critical micellar concentration. However, a certain degree of peptide hydrophobicity is necessary to obtain an interaction with nonionic surfactant. When this prerequisite is fulfilled, the peptide mainly interacts with self-assembled, micelle-like surfactant aggregates formed onto the peptide chain. Therefore, the peptide-surfactant complex is best described in terms of a necklace model, with the peptide interacting primarily with the palisade region of the micelles via its hydrophobic side chains. The interaction yields an increased amount of alpha-helix conformation in the peptide. Surfactants that combine small headgroups with a propensity to form small, nearly spherical micelles were shown to give the largest increase in alpha-helix content.

Studies on the cellular uptake of substance P and lysine-rich, KLA-derived model peptides

In the last decade many peptides have been shown to be internalized into various cell types by different, poorly characterized mechanisms. This review focuses on uptake studies with substance P (SP) aimed at unravelling the mechanism of peptide-induced mast cell degranulation, and on the characterization of the cellular uptake of designed KLA-derived model peptides. Studies on structure-activity relationships and receptor autoradiography failed to detect specific peptide receptors for the undecapeptide SP on mast cells. In view of these findings, a direct interaction of cationic peptides with heterotrimeric G proteins without the participation of a receptor has been proposed. Such a process would require insertion into and translocation of peptides across the plasma membrane. In order to clarify whether a transport of cationic peptides into rat peritoneal mast cells is possible, transport studies were performed by confocal laser scanning microscopy (CLSM) using fluorescence-labeled Arg(3),Orn(7)-SP and its D-amino acid analog, all-D-Arg(3),Orn(7)-SP, as well as by electron microscopic autoradiography using (3)H-labelled SP and (125)I-labelled all-D-SP. The results obtained by CLSM directly showed translocation of SP peptides into pertussis toxin-treated cells. Kinetic experiments indicated that the translocation process was rapid, occurring within a few seconds. Mast cell degranulation induced by analog of magainin 2 amide, neuropeptide Y and the model peptide acetyl-KLALKLALKALKAALKLA-amide was also found to be very fast, pointing to an extensive translocation of the peptides. In order to learn more about structural requirements for the cellular uptake of peptides, the translocation behavior of a set of systematically modified KLA-based model peptides has been studied in detail. By two different protocols for determining the amount of internalized peptide, evidence was found that the structure of the peptides only marginally affects their uptake, whereas the efflux of cationic, amphipathic peptides is strikingly diminished, thus allowing their enrichment within the cells. Although the mechanism of cellular uptake, consisting of energy-dependent and -independent contributions, is not well understood, KLA-derived peptides have been shown to deliver various cargos (PNAs, peptides) into cells. The results obtained with SP- and KLA-derived peptides are discussed in the context of the current literature.

Temperature profiling of polypeptides in reversed-phase liquid chromatography. II. Monitoring of folding and stability of two-stranded alpha-helical coiled-coils

The present study extends the utility of reversed-phase high-performance liquid chromatography (RP-HPLC) to monitor folding and stability of de novo designed synthetic two-stranded alpha-helical coiled-coils. Thus, we have compared the effect of temperature on the RP-HPLC retention behaviour of both oxidized (two identical five-heptad alpha-helical peptides linked by a disulfide bridge) and reduced coiled-coil analogues with various amino acids substituted into the hydrophobic core of the coiled-coil. We were able to correlate the RP-HPLC retention behaviour of the oxidized analogues over the temperature range of 10 to 80 degrees C with the stability of the analogues as determined by conventional thermal and chemical denaturation approaches. In addition, the contribution of a disulfide bridge to coiled-coil stability was highlighted by comparing the elution behaviour of the oxidized and reduced analogues. Overall, we demonstrate the excellent potential of "temperature profiling" by RP-HPLC to monitor differences in oligomerization state and protein stability.

Use of artificial neural networks for the accurate prediction of peptide liquid chromatography elution times in proteome analyses

The use of artificial neural networks (ANNs) is described for predicting the reversed-phase liquid chromatography retention times of peptides enzymatically digested from proteome-wide proteins. To enable the accurate comparison of the numerous LC/MS data sets, a genetic algorithm was developed to normalize the peptide retention data into a range (from 0 to 1), improving the peptide elution time reproducibility to approximately 1%. The network developed in this study was based on amino acid residue composition and consists of 20 input nodes, 2 hidden nodes, and 1 output node. A data set of approximately 7000 confidently identified peptides from the microorganism Deinococcus radiodurans was used for the training of the ANN. The ANN was then used to predict the elution times for another set of 5200 peptides tentatively identified by MS/MS from a different microorganism (Shewanella oneidensis). The model was found to predict the elution times of peptides with up to 54 amino acid residues (the longest peptide identified after tryptic digestion of S. oneidensis) with an average accuracy of approximately 3%. This predictive capability was then used to distinguish with high confidence isobar peptides otherwise indistinguishable by accurate mass measurements as well as to uncover peptide misidentifications. Thus, integration of ANN peptide elution time prediction in the proteomic research will increase both the number of protein identifications and their confidence.