Protein Conformation and Supercharging with DMSO from Aqueous Solution

The efficacy of dimethyl sulfoxide (DMSO) as a supercharging reagent for protein ions formed by electrospray ionization from aqueous solution and the mechanism for supercharging were investigated. Addition of small amounts of DMSO to aqueous solutions containing hen egg white lysozyme or equine myoglobin results in a lowering of charge, whereas a significant increase in charge occurs at higher concentrations. Results from both near-UV circular dichroism spectroscopy and solution-phase hydrogen/deuterium exchange mass spectrometry indicate that DMSO causes a compaction of the native structure of these proteins at low concentration, but significant unfolding occurs at ~63% and ~43% DMSO for lysozyme and myoglobin, respectively. The DMSO concentrations required to denature these two proteins in bulk solution are ~3–5 times higher than the concentrations required for the onset of supercharging, consistent with a significantly increased concentration of this high boiling point supercharging reagent in the ESI droplet as preferential evaporation of water occurs. DMSO is slightly more basic than m-nitrobenzyl alcohol and sulfolane, two other supercharging reagents, based on calculated proton affinity and gas-phase basicity values both at the B3LYP and MP2 levels of theory, and all three of these supercharging reagents are significantly more basic than water. These results provide additional evidence that the origin of supercharging from aqueous solution is the result of chemical and/or thermal denaturation that occurs in the ESI droplet as the concentration of these supercharging reagents increases, and that proton transfer reactivity does not play a significant role in the charge enhancement observed

Simultaneous Quantitation of Amino Acid Mixtures using Clustering Agents

A method that uses the abundances of large clusters formed in electrospray ionization to determine the solution-phase molar fractions of amino acids in multi-component mixtures is demonstrated. For solutions containing either four or 10 amino acids, the relative abundances of protonated molecules differed from their solution-phase molar fractions by up to 30-fold and 100-fold, respectively. For the four-component mixtures, the molar fractions determined from the abundances of larger clusters consisting of 19 or more molecules were within 25% of the solution-phase molar fractions, indicating that the abundances and compositions of these clusters reflect the relative concentrations of these amino acids in solution, and that ionization and detection biases are significantly reduced. Lower accuracy was obtained for the 10-component mixtures where values determined from the cluster abundances were typically within a factor of three of their solution molar fractions. The lower accuracy of this method with the more complex mixtures may be due to specific clustering effects owing to the heterogeneity as a result of significantly different physical properties of the components, or it may be the result of lower S/N for the more heterogeneous clusters and not including the low-abundance more highly heterogeneous clusters in this analysis. Although not as accurate as using traditional standards, this clustering method may find applications when suitable standards are not readily available

On the Zwitterionic Nature of Gas-Phase Peptides and Protein Ions

Determining the total number of charged residues corresponding to a given value of net charge for peptides and proteins in gas phase is crucial for the interpretation of mass-spectrometry data, yet it is far from being understood. Here we show that a novel computational protocol based on force field and massive density functional calculations is able to reproduce the experimental facets of well investigated systems, such as angiotensin II, bradykinin, and tryptophan-cage. The protocol takes into account all of the possible protomers compatible with a given charge state. Our calculations predict that the low charge states are zwitterions, because the stabilization due to intramolecular hydrogen bonding and salt-bridges can compensate for the thermodynamic penalty deriving from deprotonation of acid residues. In contrast, high charge states may or may not be zwitterions because internal solvation might not compensate for the energy cost of charge separation

LC-MSsim – a simulation software for liquid chromatography mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used to analyze the protein content of biological samples in large scale studies. The data resulting from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new developments in Bioinformatics, especially in the fields of algorithm development, statistics and software engineering. In a quantitative label-free mass spectrometry experiment, crucial steps are the detection of peptide features in the mass spectra and the alignment of samples by correcting for shifts in retention time. At the moment, it is difficult to compare the plethora of algorithms for these tasks. So far, curated benchmark data exists only for peptide identification algorithms but no data that represents a ground truth for the evaluation of feature detection, alignment and filtering algorithms.</p> <p>Results</p> <p>We present <it>LC-MSsim</it>, a simulation software for LC-ESI-MS experiments. It simulates ESI spectra on the MS level. It reads a list of proteins from a FASTA file and digests the protein mixture using a user-defined enzyme. The software creates an LC-MS data set using a predictor for the retention time of the peptides and a model for peak shapes and elution profiles of the mass spectral peaks. Our software also offers the possibility to add contaminants, to change the background noise level and includes a model for the detectability of peptides in mass spectra. After the simulation, <it>LC-MSsim </it>writes the simulated data to mzData, a public XML format. The software also stores the positions (monoisotopic m/z and retention time) and ion counts of the simulated ions in separate files.</p> <p>Conclusion</p> <p><it>LC-MSsim </it>generates simulated LC-MS data sets and incorporates models for peak shapes and contaminations. Algorithm developers can match the results of feature detection and alignment algorithms against the simulated ion lists and meaningful error rates can be computed. We anticipate that <it>LC-MSsim </it>will be useful to the wider community to perform benchmark studies and comparisons between computational tools.</p

Selective Removal of Alkali Metal Cations from Multiply-Charged Ions via Gas-Phase Ion/Ion Reactions Using Weakly Coordinating Anions

Selective removal of alkali metal cations from mixed cation multiply-charged peptide ions is demonstrated here using gas-phase ion/ion reactions with a series of weakly coordinating anions (WCAs), including hexafluorophosphate (PF6 (-)), tetrakis[3,5-bis(trifluoromethyl)phenyl]borate (BARF), tetrakis(pentafluorophenyl)borate (TPPB), and carborane (CHB11Cl11 (-)). In all cases, a long-lived complex is generated by dication/anion condensation followed by ion activation to compare proton transfer with alkali ion transfer from the peptide to the anion. The carborane anion was the only anion studied to undergo dissociation exclusively through loss of the metallated anion, regardless of the studied metal adduct. All other anions studied yield varying abundances of protonated and metallated peptide depending on the peptide sequence and the metal identity. Density functional theory calculations suggest that for the WCAs studied, metal ion transfer is most strongly favored thermodynamically, which is consistent with the experimental results. The carborane anion is demonstrated to be a robust reagent for the selective removal of alkali metal cations from peptide cations with mixtures of excess protons and metal cations