Determination of sequence-specific intrinsic size parameters from cross sections for 162 tripeptides

Evaluation of a Reference-Free Collision Cross Section Calibration Strategy for Proteomics Using SLIM-Based High-Resolution Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry (IMS) is a gas-phase analytical technique that separates ions with different sizes and shapes and is compatible with mass spectrometry (MS) to provide an additional separation dimension. The rapid nature of the IMS separation combined with the high sensitivity of MS-based detection and the ability to derive structural information on analytes in the form of the property collision cross section (CCS) makes IMS particularly well-suited for characterizing complex samples in -omics applications. In such applications, the quality of CCS from IMS measurements is critical to confident annotation of the detected components in the complex -omics samples. However, most IMS instrumentation in mainstream use requires calibration to calculate CCS from measured arrival times, with the most notable exception being drift tube IMS measurements using multifield methods. The strategy for calibrating CCS values, particularly selection of appropriate calibrants, has important implications for CCS accuracy, reproducibility, and transferability between laboratories. The conventional approach to CCS calibration involves explicitly defining calibrants ahead of data acquisition and crucially relies upon availability of reference CCS values. In this work, we present a novel reference-free approach to CCS calibration which leverages trends among putatively identified features and computational CCS prediction to conduct calibrations post-data acquisition and without relying on explicitly defined calibrants. We demonstrated the utility of this reference-free CCS calibration strategy for proteomics application using high-resolution structures for lossless ion manipulations (SLIM)-based IMS-MS. We first validated the accuracy of CCS values using a set of synthetic peptides and then demonstrated using a complex peptide sample from cell lysate.

The membrane activity of the antimicrobial peptide caerin 1.1 is pH dependent

Antimicrobial peptides are an important class of membrane-active peptides that can provide alternatives or complements to classic antibiotics. Among the many classes of AMPs, the histidine-rich family is of particular interest since they may induce pH-sensitive interactions with cell membranes. The AMP caerin 1.1 (Cae-1), from Australian tree frogs, has three histidine residues, and thus we studied the pH dependence of its interactions with model cell membranes. Using NMR spectroscopy and molecular dynamics simulations, we showed that Cae-1 induced greater perturbation of the lipid dynamics and water penetrations within the membrane interior in an acidic environment compared with physiological conditions. Using 31P solid-state NMR, the packing, chemical environment, and dynamics of the lipid headgroup were monitored. 2H solid-state NMR showed that Cae-1 ordered the acyl chains of the hydrophobic core of the bilayer. These results supported the molecular dynamics data, which showed that Cae-1 was mainly inserted within the lipid bilayer for both neutral and negatively charged membranes, with the charged residues pulling the water and phosphate groups inward. This could be an early step in the mechanism of membrane disruption by histidine-rich antimicrobial peptides and indicated that Cae-1 acts via a transmembrane mechanism in bilayers of neutral and anionic phospholipid membranes, especially in acidic conditions.

QSSR Modeling of Bacillus Subtilis Lipase A Peptide Collision Cross-Sections in Ion Mobility Spectrometry: Local Descriptor Versus Global Descriptor

To investigate the structure-dependent peptide mobility behavior in ion mobility spectrometry (IMS), quantitative structure-spectrum relationship (QSSR) is systematically modeled and predicted for the collision cross section Ω values of totally 162 single-protonated tripeptide fragments extracted from the Bacillus subtilis lipase A. Two different types of structure characterization methods, namely, local and global descriptor as well as three machine learning methods, namely, partial least squares (PLS), support vector machine (SVM) and Gaussian process (GP), are employed to parameterize and correlate the structures and Ω values of these peptide samples. In this procedure, the local descriptor is derived from the principal component analysis (PCA) of 516 physicochemical properties for 20 standard amino acids, which can be used to sequentially characterize the three amino acid residues composing a tripeptide. The global descriptor is calculated using CODESSA method, which can generate > 200 statistically significant variables to characterize the whole molecular structure of a tripeptide. The obtained QSSR models are evaluated rigorously via tenfold cross-validation and Monte Carlo cross-validation (MCCV). A comprehensive comparison is performed on the resulting statistics arising from the systematic combination of different descriptor types and machine learning methods. It is revealed that the local descriptor-based QSSR models have a better fitting ability and predictive power, but worse interpretability, than those based on the global descriptor. In addition, since the QSSR modeling using local descriptor does not consider the three-dimensional conformation of tripeptide samples, the method would be largely efficient as compared to the global descriptor.

A Priori Intrinsic PTM Size Parameters for Predicting the Ion Mobilities of Modified Peptides

The rising profile of ion mobility spectrometry (IMS) in proteomics has driven the efforts to predict peptide cross-sections. In the simplest approach, these are derived by adding the contributions of all amino acid residues and post-translational modifications (PTMs) defined by their intrinsic size parameters (ISPs). We show that the ISPs for PTMs can be calculated from properties of constituent atoms, and introduce the "impact scores" that govern the shift of cross-sections from the central mass-dependent trend for unmodified peptides. The ISPs and scores tabulated for 100 more common PTMs enable predicting the domains for modified peptides in the IMS/MS space that would guide subproteome investigations. Graphical Abstract ᅟ.

Examining the Influence of Phosphorylation on Peptide Ion Structure by Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS) techniques are used to study the general effects of phosphorylation on peptide structure. Cross sections for a library of 66 singly phosphorylated peptide ions from 33 pairs of positional isomers, and unmodified analogues were measured. Intrinsic size parameters (ISPs) derived from these measurements yield calculated collision cross sections for 85% of these phosphopeptide sequences that are within ±2.5% of experimental values. The average ISP for the phosphoryl group (0.64 ± 0.05) suggests that in general this moiety forms intramolecular interactions with the neighboring residues and peptide backbone, resulting in relatively compact structures. We assess the capability of ion mobility to separate positional isomers (i.e., peptide sequences that differ only in the location of the modification) and find that more than half of the isomeric pairs have >1% difference in collision cross section. Phosphorylation is also found to influence populations of structures that differ in the cis/trans orientation of Xaa-Pro peptide bonds. Several sequences with phosphorylated Ser or Thr residues located N-terminally adjacent to Pro residues show fewer conformations compared to the unmodified sequences.

Correcting the fundamental ion mobility equation for field effects

Cross sections measured by ion mobility spectrometry are corrected for collision frequency and cooling/heating-controlled momentum transfer.

Intrinsic Size Parameters for Palmitoylated and Carboxyamidomethylated Peptides

Cross sections for 61 palmitoylated peptides and 73 cysteine-unmodified peptides are determined and used together with a previously obtained tryptic peptide library to derive a set of intrinsic size parameters (ISPs) for the palmitoyl (Pal) group (1.26 ± 0.04), carboxyamidomethyl (Am) group (0.92 ± 0.04), and the 20 amino acid residues to assess the influence of Pal- and Am-modification on cysteine and other amino acid residues. These values highlight the influence of the intrinsic hydrophobic and hydrophilic nature of these modifications on the overall cross sections. As a part of this analysis, we find that ISPs derived from a database of a modifier on one amino acid residue (Cys^Pal) can be applied on the same modification group on different amino acid residues (Ser^Pal and Tyr^Pal). Using these ISP values, we are able to calculate peptide cross sections to within ± 2% of experimental values for 83% of Pal-modified peptide ions and 63% of Am-modified peptide ions. We propose that modification groups should be treated as individual contribution factors, instead of treating the combination of the particular group and the amino acid residue they are on as a whole when considering their effects on the peptide ion mobility features.

IMSPeptider: A computational peptide collision cross-section area calculator based on a novel molecular dynamics simulation protocol

Introduction of ion mobility mass spectrometry (IMS/MS) into the proteomic workflow provides an orthogonal separation to the widely used LC-MS platforms. IMS also provides structural information that could facilitate peptide identification. However, the lack of tools capable of predictive power in a high-throughput fashion makes peptide global profiling quite challenging. To target this issue, a computational workflow was developed based on biophysical principles to predict the collision cross-section area (CCS) of peptides as measured from IMS/MS experiments. Hosted on a web server, it allows the user to input a primary sequence (query) and retrieve information on peptide structure, sequence, and corresponding CCS. The current version is designed to identify peptide sequences up to 23 residues in length, in its higher charge state, based on a match of the molecule m/z and CCS. The protocol was validated against a 128-sequences-dataset and CCS predicted within 2.8% average error.

Factors that influence helical preferences for singly charged gas-phase peptide ions: the effects of multiple potential charge-carrying sites

Ion mobility-mass spectrometry is used to investigate the structure(s) of a series of model peptide [M + H](+) ions to better understand how intrinsic properties affect structure in low dielectric environments. The influence of peptide length, amino acid sequence, and composition on gas-phase structure is examined for a series of model peptides that have been previously studied in solution. Collision cross sections for the [M + H](+) ions of Ac-(AAKAA)(n)Y-NH(2) (n = 3-6) and Ac-Y(AEAAKA)(n)F-NH(2) (n = 2-5) are reported and correlated with candidate structures generated using molecular modeling techniques. The [M + H](+) ions of the AAKAA peptide series each exhibit a single, dominant ion mobility arrival time distribution (ATD) which correlates to partial helical structures, whereas the [M + H](+) ions of the AEAAKA ion series are composed of ATDs which correlate to charge-solvated globules (i.e., the charge is coordinated or solvated by polar peptide functional groups). These data raise numerous questions concerning intrinsic properties (amino acid sequence and composition as well as charge location) that dictate gas-phase peptide ion structure, which may reflect trends for peptide ion structure in low dielectric environments, such as transmembrane segments.

Conformational and noncovalent complexation changes in proteins during electrospray ionization

Electrospray ion sources efficiently produce gas-phase ions from proteins and their noncovalent complexes. Charge-state distributions of these ions are increasingly used to gauge their conformations in the solution phase. Here we investigate how this correlation is affected by the spraying conditions at the early stage of droplet generation, prior to the ionization process. We followed the folding behavior of model proteins cytochrome c and ubiquitin and the dissociation of the noncovalent holomyoglobin complex. Spray current measurements, fast Taylor cone imaging, and mass analysis of the generated ions indicated that the protein structure experienced conformational or complexation changes upon variations in the spraying mode of the electrospray ionization source. These effects resulted in a departure from the original secondary, tertiary, and quaternary structure of proteins, possibly introducing artifacts in related studies. Therefore, if a particular gas-phase ion conformation is required or correlations with the liquid-phase conformations are studied, it is advantageous to maintain a particular spraying mode. Alternatively, spraying mode-induced changes can be utilized to alter the structure of proteins in, for example, time-resolved experiments for the study of protein folding dynamics.

Quantitative structure–property relationship studies for collision cross sections of 579 singly protonated peptides based on a novel descriptor as molecular graph fingerprint (MoGF)

Aiming at ion mobility spectrometry (IMS), computer-assisted ion mobility prediction (CAIMP) has been recently developed to simulate and predict diverse IMS behaviors in assistance of mathematics and computer science. Of that, quantitative structure-property relationship (QSPR) plays a vital role, dedicating to predict properties of unknown samples by creating statistical model based on known samples. In QSPR, the key lies in how to transform structural characteristics of target compounds into a group of numerical codes. In consideration that future IMS applications may mainly focus on intricate drug/biological systems, a novel molecular structural characterization method referring to molecular graphic fingerprint (MoGF) is proposed in this paper. In MoGF approach, radical distribution function is employed to map intrinsic interatomic correlations into a coordinate system according to a reasonable sampling interval, thus forming the characteristic graph curve which is rich in information on molecular structural characteristics, possessing of great merits in easy calculation, independent of experiments, large information contents, explicit structural meanings and intuitive expressions, etc. Consequently, MoGF is utilized to QSPR studies on 579 singly protonated peptide collision cross sections, and the constructed partial least square (PLS) regression model is confirmed to be robust and predictable by rigorous both internal and external validations, with statistics as r2 = 0.991, q2 = 0.990, RMSEE = 5.526, RMSCV = 5.572, q2(ext) = 0.990, r2(ext) = 0.990, r2(0,ext) = 0.990, r'2(0,ext) = 0.990, k = 1.003, k' = 0.996 and RMSEP = 5.561, respectively.

Collision-induced alignment of H2O+ drifting in helium

The collision-induced alignment of H(2)O(+) drifting in helium is studied with a molecular dynamics method that has been extended to treat nonlinear rigid ions. Rotational distribution functions and averaged quantities are presented in terms of the rho formalism [M. Thachuk, Phys. Rev. A 72, 032722 (2005)], and it is shown that this description gives a very good agreement with simulation results. In addition to velocity and angular velocity autocorrelation functions, a velocity-angular velocity cross correlation function is introduced. This cross correlation function provides insight into the dynamical nature of the alignment mechanism.