Heuristic charge assignment for deconvolution of electrospray ionization mass spectra

We propose a new algorithm for deconvolution of electrospray ionization mass spectra based on direct assignment of charge to the measured signal at each mass-to-charge ratio (m/z). We investigate two heuristics for charge assignment: the entropy-based heuristic is adapted from a deconvolution algorithm by Reinhold and Reinhold;10 the multiplicative-correlation heuristic is adapted from the multiplicative-correlation deconvolution algorithm of Hagen and Monnig.6 The entropy-based heuristic is insensitive to overestimates of z(max), the maximum ion charge. We test the deconvolution algorithm on two single-component samples: the measured spectrum of human beta-endorphin has two prominent and one very weak line whereas myoglobin has a well-developed quasi-gaussian envelope of 17 peaks. In both cases, the deconvolution algorithm gives a clean deconvoluted spectrum with one dominant peak and very few artefacts. The relative heights of the peaks due to the parent molecules in the deconvoluted spectrum of a mixture of two peptides, which are expected to ionize with equal efficiency, give an accurate measure of their relative concentration in the sample.     

Automated deconvolution and deisotoping of electrospray mass spectra

Electrospray ionization (ESI) of peptides and proteins produces a series of multiply charged ions with a mass/charge (m/z) ratio between 500 and 2000. The resulting mass spectra are crowded by these multiple charge values for each molecular mass and an isotopic cluster for each nominal m/z value. Here, we report a new algorithm simultaneously to deconvolute and deisotope ESI mass spectra from complex peptide samples based on their mass-dependent isotopic mean pattern. All signals corresponding to one peptide in the sample were reduced to one singly charged monoisotopic peak, thereby significantly reducing the number of signals, increasing the signal intensity and improving the signal-to-noise ratio. The mass list produced could be used directly for database searching. The developed algorithm also simplified interpretation of fragment ion spectra of multiply charged parent ions.     

Correct charge state assignment of native electrospray spectra of protein complexes

Correct charge state assignment is crucial to assigning an accurate mass to supramolecular complexes analyzed by electrospray mass spectrometry. Conventional charge state assignment techniques fall short of reliably and unambiguously predicting the correct charge state for many supramolecular complexes. We provide an explanation of the shortcomings of the conventional techniques and have developed a robust charge state assignment method that is applicable to all spectra.     

Observation and implications of high mass-to-charge ratio ions from electrospray ionization mass spectrometry

High mass-to-charge ratio ions (> 4000) from electrospray ionization (ESI) have been observed for several proteins, including bovine cytochrome c (M _r 12,231) and porcine pepsin (M _r 34,584), by using a quadrupole mass spectrometer with an m/z 45,000 range. The ESI mass spectrum for cytochrome c in an aqueous solution gives a charge state distribution that ranges from 12 + to 2 +, with a broad, low-intensity peak in the mass-to-charge ratio region corresponding to the [M + H]⁺ ion. the negative ion ESI mass spectrum for pepsin in 1% acetic acid solution shows a charge state distribution ranging from 7? to 2?. To observe the [M - H]^? ion, harsher desolvation and interface conditions were required. Also observed was the abundant aggregation of the protens with average charge states substantially lower than observed for their monomeric counterparts. The negative ion ESI mass spectrum for cytochrome c in 1–100 mM NH₄OAc solutions showed greater relative abundances for the higher mass-to-charge ratio ions than in acuidic solutions, with an [M - H]^? ion relative abundance approximately 50% that of the most abundant charge state peak. The observation that protein aggregates are formed with charge states comparable to monomeric species (at fower mass-to-charge ratios) suggests that the high mass-to-charge ratio monomers may be formed by the dissociation of aggregate species. The observation of low charge state and aggregate molecular ions concurrently with highly charged species may serve to support a variation of the charged residue model, originally described by Dole and co-workers (Dole, M., et al. J. Chem. Phys. 1968, 49, 2240; Mack, L. L., et al. J. Chem. Phys. 1970, 52, 4977) which involves the Coulombically driven formation of either very highly solvated molecular ions or lower ananometer-diameter droplets.     

Effect of protein stabilization on charge state distribution in positive- and negative-ion electrospray ionization mass spectra

Changes in protein conformation are thought to alter charge state distributions observed in electrospray ionization mass spectra (ESI-MS) of proteins. In most cases, this has been demonstrated by unfolding proteins through acidification of the solution. This methodology changes the properties of the solvent so that changes in the ESI-MS charge envelopes from conformational changes are difficult to separate from the effects of changing solvent on the ionization process. A novel strategy is presented enabling comparison of ESI mass spectra of a folded and partially unfolded protein of the same amino acid sequence subjected to the same experimental protocols and conditions. The N-terminal domain of the Escherichia coli DnaB protein was cyclized by in vivo formation of an amide bond between its N- and C-termini. The properties of this stabilized protein were compared with its linear counterpart. When the linear form was unfolded by decreasing pH, a charge envelope at lower m/z appeared consistent with the presence of a population of unfolded protein. This was observed in both positive-ion and negative-ion ESI mass spectra. Under the same conditions, this low m/z envelope was not present in the ESI mass spectrum of the stable cyclized form. The effects of changing the desolvation temperature in the ionization source of the Q-TOF mass spectrometer were also investigated. Increasing the desolvation temperature had little effect on positive-ion ESI mass spectra, but in negative-ion spectra, a charge envelope at lower m/z appeared, consistent with an increase in the abundance of unfolded protein molecules.     

ESIprot: a universal tool for charge state determination and molecular weight calculation of proteins from electrospray ionization mass spectrometry data

Electrospray ionization (ESI) ion trap mass spectrometers with relatively low resolution are frequently used for the analysis of natural products and peptides. Although ESI spectra of multiply charged protein molecules also can be measured on this type of devices, only average spectra are produced for the majority of naturally occurring proteins. Evaluating such ESI protein spectra would provide valuable information about the native state of investigated proteins. However, no suitable and freely available software could be found which allows the charge state determination and molecular weight calculation of single proteins from average ESI‐MS data. Therefore, an algorithm based on standard deviation optimization (scatter minimization) was implemented for the analysis of protein ESI‐MS data. The resulting software ESIprot was tested with ESI‐MS data of six intact reference proteins between 12.4 and 66.7 kDa. In all cases, the correct charge states could be determined. The obtained absolute mass errors were in a range between ?0.2 and 1.2 Da, the relative errors below 30 ppm. The possible mass accuracy allows for valid conclusions about the actual condition of proteins. Moreover, the ESIprot algorithm demonstrates an extraordinary robustness and allows spectral interpretation from as little as two peaks, given sufficient quality of the provided m/z data, without the necessity for peak intensity data. ESIprot is independent from the raw data format and the computer platform, making it a versatile tool for mass spectrometrists. The program code was released under the open‐source GPLv3 license to support future developments of mass spectrometry software. Copyright © 2010 John Wiley & Sons, Ltd.     

A minimalist model for exploring conformational effects on the electrospray charge state distribution of proteins

The electrospray ionization (ESI) charge state distribution of proteins is highly sensitive to the protein structure in solution. Unfolded conformations generally form higher charge states than tightly folded structures. The current study employs a minimalist molecular dynamics model for simulating the final stages of the ESI process in order to gain insights into the physical reasons underlying this empirical relationship. The protein is described as a string of 27 beads ("residues"), 9 of which are negatively charged and represent possible protonation sites. The unfolded state of this bead string is a random coil, whereas the native conformation adopts a compact fold. The ESI process is simulated by placing the protein inside a solvent droplet with a 2.5 nm radius consisting of 1600 Lennard-Jones particles. In addition, the droplet contains 14 protons which are modeled as highly mobile point charges. Disintegration of the droplet rapidly releases the protein into the gas phase, resulting in average charge states of 4.8+ and 7.4+ for the folded and unfolded conformation, respectively. The protonation probabilities of individual residues in the folded state reveal a characteristic pattern, with values ranging from 0.2 to 0.8. In contrast, the protonation probabilities of the unfolded protein are more uniform and cover the range from 0.8 to 1.0. The origin of these differences can be traced back to a combination of steric and electrostatic effects. Residues exhibiting a small accessible surface area are less likely to capture a proton, an effect that is exacerbated by partial electrostatic shielding from nearby positive residues. Conversely, sites that are sterically exposed are associated with electrostatic funnels that greatly increase the likelihood of protonation. Unfolding enhances the steric and electrostatic exposure of protonation sites, thereby causing the protein to capture a greater number of protons during the droplet disintegration process.     

A MAP-based algorithm for spectroscopic semi-blind deconvolution

Spectroscopic data often suffer from common problems of bands overlapping and random noise. In this paper, we show that the issue of overlapping peaks can be considered as a maximum a posterior (MAP) problem and be solved by minimizing an object functional that includes a likelihood term and two prior terms. In the MAP framework, the likelihood probability density function (PDF) is constructed based on a spectral observation model, a robust Huber-Markov model is used as spectra prior PDF, and the kernel prior is described based on a parametric Gaussian function. Moreover, we describe an efficient optimization scheme that alternates between latent spectrum recovery and blur kernel estimation until convergence. The major novelty of the proposed algorithm is that it can estimate the kernel slit width and latent spectrum simultaneously. Comparative results with other deconvolution methods suggest that the proposed method can recover spectral structural details as well as suppress noise effectively.     

Effects of solvent on the maximum charge state and charge state distribution of protein ions produced by electrospray ionization

The effects of solvent composition on both the maximum charge states and charge state distributions of analyte ions formed by electrospray ionization were investigated using a quadrupole mass spectrometer. The charge state distributions of cytochrome c and myoglobin, formed from 47%/50%/3% water/solvent/acetic acid solutions, shift to lower charge (higher m/z) when the 50% solvent fraction is changed from water to methanol, to acetonitrile, to isopropanol. This is also the order of increasing gas-phase basicities of these solvents, although other physical properties of these solvents may also play a role. The effect is relatively small for these solvents, possibly due to their limited concentration inside the electrospray interface. In contrast, the addition of even small amounts of diethylamine (<0.4%) results in dramatic shifts to lower charge, presumably due to preferential proton transfer from the higher charge state ions to diethylamine. These results clearly show that the maximum charge states and charge state distributions of ions formed by electrospray ionization are influenced by solvents that are more volatile than water. Addition of even small amounts of two solvents that are less volatile than water, ethylene glycol and 2-methoxyethanol, also results in preferential deprotonation of higher charge state ions of small peptides, but these solvents actually produce an enhancement in the higher charge state ions for both cytochrome c and myoglobin. For instruments that have capabilities that improve with lower m/z, this effect could be taken advantage of to improve the performance of an analysis.     

Disparity between solution-phase equilibria and charge state distributions in positive-ion electrospray mass spectrometry

Two peptides, bradykinin and gramicidin S, were used to investigate the relationship between protonation in the solution phase and charge state distribution observed in electrospray ionization (ES) mass spectra. The degree of protonation in solution was estimated using acid-base equilibrium calculations where possible. Protonation in solution was varied by adjusting pH, solvent composition and peptide concentration. Major disparities were observed between calculated solution-phase peptide protonation and the charge state distributions observed in ES mass spectra. The [(M + 2H)²⁺]/[(M + H)⁺] ratio calculated in solution was larger than the abundance ratio (M + 2H)²⁺ /(M + H)⁺ in the ES mass spectra of all acidic aqueous (pH < 6.5) and non-aqueous solutions; in basic aqueous solutions (pH > 9.5) the opposite was true. At high pH, electrophoretic droplet charging may reduce the activity of OH^? in positively charged droplets. The results at low pH imply the existence of supplementary factors in the ES ionization process which largely attenuate the degree of charging in the gas phase as compared with solution. Factors such as the increasing intra- and intermolecular coulombic repulsion between charge carriers (protons) and increasing attractive forces between protonated sites and counterions at progressively later stages of charged droplet evaporation were hypothesized to be chiefly responsible for this effect. Non-aqueous solvents of high basicity compete with analytes to some extent for available protons, forming protonated solvent molecules while decreasing the sensitivity and the degree of multiple charging of peptides.     

Approaches towards the automated interpretation and prediction of electrospray tandem mass spectra of non-peptidic combinatorial compounds

Combinatorial chemistry is widely used within the pharmaceutical industry as a means of rapid identification of potential drugs. With the growth of combinatorial libraries, mass spectrometry (MS) became the key analytical technique because of its speed of analysis, sensitivity, accuracy and ability to be coupled with other analytical techniques. In the majority of cases, electrospray mass spectrometry (ES-MS) has become the default ionisation technique. However, due to the absence of fragment ions in the resulting spectra, tandem mass spectrometry (MS/MS) is required to provide structural information for the identification of an unknown analyte. This work discusses the first steps of an investigation into the fragmentation pathways taking place in electrospray tandem mass spectrometry. The ultimate goal for this project is to set general fragmentation rules for non-peptidic, pharmaceutical, combinatorial compounds. As an aid, an artificial intelligence (AI) software package is used to facilitate interpretation of the spectra. This initial study has focused on determining the fragmentation rules for some classes of compound types that fit the remit as outlined above. Based on studies carried out on several combinatorial libraries of these compounds, it was established that different classes of drug molecules follow unique fragmentation pathways. In addition to these general observations, the specific ionisation processes and the fragmentation pathways involved in the electrospray mass spectra of these systems were explored. The ultimate goal will be to incorporate our findings into the computer program and allow identification of an unknown, non-peptidic compound following insertion of its ES-MS/MS spectrum into the AI package. The work herein demonstrates the potential benefit of such an approach in addressing the issue of high-throughput, automated MS/MS data interpretation.     

Mass and charge state assignment for proteins and peptide mixtures via noncovalent adduction in electrospray mass spectrometry

A method has been developed that takes advantage of the formation of noncovalent compounds in electrospray mass spectrometry. Mixtures of proteins and peptides are shown to produce an intense ion that corresponds to a 1:1 complex with a crown ether (18-crown-6). Although the crown ether may be added directly to the solution, for the current experiments it is introduced via the methanol liquid sheath. The spacing of these complexed species in the mass spectrum allows unambiguous determination of the charge state of the ions and their actual mass. Through constant neutral loss scans, charge state may be determined, mass assigned, spectra simplified, and chemical noise may be reduced for the analysis of complex peptide samples without chromatographic separation. Finally, the prevalence of single complexation permits mass assignments based on the mass difference of a single protein ion and its complexed form at any charge state. In essence, the method performs a separation based on charge state. It can be used to complement chromatographic separation and deconvolution algorithms for the electrospray mass spectrometry analysis of peptide-protein mixtures.     

Modeling the maximum charge state of arginine-containing peptide ions formed by electrospray ionization

A model for the gas-phase proton transfer reactivity of multiply protonated molecules is used to quantitatively account for the maximum charge states of a series of arginine-containing peptide ions measured by Downard and Biemann (Int. J. Mass Spectrom. Ion Processes 1995, 148, 191-202). We find that our calculations account exactly for the maximum charge state for 7 of the 10 peptides and are off by one charge for the remaining 3. These calculations clearly predict the trend in maximum charge states for these peptides and provide further evidence that the maximum charge state of ions formed by electrospray ionization is determined by their gas-phase proton transfer reactivity.     

Genius: a genetic algorithm for automated structure elucidation from 13C NMR spectra

The automated structure elucidation of organic molecules from experimentally obtained properties is extended by an entirely new approach. A genetic algorithm is implemented that uses molecular constitution structures as individuals. With this approach, the structure of organic molecules can be optimized to meet experimental criteria, if in addition a fast and accurate method for the prediction of the used physical or chemical features is available. This is demonstrated using 13C NMR spectrum as readily obtainable information. By means of artificial neural networks a fast and accurate method for calculating the 13C NMR spectrum of the generated structures exists. The method is implemented and tested successfully for organic molecules with up to 18 non-hydrogen atoms.     

A framework for automated structure elucidation from routine NMR spectra

Methods to automate structure elucidation that can be applied broadly across chemical structure space have the potential to greatly accelerate chemical discovery. NMR spectroscopy is the most widely used and arguably the most powerful method for elucidating structures of organic molecules. Here we introduce a machine learning (ML) framework that provides a quantitative probabilistic ranking of the most likely structural connectivity of an unknown compound when given routine, experimental one dimensional ¹H and/or ¹³C NMR spectra. In particular, our ML-based algorithm takes input NMR spectra and (i) predicts the presence of specific substructures out of hundreds of substructures it has learned to identify; (ii) annotates the spectrum to label peaks with predicted substructures; and (iii) uses the substructures to construct candidate constitutional isomers and assign to them a probabilistic ranking. Using experimental spectra and molecular formulae for molecules containing up to 10 non-hydrogen atoms, the correct constitutional isomer was the highest-ranking prediction made by our model in 67.4% of the cases and one of the top-ten predictions in 95.8% of the cases. This advance will aid in solving the structure of unknown compounds, and thus further the development of automated structure elucidation tools that could enable the creation of fully autonomous reaction discovery platforms.

A machine learning model and graph generator were able to accurately predict for the presence of nearly 1000 substructures and the connectivity of small organic molecules from experimental 1D NMR data.     

Mass and charge assignment for electrospray ions by cation adduction

The assignment of the mass (m) value from the m/z value for ions with a multiple number of charges (z) in electrospray mass spectra usually utilizes multiple peaks of the same m but different z values, or unit-mass—separated isotopic peaks of the same z value from high resolution spectra. The latter approach is also feasible with much less resolving power using adduct ions of much higher mass separation. The application of this to mixture spectra containing many masses, such as spectra from tandem mass spectrometry (MS/MS) ion dissociation, does not appear to have been pointed out previously. Thus, replacing two protons by one Cu²⁺ ion increases the mass by 61.5 Da, with this shift providing a mass scale for assignment of m and z from this pair of m/z values. The more common Na⁺ adduct peaks provide a 22.0 Da separation, of utility for 1000 resolving power only below approximately 10 kDa. Further, collisional dissociation lowers the degree of Cu²⁺ adduction in the resulting sequence-specific fragment ions much less than that of the corresponding Na⁺ adducts, making the Cu²⁺ adducts far more useful for m and z determination in MS/MS studies.     

Modifying the charge state distribution of proteins in electrospray ionization mass spectrometry by chemical derivatization

Electrospray ionization (ESI) of denatured proteins produces a broad distribution of multiply-charged ions leading to multiple peaks in the mass spectrum. We investigated changes in the positive-mode ESI charge state distribution produced by several chemical modifications of denatured proteins. Capping carboxylic acid groups with neutral functional groups yields little change in charge state distribution compared with unmodified proteins. The results indicate that carboxyl groups do not play a significant role in the positive charging of denatured proteins in ESI. The modification of proteins with additional basic sites or fixed positive charges generates substantially higher charge states, providing evidence that the number of ionizable sites, rather than molecular size and shape, determines ESI charging for denatured proteins. Fixed charge modification also significantly reduces the number of protons acquired by a protein, in that the charge state envelope is not increased by the full number of fixed charges appended. This result demonstrates that Coulombic repulsion between positive charges plays a significant role in determining charge state distribution by affecting the gas-phase basicity of ionizable sites. Addition of fixed-charge moieties to a protein is a useful approach for shifting protein charge state distributions to higher charge states, and with further work, it may help limit the distribution of protein ions to fewer charge states.     

A fast algorithm and software for analysis of FT-ICR data

In this paper, we present and analyze a fast algorithm that determines the possible molecular formulae corresponding to the resolved peaks in the spectral data obtained from a mass analyzer like an FT-ICR-MS. In contrast to our approach, most known algorithms and software that attempt to solve this important problem are brute-force in nature and consequently, highly prone to combinatorial explosion when dealing with the volume of real data. We also present an object-oriented implementation of our algorithm in a general-purpose, user-friendly, interactive, and easily extensible software tool PG Compound Match Finder. A run-time performance analysis of our software shows that even when dealing with several billion theoretical possibilities matched against tens of thousands of resolved peaks, a complete analysis using today’s standard desktop machines can take only a few minutes.     

Automated charge state determination of complex isotope-resolved mass spectra by peak-target Fourier transform

This study describes a new algorithm for charge state determination of complex isotope-resolved mass spectra. This algorithm is based on peak-target Fourier transform (PTFT) of isotope packets. It is modified from the widely used Fourier transform method because Fourier transform may give ambiguous charge state assignment for low signal-to-noise ratio (S/N) or overlapping isotopic clusters. The PTFT algorithm applies a novel "folding" strategy to enhance peaks that are symmetrically spaced about the targeted peak before applying the FT. The "folding" strategy multiplies each point to the high-m/z side of the targeted peak by its counterpart on the low-m/z side. A Fourier transform of this "folded" spectrum is thus simplified, emphasizing the charge state of the "chosen" ion, whereas ions of other charge states contribute less to the transformed data. An intensity-dependent technique is also proposed for charge state determination from frequency signals. The performance of PTFT is demonstrated using experimental electrospray ionization Fourier transform ion cyclotron resonance mass spectra. The results show that PTFT is robust for charge state determination of low S/N and overlapping isotopic clusters, and also useful for manual verification of potential hidden isotopic clusters that may be missed by the current analysis algorithms, i.e., AID-MS or THRASH.