An assessment of structure and toxicity correlation in organochlorine pesticides

Organochlorines are the most successful, profitably utilized and commercialized group of pesticides. They have gained huge popularity and prominence in a short span of time by virtue of their ability to control almost all kinds of pests including insect, fungi, rodent, etc. The toxicity of an individual pesticide to the pests is predominantly determined by its structure, the different moieties attached to parent compound, their spatial arrangements within molecule, nature of substituents, polarity, symmetry and asymmetry of molecules, the solubility and sorption values. The present paper discusses the toxicity in terms of LD(50) of organochlorine pesticides on the basis of their structures. Further, the mode of action of these pesticides has been discussed for a better understanding of toxicity. Finally an attempt has been made to understand the structure toxicity relationship in organochlorine pesticides.     

Interpretation of mass spectra from organic compounds in aerosol time-of-flight mass spectrometry

Organic compounds containing a variety of functional groups have been analyzed using aerosol time-of-flight mass spectrometry. Both positive and negative laser desorption/ionization mass spectra have been acquired for compounds of relevance to ambient air particulate matter, including polycyclic aromatic hydrocarbons, heterocyclic analogues, aromatic oxygenated compounds such as phenols and acids, aliphatic dicarboxylic acids, and reduced nitrogen species such as amines. In many cases, positive ion mass spectra are similar to those found in libraries for 70-eV electron impact mass spectrometry. However, formation of even-electron molecular ions due to adduct formation also plays a major role in ion formation. Negative ion mass spectra suggest that organic compounds largely disintegrate into carbon cluster fragments (C(n)- and C(n)H-). However, information about the heteroatoms present in organic molecules, especially nitrogen and oxygen, is carried dominantly by negative ion spectra, emphasizing the importance of simultaneous analysis of positive and negative ions in atmospheric samples.     

Automatic validation of phosphopeptide identifications from tandem mass spectra

We developed and compared two approaches for automated validation of phosphopeptide tandem mass spectra identified using database searching algorithms. Phosphopeptide identifications were obtained through SEQUEST searches of a protein database appended with its decoy (reversed sequences). Statistical evaluation and iterative searches were employed to create a high-quality data set of phosphopeptides. Automation of postsearch validation was approached by two different strategies. By using statistical multiple testing, we calculate a p value for each tentative peptide phosphorylation. In a second method, we use a support vector machine (SVM; a machine learning algorithm) binary classifier to predict whether a tentative peptide phosphorylation is true. We show good agreement (85%) between postsearch validation of phosphopeptide/spectrum matches by multiple testing and that from support vector machines. Automatic methods conform very well with manual expert validation in a blinded test. Additionally, the algorithms were tested on the identification of synthetic phosphopeptides. We show that phosphate neutral losses in tandem mass spectra can be used to assess the correctness of phosphopeptide/spectrum matches. An SVM classifier with a radial basis function provided classification accuracy from 95.7% to 96.8% of the positive data set, depending on search algorithm used. Establishing the efficacy of an identification is a necessary step for further postsearch interrogation of the spectra for complete localization of phosphorylation sites. Our current implementation performs validation of phosphoserine/phosphothreonine-containing peptides having one or two phosphorylation sites from data gathered on an ion trap mass spectrometer. The SVM-based algorithm has been implemented in the software package DeBunker. We illustrate the application of the SVM-based software DeBunker on a large phosphorylation data set.     

Extraction of mass spectra and chromatographic profiles from overlapping GC/MS signal with background

An adaptive immune algorithm (AIA) was proposed for resolution of the overlapping GC/MS signal with background. By using AIA, the chromatographic profiles corresponding to the independent components (ICs) in the overlapping signal are calculated with the mass spectra extracted by means of independent component analysis (ICA). The number of the ICs in the overlapping signal is determined by the difference between the reconstructed and the original data. Both simulated and experimental data are investigated with the proposed AIA approach. It was found that the mass spectra and chromatographic profiles of the components in an overlapping multicomponent GC/MS signal can be accurately resolved with the existence of background, and the results are better than that by using an interactive self-modeling mixture analysis (SIMPLISMA) method. The AIA approach may be a promising tool for the resolution of overlapping GC/MS signal.     

Identification of bacterial proteins observed in MALDI TOF mass spectra from whole cells.

Characteristic ions in the MALDI TOF mass spectra from bacterial cells have been associated with four known proteins. The proteins, observed both from cells and in filtered cellular suspensions, were isolated by HPLC and identified on the basis of their mass spectra and their partial amino acid sequence, determined using the Edman method (10-15 residues). The acid resistance proteins HdeA and HdeB give rise to ions near m/z 9735 and 9060 in MALDI TOF mass spectra from cells and from extracts of both Escherichia coli 1090 and Shigella flexneri PHS-1059. However, the proteins associated with proteolytic cleavage by the peptidase Lep, rather than the precursor proteins, were observed, both using cells and from cellular extracts. A cold-shock protein, CspA, was associated with the ion near m/z 7643 from Pseudomonas aeruginosa. Similarly, a cold-acclimation protein, CapB, was identified as the source of the ion near m/z 7684 in P. putida. This last protein was homologous with a known CapB from P. fragi. While these experiments involved the detection of known or homologous proteins from typical bacteria, this same approach could also be applied to the detection of unique proteins or biomarker proteins associated with other bacteria of public health significance.     

SearchXLinks. A program for the identification of disulfide bonds in proteins from mass spectra

We present the computer program SearchXLinks that analyzes mass spectra with the aim of identifying disulfide bonds and other modifications in proteins of known amino acid sequence. Disulfide bonds can be intra- or intermolecular. To decrease the number of false positives, the analysis of in-source decay and tandem mass spectra are coupled into the program. The steps taken during a SearchXLinks run are outlined, and the computational costs are discussed. The application of the program is illustrated by the analysis of data from recent studies on bovine ribonuclease A and bovine serum albumin. The software can be used free of charge on the Internet at http://www.searchxlinks.de.     

InsPecT: identification of posttranslationally modified peptides from tandem mass spectra

Reliable identification of posttranslational modifications is key to understanding various cellular regulatory processes. We describe a tool, InsPecT, to identify posttranslational modifications using tandem mass spectrometry data. InsPecT constructs database filters that proved to be very successful in genomics searches. Given an MS/MS spectrum S and a database D, a database filter selects a small fraction of database D that is guaranteed (with high probability) to contain a peptide that produced S. InsPecT uses peptide sequence tags as efficient filters that reduce the size of the database by a few orders of magnitude while retaining the correct peptide with very high probability. In addition to filtering, InsPecT also uses novel algorithms for scoring and validating in the presence of modifications, without explicit enumeration of all variants. InsPecT identifies modified peptides with better or equivalent accuracy than other database search tools while being 2 orders of magnitude faster than SEQUEST, and substantially faster than X!TANDEM on complex mixtures. The tool was used to identify a number of novel modifications in different data sets, including many phosphopeptides in data provided by Alliance for Cellular Signaling that were missed by other tools.     

Method for determination of strong interaction constants from hadronic mass spectra

A method is proposed for determination of quark-antiquark strong interaction parameters in the nonperturbative domain of quantum chromodynamics at relatively large distances. The method is based on a relativistic potential model of quasi-independent quarks and allows us, using experimental data on meson mass spectra, to calculate the quark current masses and the string tension constant with high accuracy. Translated from Izmeritel'naya Tekhnika, No. 12, pp. 3–5, December, 1996.     

Evaluating chlorine isotope effects from isotope ratios and mass spectra of polychlorinated molecules

Compound-specific chlorine isotope analysis receives much interest to assess the fate of chlorinated hydrocarbons in contaminated environments. This paper provides a theoretical basis to calculate isotope ratios and quantify isotope fractionation from ion-current ratios of molecular- and fragment-ion multiplets. Because both (35)Cl and (37)Cl are of high abundance, polychlorinated hydrocarbons consist of molecules containing different numbers of (37)Cl denoted as isotopologues. We show that, during reactions, the changes in isotopologue ratios are proportional to changes in the isotope ratio assuming a nonselective isotope distribution in the initial compound. This proportionality extents even to fragments formed in the ion source of a mass spectrometer such as C 2Cl 2 (double dechlorinated fragment of perchloroethylene, PCE). Fractionation factors and kinetic isotope effects (KIE) may, therefore, be evaluated from isotope, isotopologue or even fragment ratios according to conventional simple equations. The proportionality is exact with symmetric molecules such as dichloroethylene (DCE) and PCE, whereas it is approximately true with molecules containing nonreactive positions such as trichloroethylene (TCE). If in the latter case isotope ratios are derived from dechlorinated fragments, e.g., C 2HCl 2, it is important that fragmentation in the ion source affect all molecular positions alike, as otherwise isotopic changes in reactive positions may be underrepresented.     

Generalized correlation of refrigerant mass flow rate through adiabatic capillary tubes using artificial neural network

A capillary tube is a common expansion device widely used in small-scale refrigeration and air-conditioning systems. Generalized correlation method for refrigerant flow rate through adiabatic capillary tubes is developed by combining dimensional analysis and artificial neural network (ANN). Dimensional analysis is utilized to provide the generalized dimensionless parameters and reduce the number of input parameters, while a three-layer feedforward ANN is served as a universal approximator of the nonlinear multi-input and single-output function. For ANN training and test, measured data for R12, R134a, R22, R290, R407C, R410A, and R600a in the open literature are employed. The trained ANN with just one hidden neuron is good enough for the training data with average and standard deviations of 0.4 and 6.6%, respectively. By comparison, for two test data sets, the trained ANN gives two different results. It is well interpreted by evaluating the outlier with a homogeneous equilibrium model.     

Moving window two-dimensional correlation spectroscopy and determination of signal-to-noise threshold in correlation spectra

In this paper we report two new developments in two-dimensional (2D) correlation spectroscopy; one is the combination of the moving window concept with 2D spectroscopy to facilitate the analysis of complex data sets, and the other is the definition of the noise level in synchronous/asynchronous maps. A graphical criterion for the latter is also proposed. The combination of the moving window concept with correlation spectra allows one to split a large data matrix into smaller and simpler subsets and to analyze them instead of computing overall correlation. A three-component system that mimics a consecutive chemical reaction is used as a model for the illustration of the two ideas. Both types of correlation matrices, variable-variable and sample-sample, are analyzed, and a very good agreement between the two is met. The proposed innovations enable one to comprehend the complexity of the data to be analyzed by 2D spectroscopy and thus to avoid the risks of over-interpretation, liable to occur whenever improper caution about the number of co-existing species in the system is taken.     

Prediction of collision-induced-dissociation spectra of peptides with post-translational or process-induced modifications

Mass spectrometry, combined with collision-induced dissociation (CID), has become the method of choice for analyzing protein post-translational and process-induced modifications. However, confident and automated identification of modifications and modification sites is often challenged by the diversity of modifications and their labile nature under typical CID conditions. An accurate prediction of the CID spectra of modified peptides will improve the reliability of automated determination of modifications and modification sites. In this article, the kinetic model for the prediction of peptide CID spectra is extended to the prediction of the CID spectra of modified peptides. The mathematical model for predicting CID spectra of peptides with enzymatic and chemical modifications such as (1) phosphorylation of serine, threonine, and tyrosine, (2) S-carboxymethylation and carbamidomethylation of cysteine, (3) different stages of oxidation of methionine, tryptophan, and cysteine, (4) glycation of lysine, (5) O-mannosylation of serine, (6) hydroxylation of lysine, and (7) N-monomethylation and N-dimethylation of lysine is described. The mathematical model, once established with CID spectra of peptides with known modifications and modification sites, is able to predict CID spectra with excellent accuracy in ion intensities, facilitating more reliable identification of modification and modification sites.