High-energy collision-induced dissociation (CID) mass spectrometry provides a rapid and sensitive means for determining the primary sequence of peptides. The low-mass region (below mass 300) of a large number of tandem CID spectra of peptides has been analyzed. This mass region contains several types of informative fragment ions, including dipeptide ions, immonium ions, and other related ions. Useful low-mass ions are also present in negative-ion CID spectra. Immonium ions (general structure [H2N=CH-R](+), where R is the amino acid side chain) and related ions characteristic of specific amino acid residues give information as to the presence or absence of these residues in the peptide being analyzed. Tables of observed immonium and reiated ions for the 20 standard amino acids and for a number of modified amino acids are presented. A database consisting of 228 high-energy CID spectra of peptides has been established, and the frequency of occurrence of various ions indicative of specific ammo acid residues has been determined. Two model computer-aided schemes for analysis of the ammo-acid content of unknown peptides have been developed and tested against the database.

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An algorithm is presented for the generation of a reliable peptide component peak table from liquid chromatography-mass spectrometry (LC-MS) and subsequent quantitative analysis of stable isotope coded peptide samples. The method uses chemical noise filtering, charge state fitting, and deisotoping toward improved analysis of complex peptide samples. Overlapping peptide signals in mass spectra were deconvoluted by correlation with modeled peptide isotopic peak profiles. Isotopic peak profiles for peptides were generated in silico from a protein database producing reference model distributions. Doublets of heavy and light labeled peak clusters were identified and compared to provide differential quantification of pairs of stable isotope coded peptides. Algorithms were evaluated using peptides from digests of a single protein and a seven-protein mixture that had been differentially coded with stable isotope labeling agents and mixed in known ratios. The experimental results correlated well with known mixing ratios.

With the complete sequence of the yeast genome now available, efforts by many laboratories are underway to identify each of the spots on two-dimensional (2-D) gels corresponding to the most abundant yeast proteins. The high mass accuracy now attainable using matrix assisted laser desorption/ionization (MALDI)-mass spectrometry equipped with delayed extraction simplifies the process of identification, such that many spots can be unambiguously identified in a short period of time merely by using peptide mass fingerprinting and generally available database matching programs. Although it is not always possible to match spots between gels run by different laboratories, proteins generally yield the same abundant proteolytic fragments when tryptic digestions are performed. Databases containing these signature peptides not only simplify the task of reidentifying proteins from different gels, but also make it possible to identify small amounts of cross-contaminating proteins from different spots, as well as common extraneous contaminants such as human keratins. In this paper, we present data on the identification of > 20 previously unreported yeast proteins from 2-D gels. Some novel proteins were identified from randomly analyzed spots. Focusing on 14 spots in a narrow-pH-range gel, we demonstrate how organizing peak-table data and peptide match-list data into databases enables the identification of a larger percentage of the peaks.

Drug-induced liver injury (DILI) is the primary adverse event that results in withdrawal of drugs from the market and a frequent reason for the failure of drug candidates in development. The Liver Toxicity Biomarker Study (LTBS) is an innovative approach to investigate DILI because it compares molecular events produced in vivo by compound pairs that (a) are similar in structure and mechanism of action, (b) are associated with few or no signs of liver toxicity in preclinical studies, and (c) show marked differences in hepatotoxic potential. The LTBS is a collaborative preclinical research effort in molecular systems toxicology between the National Center for Toxicological Research and BG Medicine, Inc., and is supported by seven pharmaceutical companies and three technology providers. In phase I of the LTBS, entacapone and tolcapone were studied in rats to provide results and information that will form the foundation for the design and implementation of phase II. Molecular analysis of the rat liver and plasma samples combined with statistical analyses of the resulting datasets yielded marker analytes, illustrating the value of the broad-spectrum, molecular systems analysis approach to studying pharmacological or toxicological effects.

A new strategy is reported for extracting complete and partial sequence information from collision-induced dissociation (CID) spectra of peptides, CID spectra are obtained from high energy CID of peptide molecular ions on a four-sector tandem mass spectrometer with an electro-optically coupled microchannel array detector, A peak detection routine reduces the spectrum to a list of peak masses and peak heights, which is then used for sequencing, The sequencing algorithm was designed to use spectral data to generate sequence fits directly rather than to use data to test the fit of series of sequence guesses. The peptide sequencing algorithm uses a pattern based on the polymeric nature of peptides to classify spectral peaks into sets that are related in a sequence-independent manner, It then establishes sequence relationships among these sets, Peak detection from raw data takes 10-20 s, with sequence generation requiring an additional 10-60 s on a Sun 3/60 workstation, The program is written in the C language to run on a Unix platform. The principal advantages of our method are in the speed of analysis and the potential for identifying modified or rare amino acids. The algorithm was designed to permit real-time sequencing but awaits hardware modifications to allow real-time access to CID spectra.

Fligh-throughput biomolecular proliling techniques such as transcriptomics, proteomics and metabolomics are increasingly being used in in vivo studies to recognize and characterize effects of xenobiotics on organs and systems, Of particular interest are biornalkers of treatment-related effects which are detectible in easily accessible biological fluids such as bloocl. A funclamentai challenge in such biomarker stuciies is selecting among the plethora of biomolecular changes induced by a compound and revealed by molecular profìling, to identify biomarkers which are exclusively or predominantly clLre to specific processes. In this work we present a cross-cornpaftrnent con'elation network approach, involvirig no a priori supervision or design, to integrate proteomic, metabolomic ancl transcriptomic data for selecting circulating biomarkers. The case stucly we present is the identification of bioniarkers of drug-induced hepatic toxicity effects in a rodent moclel. Biornolecular' profiling of both blood plasma and liver tissüe froni Wistar l-Iannover rats admirristerecl a toxic compound yielded many hundreds of statistically signihcant molecular changes, We exploited dmgincluced correlations between blood plasma analytes and liver tissue molecules across study animals in order to nominate selected plasnia molecules as biomarkers of drug-incluced hepatic alterations of lipid metabolisrn and urea cycle processes.

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry is now an essential tool in biopolymer analysis. Sensitivity and mass range are unsurpassed, but mass measurement accuracy and resolution have been limited. With delayed extraction and a reflecting analyzer, mass measurements using MALDI-TOF can be made with an accuracy of a few parts per million (ppm). It is possible to distinguish Lys from Gln in peptides, and to determine the elemental composition of smaller molecules (mass 100-500). In database searching strategies, a smaller mass window, resulting from an increase in mass accuracy, greatly decreases the number of possible candidates. Mass measurement accuracy with errors less than 5 ppm is demonstrated on a mixture of 12 peptides ranging in mass from ca. 900 to 3700 Da. Mass measurements on 13 peaks in an unseparated tryptic digest of myoglobin gave results with an overall average error less than 3.5 ppm, with a maximum error of 7 ppm.