The results indicate that noise, alkali ion adducts, signal overlap, as well as low intensity protein charge states, can be neglected for preliminary experiments, as well as in screening assays. One comprehensive data analysis performed as a control should be sufficient to validate this hypothesis for other binding systems as well.
State-of-the-art purification of biomolecules, as well as separation of complex omic mixtures, is crucial for modern biomedical research. Mass spectroscopy (MS) represents a technique that both requires very clean biomedical samples and can substantially assist liquid chromatography (LC) separations, using either LC-MS or LC-MS/MS methods available. Here, a brief overview of the applicability of LC-MS/MS methodology for structural analyses of complex omic mixtures without prior purification of each sample component will be given. When necessary bioinformatic tools are available, these can be carried out quite quickly. However, manual data analysis of such complex mixtures is typically very slow. On the other hand, the need for high-level purity of protein samples for modern biomedical research will be discussed. Often, modification of protein purification protocols is needed, or additional purification steps may be either required or preferred. In the context of mass spectroscopy-related biomedical research, purification of pmol and subpmol amounts of biomedical samples, as well as commercial availability of pmol amounts of purified standards will be discussed.
Hardware ion scan functions unique to tandem mass spectrometry (MS/MS) mode of data acquisition, such as precursor ion scan (PIS) and neutral loss scan (NLS), are important for selective extraction of key structural data from complex MS/MS spectra. However, their software counterparts, software ion scan (SIS) functions, are still not regularly available. Software ion scan functions can be easily coded for additional functionalities, such as software multiple precursor ion scan, software no ion scan, and software variable ion scan functions. These are often necessary, since they allow more efficient analysis of complex MS/MS datasets, often encountered in glycomics and lipidomics. Software ion scan functions can be easily coded by using modern script languages and can be independent of instrument manufacturer. Here we demonstrate the utility of SIS functions on a medium-size glycomic MS/MS dataset. Knowledge of sample properties, as well as of diagnostic and conditional diagnostic ions crucial for data analysis, was needed. Based on the tables constructed with the output data from the SIS functions performed, a detailed analysis of a complex MS/MS glycomic dataset could be carried out in a quick, accurate, and efficient manner. Glycomic research is progressing slowly, and with respect to the MS experiments, one of the key obstacles for moving forward is the lack of appropriate bioinformatic tools necessary for fast analysis of glycomic MS/MS datasets. Adding novel SIS functionalities to the glycomic MS/MS toolbox has a potential to significantly speed up the glycomic data analysis process. Similar tools are useful for analysis of lipidomic MS/MS datasets as well, as will be discussed briefly.
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