MolDiscovery: learning mass spectrometry fragmentation of small molecules.
Ontology highlight
ABSTRACT:
SUBMITTER: Cao L
PROVIDER: S-EPMC8211649 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12566-010-0015-9) contains supplementary material, which is available to authorized users.
| S-EPMC3015162 | biostudies-literature
Project description:Gas chromatography-mass spectrometry (GC-MS) acquisitions routinely yield hundreds to thousands of Electron Ionization (EI) mass spectra. The chemical identification of these spectra typically involves a search protocol that seeks an exact match to a reference spectrum. Reference spectra are found in comprehensive libraries of small molecule EI spectra curated by commercial and public entities. We developed ARISTO (Automatic Reduction of Ion Spectra To Ontology), a webtool, which provides information regarding the general chemical nature of the compound underlying an input EI mass spectrum. Importantly, ARISTO can provide such annotation without necessitating an exact match to a specific compound. ARISTO provides assignments to a subset of the ChEBI (Chemical Entities of Biological Interest) dictionary, an ontology, which aims to cover biologically relevant small molecules. Our system takes as input a mass spectrum represented as a series of mass and intensity pairs; the system returns a graphical representation of the supported ontology as well as a detailed table of suggested annotations along with their associated statistical evidence. ARISTO is accessible at this URL: http://www.ionspectra.org/aristo. The system is free, open to all and does not require registration of any sort.
| S-EPMC3125788 | biostudies-literature
Project description:Small molecules are known to stabilize membrane proteins and to modulate their function and oligomeric state, but such interactions are often hard to precisely define. Here we develop and apply a high-resolution, Orbitrap mass spectrometry-based method for analyzing intact membrane protein-ligand complexes. Using this platform, we resolve the complexity of multiple binding events, quantify small molecule binding and reveal selectivity for endogenous lipids that differ only in acyl chain length.
| S-EPMC4856209 | biostudies-literature
Project description:Matrix assisted laser desorption ionization time-of-flight (MALDI-TOF) imaging mass spectrometry has emerged as a powerful, label-free technique to visualize penetration of small molecules in vivo and in vitro, including in 3D cell culture spheroids; however, some spheroids do not grow sufficiently large to provide enough area for imaging mass spectrometry. Here, we describe an ex vivo method for visualizing unlabeled peptides and small molecules in tumor explants, which can be divided into pieces of desired size, thus circumventing the size limitations of many spheroids. As proof-of-concept, a small molecule drug (4-hydroxytamoxifen), as well as a peptide drug (cyclosporin A) and peptide chemical probe, can be visualized after in vitro incubation with tumor explants so that this technique may provide a solution to robing cell penetration by unlabeled peptides.
| S-EPMC6047048 | biostudies-literature
Project description:Ion-electron reaction based fragmentation methods (ExD) in tandem mass spectrometry (MS), such as electron capture dissociation (ECD) and electron transfer dissociation (ETD) represent a powerful tool for biological analysis. ExD methods have been used to differentiate the presence of the isoaspartate (isoAsp) from the aspartate (Asp) in peptides and proteins. IsoAsp is a ?(3)-type amino acid that has an additional methylene group in the backbone, forming a C(?)-C(?) bond within the polypeptide chain. Cleavage of this bond provides specific fragments that allow differentiation of the isomers. The presence of a C(?)-C(?) bond within the backbone is unique to ?-amino acids, suggesting a similar application of ExD toward the analysis of peptides containing other ?-type amino acids. In the current study, ECD and ETD analysis of several ?-amino acid containing peptides was performed. It was found that N-C(?) and C(?)-C(?) bond cleavages were rare, providing few c and z• type fragments, which was attributed to the instability of the C(?) radical. Instead, the electron capture resulted primarily in the formation of a• and y fragments, representing an alternative fragmentation pathway, likely initiated by the electron capture at a backbone amide nitrogen protonation site within the ? amino acid residues.
| S-EPMC4361814 | biostudies-literature
Project description:Liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) is widely used in identifying small molecules in untargeted metabolomics. Various strategies exist to acquire MS/MS fragmentation spectra; however, the development of new acquisition strategies is hampered by the lack of simulators that let researchers prototype, compare, and optimize strategies before validations on real machines. We introduce Virtual Metabolomics Mass Spectrometer (ViMMS), a metabolomics LC-MS/MS simulator framework that allows for scan-level control of the MS2 acquisition process in silico. ViMMS can generate new LC-MS/MS data based on empirical data or virtually re-run a previous LC-MS/MS analysis using pre-existing data to allow the testing of different fragmentation strategies. To demonstrate its utility, we show how ViMMS can be used to optimize N for Top-N data-dependent acquisition (DDA) acquisition, giving results comparable to modifying N on the mass spectrometer. We expect that ViMMS will save method development time by allowing for offline evaluation of novel fragmentation strategies and optimization of the fragmentation strategy for a particular experiment.
| S-EPMC6836109 | biostudies-literature
Project description:The high-throughput nature of proteomics mass spectrometry is enabled by a productive combination of data acquisition protocols and the computational tools used to interpret the resulting spectra. One of the key components in mainstream protocols is the generation of tandem mass (MS/MS) spectra by peptide fragmentation using collision induced dissociation, the approach currently used in the large majority of proteomics experiments to routinely identify hundreds to thousands of proteins from single mass spectrometry runs. Complementary to these, alternative peptide fragmentation methods such as electron capture/transfer dissociation and higher-energy collision dissociation have consistently achieved significant improvements in the identification of certain classes of peptides, proteins, and post-translational modifications. Recognizing these advantages, mass spectrometry instruments now conveniently support fine-tuned methods that automatically alternate between peptide fragmentation modes for either different types of peptides or for acquisition of multiple MS/MS spectra from each peptide. But although these developments have the potential to substantially improve peptide identification, their routine application requires corresponding adjustments to the software tools and procedures used for automated downstream processing. This review discusses the computational implications of alternative and alternate modes of MS/MS peptide fragmentation and addresses some practical aspects of using such protocols for identification of peptides and post-translational modifications.
| S-EPMC3434779 | biostudies-literature
Project description:Rapid and accurate clinical diagnosis remains challenging. A component of diagnosis tool development is the design of effective classification models with Mass spectrometry (MS) data. Some Machine Learning approaches have been investigated but these models require time-consuming preprocessing steps to remove artifacts, making them unsuitable for rapid analysis. Convolutional Neural Networks (CNNs) have been found to perform well under such circumstances since they can learn representations from raw data. However, their effectiveness decreases when the number of available training samples is small, which is a common situation in medicine. In this work, we investigate transfer learning on 1D-CNNs, then we develop a cumulative learning method when transfer learning is not powerful enough. We propose to train the same model through several classification tasks over various small datasets to accumulate knowledge in the resulting representation. By using rat brain as the initial training dataset, a cumulative learning approach can have a classification accuracy exceeding 98% for 1D clinical MS-data. We show the use of cumulative learning using datasets generated in different biological contexts, on different organisms, and acquired by different instruments. Here we show a promising strategy for improving MS data classification accuracy when only small numbers of samples are available.
| S-EPMC7644674 | biostudies-literature
Project description:Spatial and temporal changes in molecular expression are essential to embryonic development, and their characterization is critical to understand mechanisms by which cells acquire different phenotypes. Although technological advances have made it possible to quantify expression of large molecules during embryogenesis, little information is available on metabolites, the ultimate indicator of physiological activity of the cell. Here, we demonstrate that single-cell capillary electrophoresis-electrospray ionization mass spectrometry is able to test whether differential expression of the genome translates to the domain of metabolites between single embryonic cells. Dissection of three different cell types with distinct tissue fates from 16-cell embryos of the South African clawed frog (Xenopus laevis) and microextraction of their metabolomes enabled the identification of 40 metabolites that anchored interconnected central metabolic networks. Relative quantitation revealed that several metabolites were differentially active between the cell types in the wild-type, unperturbed embryos. Altering postfertilization cytoplasmic movements that perturb dorsal development confirmed that these three cells have characteristic small-molecular activity already at cleavage stages as a result of cell type and not differences in pigmentation, yolk content, cell size, or position in the embryo. Changing the metabolite concentration caused changes in cell movements at gastrulation that also altered the tissue fates of these cells, demonstrating that the metabolome affects cell phenotypes in the embryo.
| S-EPMC4450407 | biostudies-other
Project description:Methanococcus maripaludis is a methanogenic archaeon. Within its genome, there are two operons for membrane associated hydrogenases, eha and ehb. To investigate the regulation of ehb on the cell, an S40 mutant was constructed in such a way that a portion of the ehb operon was replaced by pac cassette in the wild type parental strain S2 (done by Whitman's group at the University of Georgia). The S40 and S2 strains were grown in 14N and 15N media with acetate separately. A biological replicate was made by switching the media. Mass spectrometry based quantitative proteomics were done on the mixtures to investigate the differences in expression patterns between S40 and S2. Keywords: isotope labeling mass spectrometry, quantitative proteomics
2005-09-20 | GSE2744 | GEO