Evaluating the Accuracy of the QCEIMS Approach for Computational Prediction of Electron Ionization Mass Spectra of Purines and Pyrimidines

Mass spectrometry is the most commonly used method for compound annotation in metabolomics. However, most mass spectra in untargeted assays cannot be annotated with specific compound structures because reference mass spectral libraries are far smaller than the complement of known molecules. Theoretically predicted mass spectra might be used as a substitute for experimental spectra especially for compounds that are not commercially available. For example, the Quantum Chemistry Electron Ionization Mass Spectra (QCEIMS) method can predict 70 eV electron ionization mass spectra from any given input molecular structure. In this work, we investigated the accuracy of QCEIMS predictions of electron ionization (EI) mass spectra for 80 purine and pyrimidine derivatives in comparison to experimental data in the NIST 17 database. Similarity scores between every pair of predicted and experimental spectra revealed that 45% of the compounds were found as the correct top hit when QCEIMS predicted spectra were matched against the NIST17 library of >267,000 EI spectra, and 74% of the compounds were found within the top 10 hits. We then investigated the impact of matching, missing, and additional fragment ions in predicted EI mass spectra versus ion abundances in MS similarity scores. We further include detailed studies of fragmentation pathways such as retro Diels–Alder reactions to predict neutral losses of (iso)cyanic acid, hydrogen cyanide, or cyanamide in the mass spectra of purines and pyrimidines. We describe how trends in prediction accuracy correlate with the chemistry of the input compounds to better understand how mechanisms of QCEIMS predictions could be improved in future developments. We conclude that QCEIMS is useful for generating large-scale predicted mass spectral libraries for identification of compounds that are absent from experimental libraries and that are not commercially available.

OKN-007 Alters Protein Expression Profiles in High-Grade Gliomas: Mass Spectral Analysis of Blood Sera

Current therapies for high-grade gliomas, particularly glioblastomas (GBM), do not extend patient survival beyond 16–22 months. OKN-007 (OKlahoma Nitrone 007), which is currently in phase II (multi-institutional) clinical trials for GBM patients, and has demonstrated efficacy in several rodent and human xenograft glioma models, shows some promise as an anti-glioma therapeutic, as it affects most aspects of tumorigenesis (tumor cell proliferation, angiogenesis, migration, and apoptosis). Combined with the chemotherapeutic agent temozolomide (TMZ), OKN-007 is even more effective by affecting chemo-resistant tumor cells. In this study, mass spectrometry (MS) methodology ESI-MS, mass peak analysis (Leave One Out Cross Validation (LOOCV) and tandem MS peptide sequence analyses), and bioinformatics analyses (Ingenuity® Pathway Analysis (IPA®), were used to identify up- or down-regulated proteins in the blood sera of F98 glioma-bearing rats, that were either untreated or treated with OKN-007. Proteins of interest identified by tandem MS-MS that were decreased in sera from tumor-bearing rats that were either OKN-007-treated or untreated included ABCA2, ATP5B, CNTN2, ITGA3, KMT2D, MYCBP2, NOTCH3, and VCAN. Conversely, proteins of interest in tumor-bearing rats that were elevated following OKN-007 treatment included ABCA6, ADAMTS18, VWA8, MACF1, and LAMA5. These findings, in general, support our previous gene analysis, indicating that OKN-007 may be effective against the ECM. These findings also surmise that OKN-007 may be more effective against oligodendrogliomas, other brain tumors such as medulloblastoma, and possibly other types of cancers.

Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry

Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomic analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.

Synthesis, Molecular Docking and DFT Studies of Biologically Active N-((3-(4-Nitrophenyl)-1-phenyl-1H-pyrazol-4-yl)methylene)aniline Derivatives

Some biologically active pyrazole clubbed imino molecules have been designed and synthesized from 1-phenyl-3-nitro phenyl-1H- pyrazol-4-carboxaldehyde and substituted aromatic amines via acid catalyzed condensation reaction. All the synthesized molecules were characterized by IR, 1H NMR, 13C NMR and mass spectral techniques. The in vitro antibactericidal property of the synthesized compounds was screened and compared with the results of theoretical molecular docking. Optimization of molecular geometry, DNA binding interaction and FMO analysis were also investigated by computational studies using Gaussian 16 package at B3LYP/6-31G(d,p) level. All the synthesized compounds exhibited moderate to good biological activities both experimentally and theoretically.

Eco-friendly Synthesis of Some New Benzylidene-iminothiazolyl-pyrazol-3-ol Derivatives via One-Pot Multicomponent Reaction and Evaluation of Antioxidant Activities

In present work, one-pot multicomponent reaction (MCR) route for the synthesis of benzylideneiminothiazolyl- pyrazol-3-ol derivatives (5a-p) by reacting ethyl cyanoacetate (1), substituted benzaldehyde (2a-c), thiosemicarbazide (3) and substituted phenacyl bromide (4a-g). This reaction proceeds by using bleaching earth clay (BEC) (pH 12.5) in PEG-400 as a green reaction media. All the synthesized compounds were characterized by IR, 1H NMR, 13C NMR and mass spectral data. The pharmacological investigation of the synthesized compounds suggest that most of them showed good antioxidant activity.

Comprehensive Investigation of a Toxic Microcystis sp. (Cyanobacteria) Collected from Snow Lake (New Mexico, USA).

The toxin producing cyanobacterium Microcystis sp. was collected in the mid October 2020 from the shallow waters of Snow Lake (New Mexico, USA). This species caused a visible bloom consisting of the pale green irregular macro colonies. Mass spectral analysis of the biomass revealed the presence of 4 derivatives of microcystin in that bloom: MC-LR (in the water and biomass), MC-RR (in biomass), MC-LY (in biomass), and MC-YR (in biomass).Next-generation sequencing allowed the retrieval of two Microcystis sequences in the bloom; which are molecular benchmarks for toxic Microcystis that may be used in future monitoring studies. Light microscopy provided evidence for the taxonomic affiliation of the found morphotype as Microcystis flos-aquae (Wittrock) Kirchner. However, molecular sequencing and the present situation in cyanobacterial taxonomy prevented affiliation of our morphotype to Microcystis flos-aquae, justifying following name – Microcystis sp. Confocal microscopy was used to determine the distribution of the cell content utilizing 3D stereo imaging. Emission spectra analysis identified the pigment composition and pigment distribution within the cells. SEM revealed 3D arrangement of the cells in the colonies, texture of the surface of the cells (perhaps dehydrated collapsed polysaccharides), F-layer and pili-like structures. Additionally, SEM/EDS analysis confirmed the F-layer using elemental composition analysis, which showed sulfur in the F-layer – typical element for that structure. Through the use of AFM, we analyzed the texture of the cell's surface and confirmed pili-like structures.

Contamination of the Dzheltulak-1 river basin under alluvial gold mining (the Amur region)

The purpose of the introduced research is to study the environmental impact of placer gold mining. The object of the study is natural and natural-man-made geosystems of the Dzheltulak-1 river located in the Amur region. The content of the main cations and microelements in water samples was determined by atomic emission and mass spectral methods. The content of micro- and rock-forming elements in bottom sediments and soils was determined by X-ray fluorescence using XRF-1800 X-ray spectrometer (Shimadzu, Japan). The results of the conducted studies indicate that the contents of iron, manganese, copper, aluminum, vanadium, molybdenum, mercury and ammonium ions exceed commercial fishery standards in a significant part of the surface water samples. It is found out that settlement ponds negatively affect the water quality in the river Dzheltulak-1 downstream due to the dam drainage. The highest concentrations of dissolved forms of mercury were noted in the water of the settlement ponds. The gross content of arsenic in the samples of bottom sediments and soils exceeds sanitary and hygienic standards by 2.7–14.5 times. The distributions of mercury as the most dangerous pollutant among the biogenic components of geochemical landscape were worked out in detail. Mercury contamination of soils was classified according to the forms of mercury occurrence: free, physically sorbed, chemisorbed, sulfide and isomorphic. It has been shown that the free form is characteristic of fresh mercury contamination due to the use of prohibited technological schemes for gold-bearing sands separation by the amalgamation method.

MEMO: Mass Spectrometry-based Sample Vectorization to Explore Chemodiverse Datasets

In natural products research, chemodiverse extracts coming from multiple organisms are explored for novel bioactive molecules, sometimes over extended periods. Samples are usually analyzed by liquid chromatography coupled with fragmentation mass spectrometry to acquire informative mass spectral ensembles. Such data is then exploited to establish relationships among analytes or samples (e.g. via molecular networking) and annotate metabolites. However, the comparison of samples profiled in different batches is challenging with current metabolomics methods. Indeed, the experimental variation - changes in chromatographical or mass spectrometric conditions - often hinders the direct comparison of the profiled samples. Here we introduce MEMO - MS2 BasEd SaMple VectOrization - a method allowing to cluster large amounts of chemodiverse samples based on their LC-MS/MS profiles in a retention time agnostic manner. This method is particularly suited for heterogeneous and chemodiverse sample sets. MEMO demonstrated similar clustering performance as state-of-the-art metrics taking into account fragmentation spectra. More importantly, such performance was achieved without the requirement of a prior feature alignment step and in a significantly shorter computational time. MEMO thus allows the comparison of vast ensembles of samples, even when analyzed over long periods of time, and on different chromatographic or mass spectrometry platforms. This new addition to the computational metabolomics toolbox should drastically expand the scope of large-scale comparative analysis.

From mass spectral features to molecules in molecular networks: a novel workflow for untargeted metabolomics.

In the context of untargeted metabolomics, molecular networking is a popular and efficient tool which organizes and simplifies mass spectrometry fragmentation data (LC-MS/MS), by clustering ions based on a cosine similarity score. However, the nature of the ion species is rarely taken into account, causing redundancy as a single compound may be present in different forms throughout the network. Taking advantage of the presence of such redundant ions, we developed a new method named MolNotator. Using the different ion species produced by a molecule during ionization (adducts, dimers, trimers, in-source fragments), a predicted molecule node (or neutral node) is created by triangulation, and ultimately computing the associated molecule calculated mass. These neutral nodes provide researchers with several advantages. Firstly, each molecule is then represented in its ionization context, connected to all produced ions and indirectly to some coeluted compounds, thereby also highlighting unexpected widely present adduct species. Secondly, the predicted neutrals serve as anchors to merge the complementary positive and negative ionization modes into a single network. Lastly, the dereplication is improved by the use of all available ions connected to the neutral nodes, and the computed molecular masses can be used for exact mass dereplication. MolNotator is available as a Python library and was validated using the lichen database spectra acquired on an Orbitrap, computing neutral molecules for >90% of the 156 molecules in the dataset. By focusing on actual molecules instead of ions, MolNotator greatly facilitates the selection of molecules of interest.

Preparation and Characterization of New 1,3,5-Trisubstituted-2-Pyrazolines Derivative for their Anti-Inflammatory Activity

The objective of the paper was to design, synthesis and characterization of new 1,3,5-trisubstituted-2-pyrazolines derivative and evaluate for anti-inflammatory potential. The 1,3,5-tri-substituted-2-pyrazolines derivatives has been synthesized by the reaction of chalcone derivatives with 4-hydrazinylbenzene sulfonamide hydrochloride and phenyl hydrazine hydrochloride. Total Sixteen compounds has been synthesized and characterized by the IR, 1HNMR and mass spectral analysis. Proposed compounds have been evaluated for anti-inflammatory activity. Anti-inflammatory activity of the compounds carried out by two animal model i.e. Carrageenan induced, paw edema in rats and Inhibition of formalin induced paw edema in rats. Anti-inflammatory activity of the compounds C7, C8 and C2 were shown 98.26, 92.77 and 96.24 percentages of inhibition and compounds D7, D8 and D2 were shown 81.50, 83.81 and 78.32 percentages of inhibition as compared to the standard drug Diclofenac at 10 mg/kg was inhibit the inflammation 99.42 % after 6h. These result is a evident that synthesized compounds show relevant degree of anti-inflammatory activity as compared to the standard drug. It is also concluded that the presence of SO2NH2 group, Cl, CH3, OCH3 and N(CH3)2 group may provide the active compounds when attached to the pyrazoline group. But the addition of OH, Br and no substitution in phenyl ring may diminish the activity.