Hepatoprotective Activity of Lignin-Derived Polyphenols Dereplicated Using High-Resolution Mass Spectrometry, In Vivo Experiments, and Deep Learning.

Chronic liver diseases affect more than 1 billion people worldwide and represent one of the main public health issues. Nonalcoholic fatty liver disease (NAFLD) accounts for the majority of mortal cases, while there is no currently approved therapeutics for its treatment. One of the prospective approaches to NAFLD therapy is to use a mixture of natural compounds. They showed effectiveness in alleviating NAFLD-related conditions including steatosis, fibrosis, etc. However, understanding the mechanism of action of such mixtures is important for their rational application. In this work, we propose a new dereplication workflow for deciphering the mechanism of action of the lignin-derived natural compound mixture. The workflow combines the analysis of molecular components with high-resolution mass spectrometry, selective chemical tagging and deuterium labeling, liver tissue penetration examination, assessment of biological activity in vitro, and computational chemistry tools used to generate putative structural candidates. Molecular docking was used to propose the potential mechanism of action of these structures, which was assessed by a proteomic experiment.

PyFragMS-A Web Tool for the Investigation of the Collision-Induced Fragmentation Pathways.

Dissociation induced by the accumulation of internal energy via collisions of ions with neutral molecules is one of the most important fragmentation techniques in mass spectrometry (MS), and the identification of small singly charged molecules is based mainly on the consideration of the fragmentation spectrum. Many research studies have been dedicated to the creation of databases of experimentally measured tandem mass spectrometry (MS/MS) spectra (such as MzCloud, Metlin, etc.) and developing software for predicting MS/MS fragments in silico from the molecular structure (such as MetFrag, CFM-ID, CSI:FingerID, etc.). However, the fragmentation mechanisms and pathways are still not fully understood. One of the limiting obstacles is that protomers (positive ions protonated at different sites) produce different fragmentation spectra, and these spectra overlap in the case of the presence of different protomers. Here, we are proposing to use a combination of two powerful approaches: computing fragmentation trees that carry information of all consecutive fragmentations and consideration of the MS/MS data of isotopically labeled compounds. We have created PyFragMS-a web tool consisting of a database of annotated MS/MS spectra of isotopically labeled molecules (after H/D and/or 16O/18O exchange) and a collection of instruments for computing fragmentation trees for an arbitrary molecule. Using PyFragMS, we investigated how the site of protonation influences the fragmentation pathway for small molecules. Also, PyFragMS offers capabilities for performing database search when MS/MS data of the isotopically labeled compounds are taken into account.

Increasing the reliability of compound identification in biological samples using 16O/18O-exchange mass spectrometry.

The task of multipurpose analysis of biological samples and identification of individual compounds in them is actual for many organizations in various fields; the results of such analyses can affect lives. The most frequently used, most accurate, and highly sensitive method used for this kind of analysis is the combination of gas/liquid chromatography and high-resolution mass spectrometry. However, in some areas, it is necessary to increase the reliability of compound identification. In this paper, we present a method that combines the reaction of oxygen isotope exchange with mass spectrometry; the method allows to increase the reliability of identification of individual compounds. Oxygen isotope exchange reaction is a "selective" one, which means that not all oxygen present in the molecule can exchange, but only in certain functional groups. Thus, by the number of isotope exchanges that have occurred in this molecule, the right structural formula might be more accurately chosen. The method was tested both on pure pharmaceutical substances and on real human urine samples. In both cases, the effectiveness of the method was shown: the number of expected exchanges in known substances coincided with the experimental one, and from several possible structures of unknown substances, the correct one was chosen based on the number of isotope exchanges.

Oxygen Isotope Exchange Reaction for Untargeted LC-MS Analysis.

LC-MS is a key technique for the identification of small molecules in complex samples. Accurate mass, retention time, and fragmentation spectra from LC-MS experiments are compared to reference values for pure chemical standards. However, this information is often unavailable or insufficient, leading to an assignment to a list of candidates instead of a single hit; therefore, additional features are desired to filter candidates. One such promising feature is the number of specific functional groups of a molecule that can be counted via derivatization or isotope-exchange techniques. Hydrogen/deuterium exchange (HDX) is the most widespread implementation of isotope exchange for mass spectrometry, while oxygen 16O/18O exchange is not applied as frequently as HDX. Nevertheless, it is known that some functional groups may be selectively exchanged in 18O enriched media. Here, we propose an implementation of 16O/18O isotope exchange to highlight various functional groups. We evaluated the possibility of using the number of exchanged oxygen atoms as a descriptor to filter database candidates in untargeted LC-MS-based workflows. It was shown that 16O/18O exchange provides 62% (median, n = 45) search space reduction for a panel of drug molecules. Additionally, it was demonstrated that studying the fragmentation spectra after 16O/18O can aid in eliminating false positives and, in some cases, help to annotate fragments formed with water traces in the collisional cell.

Genetic diversity of SAD and FAD genes responsible for the fatty acid composition in flax cultivars and lines.

BACKGROUND: Flax (Linum usitatissimum L.) is grown for fiber and seed in many countries. Flax cultivars differ in the oil composition and, depending on the ratio of fatty acids, are used in pharmaceutical, food, or paint industries. It is known that genes of SAD (stearoyl-ACP desaturase) and FAD (fatty acid desaturase) families play a key role in the synthesis of fatty acids, and some alleles of these genes are associated with a certain composition of flax oil. However, data on genetic polymorphism of these genes are still insufficient. RESULTS: On the basis of the collection of the Institute for Flax (Torzhok, Russia), we formed a representative set of 84 cultivars and lines reflecting the diversity of fatty acid composition of flax oil. An approach for the determination of full-length sequences of SAD1, SAD2, FAD2A, FAD2B, FAD3A, and FAD3B genes using the Illumina platform was developed and deep sequencing of the 6 genes in 84 flax samples was performed on MiSeq. The obtained high coverage (about 400x on average) enabled accurate assessment of polymorphisms in SAD1, SAD2, FAD2A, FAD2B, FAD3A, and FAD3B genes and evaluation of cultivar/line heterogeneity. The highest level of genetic diversity was observed for FAD3A and FAD3B genes - 91 and 62 polymorphisms respectively. Correlation analysis revealed associations between particular variants in SAD and FAD genes and predominantly those fatty acids whose conversion they catalyze: SAD - stearic and oleic acids, FAD2 - oleic and linoleic acids, FAD3 - linoleic and linolenic acids. All except one low-linolenic flax cultivars/lines contained both the substitution of tryptophan to stop codon in the FAD3A gene and histidine to tyrosine substitution in the FAD3B gene, while samples with only one of these polymorphisms had medium content of linolenic acid and cultivars/lines without them were high-linolenic. CONCLUSIONS: Genetic polymorphism of SAD and FAD genes was evaluated in the collection of flax cultivars and lines with diverse oil composition, and associations between particular polymorphisms and the ratio of fatty acids were revealed. The achieved results are the basis for the development of marker-assisted selection and DNA-based certification of flax cultivars.

Machine learning to predict retention time of small molecules in nano-HPLC.

Retention time is an important parameter for identification in untargeted LC-MS screening. Precise retention time prediction facilitates the annotation process and is well known for proteomics. However, the lack of available experimental information for a long time has limited the prediction accuracy for small molecules. Recently introduced large databases for small-molecule retention times make possible reliable machine learning-based predictions for the whole diversity of compounds. Applying simple projections may expand these predictions on various LC systems and conditions. In our work, we describe a complex approach to predict retention times for nano-HPLC that includes the consequent deployment of binary and regression gradient boosting models trained on the METLIN small-molecule dataset and simple projection of the results with a small number of easily available compounds onto nano-HPLC separations. The proposed model outperforms previous attempts to use machine learning for predictions with a 46-s mean absolute error. The overall performance after transfer to nano-LC conditions is less than 155 s (10.8%) in terms of the median absolute (relative) error. To illustrate the applicability of the described approach, we successfully managed to eliminate averagely 25 to 42% of false-positives with a filter threshold derived from ROC curves. Thus, the proposed approach should be used in addition to other well-established in silico methods and their integration may broaden the range of correctly identified molecules.

Hydrogen/Deuterium and 16O/18O-Exchange Mass Spectrometry Boosting the Reliability of Compound Identification.

Accurate and reliable identification of chemical compounds is the ultimate goal of mass spectrometry analyses. Currently, identification of compounds is usually based on the measurement of the accurate mass and fragmentation spectrum, chromatographic elution time, and collisional cross section. Unfortunately, despite the growth of databases of experimentally measured MS/MS spectra (such as MzCloud and Metlin) and developing software for predicting MS/MS fragments in silico from SMILES patterns (such as MetFrag, CFM-ID, and Ms-Finder), the problem of identification is still unsolved. The major issue is that the elution time and fragmentation spectra depend considerably on the equipment used and are not the same for different LC-MS systems. It means that any additional descriptors depending only on the structure of the chemical compound will be of big help for LC-MS/MS-based omics. Our approach is based on the characterization of compounds by the number of labile hydrogen and oxygen atoms in the molecule, which can be measured using hydrogen/deuterium and 16O/18O-exchange approaches. The number of labile atoms (those from -OH, -NH, ═O, and -COOH groups) can be predicted from SMILES patterns and serves as an additional structural descriptor when performing a database search. In addition, distribution of isotope labels among MS/MS fragments can be roughly predicted by software such as MetFrag or CFM-ID. Here, we present an approach utilizing the selection of structural candidates from a database on the basis of the number of functional groups and analysis of isotope labels distribution among fragments. It was found that our approach allows reduction of the search space by a factor of 10 and considerably increases the reliability of the compound identification.

Preferential DNA photocleavage potency of Zn(II) over Ni(II) derivatives of carboxymethyl tetracationic porphyrin: the role of the mode of binding to DNA.

The porphyrin-based photosensitizers capable of binding to DNA are perspective drug candidates. Here we report the interactions with calf thymus DNA of 5,10,15,20-tetrakis(N-carboxymethyl-4-pyridinium)porphyrin (P1) and its derivatives containing Zn(II) or Ni(II) in the coordination sphere. These interactions were studied with absorption and circular dichroism spectroscopy. NiP1 and ZnP1 formed different types of complexes with DNA. NiP1 intercalated into the double helix, whereas ZnP1 bound the DNA groove. Compound P1 displayed both binding modes. The ZnP1-DNA binding constant was approximately three times smaller than the respective values for P1-DNA and NiP1-DNA complexes. Light induced degradation of the reactive oxygen species (ROS) trap 1,3-diphenylisobenzofuran in the presence of P1 and its metal derivatives revealed that NiP1 was a weaker photooxidative agent, whereas P1 and ZnP1 generated ROS to similar extents. Nevertheless, the DNA photodamaging effect of ZnP1 was the most pronounced. Illumination of the supercoiled plasmid caused single-strand DNA photocleavage in the presence of P1 and ZnP1; double strand breaks were detectable with micromolar concentrations of ZnP1. The concentration of ZnP1 required for plasmid photonicking was two times smaller than that of P1 and ~20 times lower than that for NiP1. Thus, the modes of P1, NiP1 and ZnP1 binding to DNA determine the differential photodamaging potency of these porphyrins. A greater accessibility to the solvent of the groove binder ZnP1, compared to the shielded intercalator NiP1 and the intercalated P1 molecules, allows for an efficient local generation of ROS followed by DNA photocleavage.

The role of carboxymethyl substituents in the interaction of tetracationic porphyrins with DNA.

Cationic porphyrin-based compounds capable of interacting with DNA are currently under extensive investigation as prospective anticancer and anti-infective drugs. One of the approaches to enhancing the DNA-binding affinity of these ligands is chemical modification of functional groups of the porphyrin macrocycle. We analyzed the interaction with DNA of novel derivatives containing carboxymethyl and ethoxycarbonylmethyl substituents at quaternary nitrogen atoms of pyridinium groups at the periphery of the porphyrin macrocycle. The parameters of binding of 5,10,15,20-tetrakis(N-carboxymethyl-4-pyridinium)porphyrin (P1) and 5,10,15,20-tetrakis(N-ethoxycarbonylmethyl-4-pyridinium)porphyrin (P2) to double-stranded DNA sequences of different nucleotide content were determined using optical spectroscopy. The association constant of P1 interaction with calf thymus DNA (K = 3.4 × 10(6) M(-1)) was greater than that of P2 (K = 2.8 × 10(5) M(-1)). Preferential binding of P1 to GC- rather than AT-rich oligonucleotides was detected. In contrast, P2 showed no preference for particular nucleotide content. Modes of binding of P1 and P2 to GC and AT duplexes were verified using the induced circular dichroism spectra. Molecular modeling confirmed an intercalative mode of interaction of P1 and P2 with CpG islands. The carboxyl groups of the peripheral substituent in P1 determine the specific interactions with GC-rich DNA regions, whereas ethoxycarbonylmethyl substituents disfavor binding to DNA. This study contributes to the understanding of the impact of peripheral substituents on the DNA-binding affinity of cationic porphyrins, which is important for the design of DNA-targeting drugs.