Microbe cultivation guidelines to optimize rhamnolipid applications.

In the growing landscape of interest in natural surfactants, selecting the appropriate one for specific applications remains challenging. The extensive, yet often unsystematized, knowledge of microbial surfactants, predominantly represented by rhamnolipids (RLs), typically does not translate beyond the conditions presented in scientific publications. This limitation stems from the numerous variables and their interdependencies that characterize microbial surfactant production. We hypothesized that a computational recipe for biosynthesizing RLs with targeted applicational properties could be developed from existing literature and experimental data. We amassed literature data on RL biosynthesis and micellar solubilization and augmented it with our experimental results on the solubilization of triglycerides (TGs), a topic underrepresented in current literature. Utilizing this data, we constructed mathematical models that can predict RL characteristics and solubilization efficiency, represented as logPRL = f(carbon and nitrogen source, parameters of biosynthesis) and logMSR = f(solubilizate, rhamnolipid (e.g. logPRL), parameters of solubilization), respectively. The models, characterized by robust R2 values of respectively 0.581-0.997 and 0.804, enabled the ranking of descriptors based on their significance and impact-positive or negative-on the predicted values. These models have been translated into ready-to-use calculators, tools designed to streamline the selection process for identifying a biosurfactant optimally suited for intended applications.

Keratinocyte-derived small extracellular vesicles supply antigens for CD1a-resticted T cells and promote their type 2 bias in the context of filaggrin insufficiency.

Introduction: Exosome-enriched small extracellular vesicles (sEVs) are nanosized organelles known to participate in long distance communication between cells, including in the skin. Atopic dermatitis (AD) is a chronic inflammatory skin disease for which filaggrin (FLG) gene mutations are the strongest genetic risk factor. Filaggrin insufficiency affects multiple cellular function, but it is unclear if sEV-mediated cellular communication originating from the affected keratinocytes is also altered, and if this influences peptide and lipid antigen presentation to T cells in the skin. Methods: Available mRNA and protein expression datasets from filaggrin-insufficient keratinocytes (shFLG), organotypic models and AD skin were used for gene ontology analysis with FunRich tool. sEVs secreted by shFLG and control shC cells were isolated from conditioned media by differential centrifugation. Mass spectrometry was carried out for lipidomic and proteomic profiling of the cells and sEVs. T cell responses to protein, peptide, CD1a lipid antigens, as well as phospholipase A2-digested or intact sEVs were measured by ELISpot and ELISA. Results: Data analysis revealed extensive remodeling of the sEV compartment in filaggrin insufficient keratinocytes, 3D models and the AD skin. Lipidomic profiles of shFLGsEV showed a reduction in the long chain (LCFAs) and polyunsaturated fatty acids (PUFAs; permissive CD1a ligands) and increased content of the bulky headgroup sphingolipids (non-permissive ligands). This resulted in a reduction of CD1a-mediated interferon-γ T cell responses to the lipids liberated from shFLG-generated sEVs in comparison to those induced by sEVs from control cells, and an increase in interleukin 13 secretion. The altered sEV lipidome reflected a generalized alteration in the cellular lipidome in filaggrin-insufficient cells and the skin of AD patients, resulting from a downregulation of key enzymes implicated in fatty acid elongation and desaturation, i.e., enzymes of the ACSL, ELOVL and FADS family. Discussion: We determined that sEVs constitute a source of antigens suitable for CD1a-mediated presentation to T cells. Lipids enclosed within the sEVs secreted on the background of filaggrin insufficiency contribute to allergic inflammation by reducing type 1 responses and inducing a type 2 bias from CD1a-restricted T cells, thus likely perpetuating allergic inflammation in the skin.

Modification of gradient HPLC method for determination of small molecules' affinity to human serum albumin under column safety conditions: Robustness and chemometrics study.

In the early stages of drug discovery, beyond the biological activity screening, determining the physicochemical properties that affect the distribution of molecules in the human body is an essential step. Plasma protein binding (PPB) is one of the most important investigated endpoints. Nevertheless, the methodology for measuring %PPB is significantly less popular and standardized than other physicochemical properties, like lipophilicity. Here, we proposed how to modify protocols presented by Valko into column safety conditions and evaluated their robustness using fractional factorial design. For robustness testing, four factors were selected: column temperature, mobile phase flow rate, maximum isopropanol concentration in the mobile phase, and buffer pH. Elaborate methods have been applied for the analysis of HSA affinity for three groups of antibiotic-oriented substances that vary in chemical structure: fluoroquinolones, sulfonamides, and tetrazole derivatives. Furthermore, based on the reversed-phase chromatography the workflow of pilot studies was proposed to select molecules that have high affinity to HSA and can not be eluted from the HSA column using the concentration of organic modifier recommended by the column manufacturer.

Characterization of GM3 Gangliosides in Human Milk throughout Lactation: Insights from the Analysis with the Use of Reversed-Phase Liquid Chromatography Coupled to Quadrupole Time-Of-Flight Mass Spectrometry.

Gangliosides are complex lipids found in human milk that play important structural and biological functions. In this study, we utilized reversed-phase liquid chromatography coupled to quadrupole time-of-flight mass spectrometry to evaluate the molecular distribution of GM3 in human milk samples collected at distinct lactation stages, ranging from colostrum to advanced lactation samples. Throughout lactation, GM3 d40:1 emerged as the most abundant GM3 species, except in colostrum, where GM3 d42:2 prevailed. The relative content of GM3 species containing very long N-fatty acyl (N-FA) substituents with >22 carbon atoms decreased, while the content of GM3 species containing 14:0, 18:0, 18:1, and 20:0 N-FA substituents increased in the later months of lactation. These findings highlight the divergence of GM3 profiles across the lactation period. Moreover, considerable interindividual variance was observed among the analyzed samples. The assessment of the GM3 profiles contributes to our understanding of the dynamic composition of human milk.

Pre-analytical aspects in metabolomics of human biofluids - sample collection, handling, transport, and storage.

Metabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the study data. The study design process should include a careful selection of conditions for each experimental step, from sample collection to data analysis. The pre-analytical variability that can introduce bias to the subsequent analytical process, decrease the outcome reliability, and confuse the final results of the metabolomics research, should also be considered. Herein, we provide key information regarding the pre-analytical variables affecting the metabolomics studies of biological fluids that are the most desirable type of biological samples. Our work offers a practical review that can serve and guide metabolomics pre-analytical design. It indicates pre-analytical factors, which can introduce artificial data variation and should be identified and understood during experimental design (through literature overview or analytical experiments).

IFI16 Impacts Metabolic Reprogramming during Human Cytomegalovirus Infection.

Cellular lipid metabolism plays a pivotal role in human cytomegalovirus (HCMV) infection, as increased lipogenesis in HCMV-infected cells favors the envelopment of newly synthesized viral particles. As all cells are equipped with restriction factors (RFs) able to exert a protective effect against invading pathogens, we asked whether a similar defense mechanism would also be in place to preserve the metabolic compartment from HCMV infection. Here, we show that gamma interferon (IFN-γ)-inducible protein 16 (IFI16), an RF able to block HCMV DNA synthesis, can also counteract HCMV-mediated metabolic reprogramming in infected primary human foreskin fibroblasts (HFFs), thereby limiting virion infectivity. Specifically, we find that IFI16 downregulates the transcriptional activation of the glucose transporter 4 (GLUT4) through cooperation with the carbohydrate-response element-binding protein (ChREBP), thereby reducing HCMV-induced transcription of lipogenic enzymes. The resulting decrease in glucose uptake and consumption leads to diminished lipid synthesis, which ultimately curbs the de novo formation of enveloped viral particles in infected HFFs. Consistently, untargeted lipidomic analysis shows enhanced cholesteryl ester levels in IFI16 KO versus wild-type (WT) HFFs. Overall, our data unveil a new role of IFI16 in the regulation of glucose and lipid metabolism upon HCMV replication and uncover new potential targets for the development of novel antiviral therapies. IMPORTANCE Human cytomegalovirus (HCMV) gathers all the substrates and enzymes necessary for the assembly of new virions from its host cell. For instance, HCMV is known to induce cellular metabolism of infected cells to favor virion assembly. Cells are, however, equipped with a first-line defense represented by restriction factors (RFs), which after sensing viral DNA can trigger innate and adaptive responses, thereby blocking HCMV replication. One such RF is IFN-γ-inducible protein 16 (IFI16), which we have shown to downregulate viral replication in human fibroblasts. Thus, we asked whether IFI16 would also play a role in preserving cellular metabolism upon HCMV infection. Our findings highlight an unprecedented role of IFI16 in opposing the metabolic changes elicited by HCMV, thus revealing new promising targets for antiviral therapy.

A method for a comprehensive lipidomic analysis of flaxseed (Linum usitatissimum) with the use of LC-Q-TOF-MS and dispersive micro-solid-phase (µDSPE) extraction.

Flaxseed (FS) is one of the richest sources of α-linolenic acid oil and lignans, and it is suggested that the consumption of flaxseed may contribute to the prevention of certain chronic diseases such as many types of cancer, diabetes, cardiovascular diseases and cerebrovascular stroke. Here, we demonstrate a new method for comprehensive FS lipidome profiling with the use of LC-Q-TOF-MS and dispersive micro-solid-phase extraction. The effects of stationary phase amount, flaxseed amount and different organic solvents for non-polar lipid elution on the FS lipidome coverage were investigated. The developed and validated protocol allowed for improved monitoring of both polar and non-polar lipids simultaneously, overcoming the challenge of low- and high-abundance lipid species. Furthermore, the method was applied to characterize a set of brown flaxseed and yellow flaxseed samples, as well as flaxseed meal.

The Influence of Storage on Human Milk Lipidome Stability for Lipidomic Studies.

Human milk (HM) lipidome stability during storage is crucial in lipidomic studies to avoid misinterpretations. Facing the lack of comprehensive work on the HM lipidome stability, we performed a study on a potential alteration in the lipid profiles of HM samples stored under different conditions. An untargeted LC-Q-TOF-MS-based approach was applied to study the influence of storage conditions as well as the interaction of the storage temperature and time on HM lipid profiles. The samples were stored for 4-84 days at temperatures in the range from 4 to -80 °C and also were exposed to up to three freeze-thaw cycles. The results showed that the storage at 4 °C for just 4 days as well as being subjected to three freeze-thaw cycles can lead to a change in the content of lipids. The observed differences in levels of some lipid species in samples stored at -20 °C in comparison to the concentration level of those lipids in samples stored at -80 °C were not statistically significant, and inter-individual variance regardless of sample storage condition was maintained. The storage of HM samples at -20 °C for up to 3 weeks and -80 °C for up to 12 weeks ensures sample lipidome stability.

Untargeted Lipidomics Analysis of the Cyanobacterium Synechocystis sp. PCC 6803: Lipid Composition Variation in Response to Alternative Cultivation Setups and to Gene Deletion.

Cyanobacteria play an important role in several ecological environments, and they are widely accepted to be the ancestors of chloroplasts in modern plants and green algae. Cyanobacteria have become attractive models for metabolic engineering, with the goal of exploring them as microbial cell factories. However, the study of cyanobacterial lipids' composition and variation, and the assessment of the lipids' functional and structural roles have been largely overlooked. Here, we aimed at expanding the cyanobacterial lipidomic analytical pipeline by using an untargeted lipidomics approach. Thus, the lipid composition variation of the model cyanobacterium Synechocystis sp. PCC 6803 was investigated in response to both alternative cultivation setups and gene deletion. This approach allowed for detecting differences in total lipid content, alterations in fatty-acid unsaturation level, and adjustments of specific lipid species among the identified lipid classes. The employed method also revealed that the cultivation setup tested in this work induced a deeper alteration of the cyanobacterial cell lipidome than the deletion of a gene that results in a dramatic increase in the release of lipid-rich outer membrane vesicles. This study further highlights how growth conditions must be carefully selected when cyanobacteria are to be engineered and/or scaled-up for lipid or fatty acids production.

Comparative Lipidomic Study of Human Milk from Different Lactation Stages and Milk Formulas.

In this report, we present a detailed comparison of the lipid composition of human milk (HM) and formula milk (FM) targeting different lactation stages and infant age range. We studied HM samples collected from 26 Polish mothers from colostrum to 19 months of lactation, along with FM from seven brands available on the Polish market (infant formula, follow-on formula and growing-up formula). Lipid extracts were analysed using liquid chromatography coupled to high-resolution mass spectrometry (LC-Q-TOF-MS). We found that the lipid composition of FM deviates significantly from the HM lipid profile in terms of qualitative and quantitative differences. FM had contrasting lipid profiles mostly across brands and accordingly to the type of fat added but not specific to the target age range. The individual differences were dominant in HM; however, differences according to the lactation stage were also observed, especially between colostrum and HM collected in other lactation stages. Biologically and nutritionally important lipids, such as long-chain polyunsaturated fatty acids (LC-PUFAs) containing lipid species, sphingomyelines or ether analogues of glycerophosphoethanoloamines were detected in HM collected in all studied lactation stages. The observed differences concerned all the major HM lipid classes and highlight the importance of the detailed compositional studies of both HM and FM.

Nuclear Magnetic Resonance Metabolomics Reveals Qualitative and Quantitative Differences in the Composition of Human Breast Milk and Milk Formulas.

Commercial formula milk (FM) constitutes the best alternative to fulfill the nutritional requirements of infants when breastfeeding is precluded. Here, we present the comparative study of polar metabolite composition of human breast milk (HBM) and seven different brands of FM by nuclear magnetic resonance spectroscopy. The results of the multivariate data analysis exposed qualitative and quantitative differences between HBM and FM composition as well as within FM of various brands and in HBM itself (between individual mothers and lactation period). Several metabolites were found exclusively in HBM and FM. Statistically significant higher levels of isoleucine and methionine in their free form were detected in FM samples based on caprine milk, while FM samples based on bovine milk showed a higher level of glucose and galactose in comparison to HBM. The results suggest that the amelioration of FM formulation is imperative to better mimic the composition of minor nutrients in HBM.

A new dilution-enrichment sample preparation strategy for expanded metabolome monitoring of human breast milk that overcomes the simultaneous presence of low- and high-abundance lipid species.

The complex nature of human breast milk (HBM) makes samples difficult to analyze, requiring several extraction techniques and analytical platforms to obtain high metabolome coverage. In this work, we combined liquid-liquid extraction (LLE) and solid-phase extraction (SPE) techniques to prepare HBM samples to overcome the challenge of low- and high-abundance lipid species, enabling the semiquantitative analysis of total HBM lipids in one liquid chromatography-mass spectrometry (LC-MS) run. A nonorganic fraction obtained during the LLE step was used to analyze small polar metabolites. This analytical approach allows extensive metabolome coverage, especially for low-abundance glycerophospholipids and sphingolipids. The method was applied to monitor short-term metabolome changes in HBM composition within individual mothers and the results showed variable metabolite composition patterns. Simultaneous detection of high-abundance glycerolipids and low-abundance but not less significant phospholipids in one LC-MS run saves time, decreases cost, and enables comprehensive insight into the dynamics of HBM composition.

Chemistry of Human Breast Milk-A Comprehensive Review of the Composition and Role of Milk Metabolites in Child Development.

Early nutrition has an enormous influence on a child's physiological function, immune system maturation, and cognitive development. Human breast milk (HBM) is recognized as the gold standard for human infant nutrition. According to a WHO report, breastfeeding is considered as an unequaled way of providing ideal food to the infant, which is required for his healthy growth and development. HBM contains various macronutrients (carbohydrates, proteins, lipids, and vitamins) as well as numerous bioactive compounds and interactive elements (growth factors, hormones, cytokines, chemokines, and antimicrobial compounds. The aim of this review is to summarize and discuss the current knowledge about metabolites, which are the least understood components of HBM, and their potential role in infant development. We focus on small metabolites (<1500 Da) and characterize the chemical structure and biological function of polar metabolites such as human milk oligosaccharides, nonprotein molecules containing nitrogen (creatine, amino acids, nucleotides, polyamines), and nonpolar lipids. We believe that this manuscript will provide a comprehensive insight into a HBM metabolite composition, chemical structure, and their role in a child's early life nutrition.

Rapid Characterization of the Human Breast Milk Lipidome Using a Solid-Phase Microextraction and Liquid Chromatography-Mass Spectrometry-Based Approach.

Human breast milk (HBM) is a biofluid consisting of various biomolecules such as proteins, lipids, carbohydrates, minerals and bioactive substances. Due to its unique and complex composition, HBM provides not only nutritional components required for the growth of the infant, but also additional protection against infections. Global insight into the composition of HBM is crucial to understanding the health benefits infants receive from breastfeeding and could be used to improve the composition of milk formula for babies that cannot be breastfed. To improve global profiling of the HBM lipidome, a new analytical approach based on solid-phase microextraction (SPME) and liquid chromatography-mass spectrometry (LC-MS) was developed. The new extraction method allows for the rapid and simple extraction of a broad range of lipids directly from HBM samples. Moreover, the optimized two-step lipid extraction protocol ensures high lipidome coverage without using toxic solvents such as chloroform. The use of liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) and an automated search of a lipid database allows comprehensive identification of the lipids contained in HBM. The demonstrated analytical approach based on SPME sample preparation and LC-Q-TOF-MS is rapid, free of toxic solvents, and suited for the qualitative analysis of the HBM lipid composition.

Forced Degradation Studies of Ivabradine and In Silico Toxicology Predictions for Its New Designated Impurities.

All activities should aim to eliminate genotoxic impurities and/or protect the API against degradation. There is a necessity to monitor impurities from all classification groups, hence ivabradine forced degradation studies were performed. Ivabradine was proved to be quite durable active substance, but still new and with insufficient stability data. Increased temperature, acid, base, oxidation reagents and light were found to cause its degradation. Degradation products were determined with the usage of HPLC equipped with Q-TOF-MS detector. Calculations of pharmacological and toxicological properties were performed for six identified degradation products. Target prediction algorithm was applied on the basis of Hyperpolarization-activated cyclic nucleotide-gated cation channels, as well as more general parameters like logP and aqueous solubility. Ames test and five cytochromes activities were calculated for toxicity assessment for selected degradation products. Pharmacological activity of photodegradation product (UV4), which is known as active metabolite, was qualified and identified. Two other degradation compounds (Ox1 and N1), which were formed during degradation process, were found to be pharmacologically active.

Untargeted Lipidomics Reveals Differences in the Lipid Pattern among Clinical Isolates of Staphylococcus aureus Resistant and Sensitive to Antibiotics.

Staphylococcus aureus resistance to antibiotics is a significant clinical problem worldwide. In this study, an untargeted lipidomics approach was used to compare the lipid fingerprints of S. aureus clinical isolates that are resistant and sensitive to antibiotics. High-performance liquid chromatography coupled with time-of-flight mass spectrometry was employed to rapidly and comprehensively analyze bacterial lipids. Chemometric and statistical analyses of the obtained lipid fingerprints revealed variations in several lipid groups between S. aureus strains resistant and sensitive to tested antibiotics including methicillin, gentamicin, ciprofloxacin, erythromycin, and fusidic acid. The levels of identified monoglycosyldiacylglycerol, phosphatidylglycerol, and diglycosyldiacylglycerol lipid groups were found to be upregulated in antibiotic-resistant S. aureus strains, whereas the levels of diacylglycerol lipid groups were downregulated. Differences in the lipid patterns between sensitive and resistant S. aureus strains suggest that antibiotic susceptibility may be associated with the lipid composition of bacterial cells. The lipids that were found to significantly differ between antibiotic-resistant and antibiotic-sensitive clinical isolates are involved in the biosynthesis of major S. aureus membrane lipids and lipoteichoic acid. This study indicates that S. aureus lipid biosynthesis pathways should be explored further to better understand the mechanism of antibiotic resistance in S. aureus strains.

Photoinactivation of Staphylococcus aureus using protoporphyrin IX: the role of haem-regulated transporter HrtA.

Light- and photosensitiser-based antimicrobial photodynamic therapy is a very promising approach to the control of microbial infections. How the phenotypic features of a microorganism affect its response to photosensitiser-based photokilling represents an area of substantial research interest. To understand the mechanisms governing the phenomenon of a strain-dependent response to photodynamic inactivation (PDI), we analysed the possible role of the membrane-located haem transporter HrtA in Staphylococcus aureus. We used a S. aureus strains with an inactivated component of the haem-regulated transporter, HrtA, along with its wild-type counterpart to determine differences in PDI outcome and photosensitiser uptake between the studied isogenic strains. We observed that a lack of HrtA protein potentiates the phototoxic effect towards S. aureus but only when extracellular protoporphyrin IX is used. The observed effect may depend on the function of the HrtA transporter but is likely to result from changed membrane properties following the absence of the protein in the membrane. This indicates that disturbing the membrane properties is an attractive method for improving the efficacy of the photodynamic inactivation of microorganisms.

Prediction of overall in vitro microsomal stability of drug candidates based on molecular modeling and support vector machines. Case study of novel arylpiperazines derivatives.

Other than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model and predict metabolic stability quantitatively is still lacking. This study proposes a workflow for developing quantitative metabolic stability-structure relationships, taking a set of 30 arylpiperazine derivatives as an example. The metabolic stability of the compounds was assessed in in vitro incubations in the presence of human liver microsomes and NADPH and subsequently quantified by liquid chromatography-mass spectrometry (LC-MS). Density functional theory (DFT) calculations were used to obtain 30 models of the molecules, and Dragon software served as a source of structure-based molecular descriptors. For modeling structure-metabolic stability relationships, Support Vector Machines (SVM), a non-linear machine learning technique, were found to be more effective than a regression technique, based on the validation parameters obtained. Moreover, for the first time, general sites of metabolism for arylpiperazines bearing the 4-aryl-2H-pyrido[1,2-c]pyrimidine-1,3-dione system were defined by analysis of Q-TOF-MS/MS spectra. The results indicated that the application of one of the most advanced chemometric techniques combined with a simple and quick in vitro procedure and LC-MS analysis provides a novel and valuable tool for predicting metabolic half-life values. Given the reduced time and simplicity of analysis, together with the accuracy of the predictions obtained, this is a valid approach for predicting metabolic stability using structural data. The approach presented provides a novel, comprehensive and reliable tool for investigating metabolic stability, factors that affect it, and the proposed structures of metabolites at the same time. The performance of the DFT-SVM-based approach provides an opportunity to implement it in a standard drug development pipeline.

Comprehensive methodology for Staphylococcus aureus lipidomics by liquid chromatography and quadrupole time-of-flight mass spectrometry.

Staphylococcus aureus is a common pathogen known to cause relatively minor infections as well as severe disorders in humans. Although there is fair amount of published data concerning various aspects of its biology, epidemiology, genetics, etc., there is still a scarce amount of data presenting reliable and thorough investigations regarding high-throughput analysis of total S. aureus lipid content. Therefore, the aim of this study was to develop an analytical method that in combination with advanced chemometric tools enables comprehensive lipidomic analysis of S. aureus cells. The newly developed method uses high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) to directly examine extracted lipids and further identify them within a newly developed novel S. aureus lipids database. High coverage of the S. aureus lipidome was obtained by simultaneous bacterial cell lysis and liquid-liquid extraction. The combination of three techniques enabled the analysis of the major membrane lipid classes of S. aureus: separation of the lipid extract in reversed-phase mode, Q-TOF-MS detection in positive ion mode, and lipid database mining. The developed lipidomic approach is also a powerful tool that allows one to assess the lipid content of S. aureus cells in a comparative manner between strains characterized by different phenotypic features as exemplified here by their various sensitivities toward antibiotics.

Mass spectrometry based identification of geometric isomers during metabolic stability study of a new cytotoxic sulfonamide derivatives supported by quantitative structure-retention relationships.

A set of 15 new sulphonamide derivatives, presenting antitumor activity have been subjected to a metabolic stability study. The results showed that besides products of biotransformation, some additional peaks occurred in chromatograms. Tandem mass spectrometry revealed the same mass and fragmentation pathway, suggesting that geometric isomerization occurred. Thus, to support this hypothesis, quantitative structure-retention relationships were applied. Human liver microsomes were used as an in vitro model of metabolism. The biotransformation reactions were tracked by liquid chromatography assay and additionally, fragmentation mass spectra were recorded. In silico molecular modeling at a semi-empirical level was conducted as a starting point for molecular descriptor calculations. A quantitative structure-retention relationship model was built applying multiple linear regression based on selected three-dimensional descriptors. The studied compounds revealed high metabolic stability, with a tendency to form hydroxylated biotransformation products. However, significant chemical instability in conditions simulating human body fluids was noticed. According to literature and MS data geometrical isomerization was suggested. The developed in sillico model was able to describe the relationship between the geometry of isomer pairs and their chromatographic retention properties, thus it supported the hypothesis that the observed pairs of peaks are most likely geometric isomers. However, extensive structural investigations are needed to fully identify isomers' geometry. An effort to describe MS fragmentation pathways of novel chemical structures is often not enough to propose structures of potent metabolites and products of other chemical reactions that can be observed in compound solutions at early drug discovery studies. The results indicate that the relatively non-expensive and not time- and labor-consuming in sillico approach could be a good supportive tool assisting the identification of cis-trans isomers based on retention data. This methodology can be helpful during the structural identification of biotransformation and degradation products of new chemical entities--potential new drugs.