Modern analytical methods for consideration of natural biological activity

Structure-based chemical ontology improves chemometric prediction of antibacterial essential oils

Plants are valuable resources for drug discovery as they produce diverse bioactive compounds. However, the chemical diversity makes it difficult to predict the biological activity of plant extracts via conventional chemometric methods. In this research, we propose a new computational model that integrates chemical composition data with structure-based chemical ontology. For a model validation, two training datasets were prepared from literature on antibacterial essential oils to classify active/inactive oils. Random forest classifiers constructed from the data showed improved prediction performance in both test datasets. Prior feature selection using hierarchical information criterion further improved the performance. Furthermore, an antibacterial assay using a standard strain of Staphylococcus aureus revealed that the classifier correctly predicted the activity of commercially available oils with an accuracy of 83% (= 10/12). The results of this study indicate that machine learning of chemical composition data integrated with chemical ontology can be a highly efficient approach for exploring bioactive plant extracts.

Combined Micellar Liquid Chromatography Technique and QSARs Modeling in Predicting the Blood-Brain Barrier Permeation of Heterocyclic Drug-like Compounds

The quantitative structure-activity relationship (QSAR) methodology was used to predict the blood-brain permeability (log BB) for 65 synthetic heterocyclic compounds tested as promising drug candidates. The compounds were characterized by different descriptors: lipophilicity, parachor, polarizability, molecular weight, number of hydrogen bond acceptors, number of rotatable bonds, and polar surface area. Lipophilic properties of the compounds were evaluated experimentally by micellar liquid chromatography (MLC). In the experiments, sodium dodecyl sulfate (SDS) as the effluent component and the ODS-2 column were used. Using multiple linear regression and leave-one-out cross-validation, we derived the statistically significant and highly predictive quantitative structure-activity relationship models. Thus, this study provides valuable information on the expected properties of the substances that can be used as a support tool in the design of new therapeutic agents.

Synthesis and Anti-Inflammatory Activity of 1-Methylhydantoin Cinnamoyl Imides

In this study, 1-methylhydantoin cinnamic imides were synthesized from 1-methylhydantoin and trans-cinnamic acid, and their anti-inflammatory activity was investigated. The anti-inflammatory activity in vitro was evaluated by measuring the contents of NO, TNF-α and IL-1β in the supernatant of RAW264.7 cells stimulated by LPS. The cytotoxicity of 1-methylhydantoin cinnamoyl imides on RAW264.7 cells was detected using the CCK-8 method. The results showed that compounds 2 and 4 can significantly inhibit the release of NO and reduce the secretion of TNF-α and IL-1β. Compound 3 inhibited the production of TNF-α. The inhibition rate of COX was evaluated in vitro. The in vivo anti-inflammatory activities of the five compounds were evaluated by establishing an animal model of xylene ear swelling. The results showed that 1-methylhydantoin cinnamic imides could alleviate xylene-induced ear edema in mice in a dose-dependent manner. Among them, the effect of compound 5 was the most significant. Under the action of high dosage, its ear swelling inhibition rate was as high as 52.08%.

Separation Sciences in Poland

This paper describes the most significant achievements related to the creation and development of separation methods. Tswiett Nerst’s achievements and the role of such centers as Lublin, Warsaw, Gdańsk, Poznań, Łódź, Silesia, Kraków and Toruń are presented, as well as the role of leaders who created theories and methodological studies on chromatography and related techniques. The role of sample preparation methods is emphasized based on the same or similar theoretical foundations. The directions of developing these techniques in Poland today and in the future are presented.

Silver nanoparticles: Synthesis, investigation techniques, and properties

The unique silver properties, especially in the form of nanoparticles (NPs), allow to utilize them in numerous applications. For instance, Ag NPs can be utilized for the production of electronic and solar energy harvesting devices, in advanced analytical techniques (NALDI, SERS), catalysis and photocatalysis. Moreover, the Ag NPs can be useful in medicine for bioimaging, biosensing as well as in antibacterial and anticancer therapies. The Ag NPs utilization requires comprehensive knowledge about their features regarding the synthesis approaches as well as exploitation conditions. Unfortunately, a large number of scientific articles provide only restricted information according to the objects under investigation. Additionally, the results could be affected by artifacts introduced with exploited equipment, the utilized technique or sample preparation stages. However, it is rather difficult to get information about problems, which may occur during the studies. Thus, the review provides information about novel trends in the Ag NPs synthesis, among which the physical, chemical, and biological approaches can be found. Basic information about approaches for the control of critical parameters of NPs, i.e. size and shape, was also revealed. It was shown, that the reducing agent, stabilizer, the synthesis environment, including trace ions, have a direct impact on the Ag NPs properties. Further, the capabilities of modern analytical techniques for Ag NPs and nanocomposites investigations were shown, among other microscopic (optical, TEM, SEM, STEM, AFM), spectroscopic (UV-Vis, IR, Raman, NMR, electron spectroscopy, XRD), spectrometric (MALDI-TOF MS, SIMS, ICP-MS), and separation (CE, FFF, gel electrophoresis) techniques were described. The limitations and possible artifacts of the techniques were mentioned. A large number of presented techniques is a distinguishing feature, which makes the review different from others. Finally, the physicochemical and biological properties of Ag NPs were demonstrated. It was shown, that Ag NPs features are dependent on their basic parameters, such as size, shape, chemical composition, etc. At the end of the review, the modern theories of the Ag NPs toxic mechanism were shown in a way that has never been presented before. The review should be helpful for scientists in their own studies, as it can help to prepare experiments more carefully.

Mechanistic Chromatographic Column Characterization for the Analysis of Flavonoids Using Quantitative Structure-Retention Relationships Based on Density Functional Theory

This work aimed to unravel the retention mechanisms of 30 structurally different flavonoids separated on three chromatographic columns: conventional Kinetex C18 (K-C18), Kinetex F5 (K-F5), and IAM.PC.DD2. Interactions between analytes and chromatographic phases governing the retention were analyzed and mechanistically interpreted via quantum chemical descriptors as compared to the typical 'black box' approach. Statistically significant consensus genetic algorithm-partial least squares (GA-PLS) quantitative structure retention relationship (QSRR) models were built and comprehensively validated. Results showed that for the K-C18 column, hydrophobicity and solvent effects were dominating, whereas electrostatic interactions were less pronounced. Similarly, for the K-F5 column, hydrophobicity, dispersion effects, and electrostatic interactions were found to be governing the retention of flavonoids. Conversely, besides hydrophobic forces and dispersion effects, electrostatic interactions were found to be dominating the IAM.PC.DD2 retention mechanism. As such, the developed approach has a great potential for gaining insights into biological activity upon analysis of interactions between analytes and stationary phases imitating molecular targets, giving rise to an exceptional alternative to existing methods lacking exhaustive interpretations.

Predicting the Blood-Brain Barrier Permeability of New Drug-Like Compounds via HPLC with Various Stationary Phases

The permeation of the blood-brain barrier is a very important consideration for new drug candidate molecules. In this research, the reversed-phase liquid chromatography with different columns (Purosphere RP-18e, IAM.PC.DD2 and Cosmosil Cholester) was used to predict the penetration of the blood-brain barrier by 65 newly-synthesized drug-like compounds. The linear free energy relationships (LFERs) model (log BB = c + eE + sS + aA + bB + vV) was established for a training set of 23 congeneric biologically active azole compounds with known experimental log BB (BB = C_blood/C_brain) values (R² = 0.9039). The reliability and predictive potency of the model were confirmed by leave-one-out cross validation as well as leave-50%-out cross validation. Multiple linear regression (MLR) was used to develop the quantitative structure-activity relationships (QSARs) to predict the log BB values of compounds that were tested, taking into account the chromatographic lipophilicity (log k_w), polarizability and topological polar surface area. The excellent statistics of the developed MLR equations (R² > 0.8 for all columns) showed that it is possible to use the HPLC technique and retention data to produce reliable blood-brain barrier permeability models and to predict the log BB values of our pharmaceutically important molecules.

Antitussive and Anti-inflammatory Dual-active Agents Developed from Natural Product Lead Compound 1-Methylhydantoin

Natural products play an important role in drug discovery. This work employed a natural product 1-methylhydantoin as the lead compound to develop novel dual-active drugs. 1-Methylhydantoin was isolated from Oviductus Ranae, which is a traditional Chinese medicine that has been used for tussive and inflammation treatment for a long time. An in silico study screened the more active 1-methylhydantoin derivatives. Antitussive assessment indicated that the newly synthesized agent had similar bioactivity with the natural product. An anti-inflammatory model used xylene induced ear edema model. At the same dosage (100 mg/Kg), the newly prepared agent had an inhibition rate 53.18% which was much higher than that of the lead compound (22.69%). The results might be ascribed to the cyclooxygenases-1 (COX-1) and cyclooxygenases-2 (COX-2) selectivity, and the fitness of the compound, and the binding pocket. The anti-particulate matter (PM 2.5) acute pneumonia was evaluated through an in vivo model constructed by nasal instillation with PM 2.5 suspension. The results of the above models suggested that this novel agent had remarkable antitussive, anti-inflammatory, and anti-PM 2.5 acute pneumonia activities.

Immunoregulatory natural compounds in stress-induced depression: An alternative or an adjunct to conventional antidepressant therapy?

The interplay of chronic stress, neuroinflammation and altered immune reactivity has been shown to be important for the pathophysiology of brain disorders such as schizophrenia, depressive disorders and post-traumatic stress disorder. This immuno-inflammatory theory has been extensively studied in the past three decades leading to the formation of the integrative discipline of psychoneuroimmunology. Targeting of the central nervous system by conventional pharmacotherapeutic methods is mainly through modulation of neuroendocrine systems such as the dopaminergic, GABA-ergic, adrenergic and serotoninergic systems. In recent years an increasing number of both experimental and clinical studies have shown that antidepressants can affect the immune system by reducing the production of pro-inflammatory cytokines such as IL-1β, IL-6 and TNF-α. However, due to the serious adverse effects accompanying the chronic administration of psychoactive drugs there is a continuous need to produce novel therapeutics that are both potent and safe. The present review aims to summarize the current knowledge in the field of psychoneuroimmunology and to delineate the main interactions between stress, inflammation, immunity and the brain. Additionally, this paper explores the use of plant-derived molecules that display a strong anti-stress effect and simultaneously modulate the immune response as an alternative or adjuvant to classical antidepressant drugs.