000Synthesis of new α-aminophosphonates: Evaluation as anti-inflammatory agents and QSAR studies

Antinociceptive and Anti-Inflammatory Activities of Acetonic Extract from Bougainvillea x buttiana (var. Rose)

Background:Bougainvillea x buttiana is an ornamental plant with antioxidant, anti-inflammatory, and cytotoxic activities, which has been traditionally used to treat respiratory diseases. This study aimed to investigate whether the acetonic extract of Bougainvillea x buttiana var. Rose (BxbRAE-100%) has analgesic and anti-inflammatory properties and its potential action mechanisms. Methods: Analgesic and anti-inflammatory activities were evaluated using three murine pain models and two acute inflammation models. In vitro, the ability of the extract to inhibit proteolytic activity and the activities of the enzymes phospholipase A2 (PLA2) and cyclooxygenase (COX) were evaluated. In silico analysis was performed to predict the physicochemical and Absorption, distribution, metabolism, and excretion (ADME) profiles of the compounds previously identified in BxbRAE-100%. Results: In vivo BxbRAE-100% decreased the nociceptive behaviors in the writhing model, the tail immersion, and the formalin test, suggesting that the extract has the potential to relieve pain at peripheral and central levels. Additionally, topical or oral BxbRAE-100% treatment reduced dose-dependent 12-O-Tetradecanoylphorbol-13-acetate (TPA)-induced ear inflammation and carrageenan-induced paw edema, respectively. In vitro, BxbRAE-100% significantly inhibited proteolytic activity and PLA2, COX-1 and COX-2 activities. In silico, the compounds previously identified in BxbRAE-100% met Lipinski's rule of five and showed adequate ADME properties. Conclusions: These results support the use of B. x buttiana in Traditional Mexican Medicine and highlight its potential for the development of new treatments for pain and inflammation.

Characterization and relationship analysis of antioxidant and anti-inflammatory peptides in pomelo fruitlet albumin

Several macromolecules from the pomelo fruitlet (PF) have demonstrated functional potential in previous research. In this study, pomelo fruitlet albumin (PFA) was extracted from PF, its anti-inflammatory and antioxidant properties were assessed using enzyme-linked immunosorbent assays, and its capacity to clear free radicals was measured. Meanwhile, we hypothesize that the amino acid sequence may affect the anti-inflammatory and antioxidant properties, and the two may rely on common significant sites within the amino acid sequence. Therefore, we analyzed the amino acid sequence using a quantitative structure-activity relationship model to explore the connection between the antioxidant and anti-inflammatory capacities of PFA. Both capacities were closely associated with six sites within the amino acid sequence. Collectively, this study illustrates that PFA exhibits both anti-inflammatory and antioxidant capacities, with six specific sites identified as significantly affecting both activities.

A Computational Method for the Binding Mode Prediction of COX-1 and COX-2 Inhibitors: Analyzing the Union of Coxibs, Oxicams, Propionic and Acetic Acids

Among the biological targets extensively investigated to improve inflammation and chronic inflammatory conditions, cyclooxygenase enzymes (COXs) occupy a prominent position. The inhibition of these enzymes, essential for mitigating inflammatory processes, is chiefly achieved through Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). In this work, we introduce a novel method-based on computational molecular docking-that could aid in the structure-based design of new compounds or the description of the anti-inflammatory activity of already-tested compounds. For this, we used eight crystal complexes (four COX-1 and COX-2 each), and each pair had a specific NSAID: Celecoxib, Meloxicam, Ibuprofen, and Indomethacin. This selection was based on the ligand selectivity towards COX-1 or COX-2 and their binding mode. An interaction profile of each NSAID was compiled to detect the residues that are key for their binding mode, highlighting the interaction made by the Me group. Furthermore, we rigorously validated our models based on structural accuracy (RMSD < 1) and (R2 > 70) using eight NSAIDs and thirteen compounds with IC50 values for each enzyme. Therefore, this model can be used for the binding mode prediction of small and structurally rigid compounds that work as COX inhibitors or the prediction of new compounds that are designed by means of a structure-based approach.

Stability Constant and Potentiometric Sensitivity of Heavy Metal-Organic Fluorescent Compound Complexes: QSPR Models for Prediction and Design of Novel Coumarin-like Ligands

Industrial wastewater often consists of toxic chemicals and pollutants, which are extremely harmful to the environment. Heavy metals are toxic chemicals and considered one of the major hazards to the aquatic ecosystem. Analytical techniques, such as potentiometric methods, are some of the methods to detect heavy metals in wastewaters. In this work, the quantitative structure-property relationship (QSPR) was applied using a range of machine learning techniques to predict the stability constant (logβ_ML) and potentiometric sensitivity (PS_ML) of 200 ligands in complexes with the heavy metal ions Cu²⁺, Cd²⁺, and Pb²⁺. In result, the logβML models developed for four ions showed good performance with square correlation coefficients (R²) ranging from 0.80 to 1.00 for the training and 0.72 to 0.85 for the test sets. Likewise, the PSML displayed acceptable performance with an R² of 0.87 to 1.00 for the training and 0.73 to 0.95 for the test sets. By screening a virtual database of coumarin-like structures, several new ligands bearing the coumarin moiety were identified. Three of them, namely NEW02, NEW03, and NEW07, showed very good sensitivity and stability in the metal complexes. Subsequent quantum-chemical calculations, as well as physicochemical/toxicological profiling were performed to investigate their metal-binding ability and developability of the designed sensors. Finally, synthesis schemes are proposed to obtain these three ligands with major efficiency from simple resources. The three coumarins designed clearly demonstrated capability to be suitable as good florescent chemosensors towards heavy metals. Overall, the computational methods applied in this study showed a very good performance as useful tools for designing novel fluorescent probes and assessing their sensing abilities.

Theoretical exploration on structures, bonding aspects and molecular docking of α-aminophosphonate ligated copper complexes against SARS-CoV-2 proteases

Recent years have witnessed a growing interest in the biological activity of metal complexes of α-aminophosphonates. Here for the first time, a detailed DFT study on five α-aminophosphonate ligated mononuclear/dinuclear CuII complexes is reported using the dispersion corrected density functional (B3LYP-D2) method. The electronic structures spin densities, FMO analysis, energetic description of spin states, and theoretical reactivity behaviour using molecular electrostatic potential (MEP) maps of all five species are reported. All possible spin states of the dinuclear species were computed and their ground state S values were determined along with the computation of their magnetic coupling constants. NBO analysis was also performed to provide details on stabilization energies. A molecular docking study was performed for the five complexes against two SARS-CoV-2 coronavirus protein targets (PDB ID: 6LU7 and 7T9K). The docking results indicated that the mononuclear species had a higher binding affinity for the targets compared to the dinuclear species. Among the species investigated, species I showed the highest binding affinity with the SARS-CoV-2 Omicron protease. NPA charge analysis showed that the heteroatoms of model species III had a more nucleophilic nature. A comparative study was performed to observe any variations and/or correlations in properties among all species.

Some important inhibitors and mechanisms of rheumatoid arthritis

Rheumatoid arthritis is a chronic disease that seriously affects human health and quality of life, and it is one of the main causes of labor loss and disability. Many countries have listed rheumatoid arthritis as one of the national a key diseases to tackle. The pathogenesis of RA in humans is still unknown, and medical researchers believe that the pathogenesis of RA may be the result of a combination of genetic and environmental factors. RA is an incurable condition that can only be controlled and treated with conventional drugs. In this paper, the pathologic features and pathogenesis of RA were introduced, and the research progress of new anti-rheumatoid arthritis chemical drugs in recent years was reviewed.

Of Drugs and Trypanosomatids: New Tools and Knowledge to Reduce Bottlenecks in Drug Discovery

Leishmaniasis (Leishmania species), sleeping sickness (Trypanosoma brucei), and Chagas disease (Trypanosoma cruzi) are devastating and globally spread diseases caused by trypanosomatid parasites. At present, drugs for treating trypanosomatid diseases are far from ideal due to host toxicity, elevated cost, limited access, and increasing rates of drug resistance. Technological advances in parasitology, chemistry, and genomics have unlocked new possibilities for novel drug concepts and compound screening technologies that were previously inaccessible. In this perspective, we discuss current models used in drug-discovery cascades targeting trypanosomatids (from in vitro to in vivo approaches), their use and limitations in a biological context, as well as different examples of recently discovered lead compounds.