Molecular Diversity最新文献

In this paper, we present a green application for the synthesis of novel pyridine derivatives 4a-f via one-pot, multicomponent reaction (MCRs) of some aromatic aldehydes 1a-f with malononitrile (2) and N-(4-acetylphenyl)-4-methylbenzenesulfonamide (3) in the presence of ammonium acetate using ultrasonic irradiation (U.S) in an aqueous solvent H₂O:EtOH (2:1). The structures of all synthesized pyridines 4a-f were confirmed via elemental analysis and different spectroscopic techniques. This application has many advantages such as avoiding hazardous solvents, excellent yields, inexpensive, simple application, in addition to obtain pure compounds. The anti-inflammatory activity of the newly compounds was examined with the reference drug Ibuprofen. The obtained results showed that most derivatives are promising anti-inflammatory activates. Moreover, compound 4b exhibits the most anti-inflammatory activity with a percentage of inhibition with 51.67% compared with Ibuprofen 53.96%. Furthermore, the newly compounds were studied in their molecular docking simulations against the enzyme Human Cyclooxygenase-2, with Tolfenamic Acid as a reference ligand (PDB ID: 5IKT). Compound 4b demonstrated a robust binding affinity with the target protein 5ikt, evidenced by its binding affinity score of - 11.16 kcal/mol, which is the highest among the studied compounds.

A bibliometric analysis of the Cheminformatics/QSAR articles published in the present century (2000-2023) is presented based on a SCOPUS search made in October 2024 using a given set of search criteria. The obtained results of 52,415 documents against the specific query are analyzed based on the number of documents per year, contributions of different countries and Institutes in Cheminformatics/QSAR publications, the contributions of researchers based on the number of documents, appearance in the top-cited articles, h-index, composite c-score (ns), and the newly introduced q-score. Finally, a list of the top 50 Cheminformatics/QSAR researchers is presented. An analysis is also made for the content of the top-cited articles during the period 2000-2023 in comparison to those before 2000 to capture the trend of changes in the Cheminformatics/QSAR research. The limiting factors of any bibliometric analysis are also briefly presented.

The translocator protein 18 kDa (TSPO) is a crucial external mitochondrial protein involved in cholesterol translocation, which is essential for steroid production. As a primary marker of neuroinflammation, TSPO has been implicated in the development and progression of various neurodegenerative and neuropsychiatric disorders. This review highlights the structural diversity of TSPO ligands, many of which have undergone modifications from selective central benzodiazepine receptor (CBR) ligands to enhance their affinity for TSPO. The paper discusses the significant advancements in the design of these ligands, emphasizing their binding efficacy and specificity. Additionally, it provides an update on the progress of several TSPO ligands that have advanced to clinical trials. The review aims to elucidate the structure-activity relationships (SAR) that govern the interaction between TSPO and its ligands, thereby offering insights into the development of new therapeutic agents targeting TSPO for the treatment of neuroinflammatory conditions. Overall, this work provided an update on previous finding and serves as a valuable resource for researchers in the field.

In this study, one-pot multicomponent reactions of novel chromeno[2,3-c]pyrazole derivatives (1-14) were performed using an AlCl₃ catalyst via cyclisation. Various spectral and chromatographic techniques were used to elucidate the structure of the synthesised derivatives (1-14). The synthesised compounds were then inspected for their antibacterial, antioxidant, and tyrosinase inhibition activities. An in silico screening approach was also employed to identify highly potent derivatives. Besides, we utilised density functional theory (DFT) with the B3LYP/6-31G⁺ (d, p) basis set to optimise the newly modified derivatives. This approach was used to calculate various properties, including electron density, electrostatic potential map, interaction strength, frontier molecular orbital energy, and reactivity characteristics. To examine the binding affinity, modes, and stability of the protein-drug complex, molecular docking with the 2Y9X protein structure were employed. The findings from DFT computations, along with physicochemical information and molecular docking binding affinity, showed promising results than standard and low active compound 1. The absorption, metabolism, and cytotoxic characteristics of all the novel derivatives were investigated in the ADMET prediction. Our findings could prove valuable in developing novel drugs for medicinal and pharmaceutical fields.

To overcome T790M mutation, a novel series of 4-indazolypyrimidine derivatives were developed as novel EGFR inhibitors employing a scaffold hopping drug design strategy. The biological activities of the target compounds were evaluated against two tumor cell lines (A431 and NCI-H1975), normal cell 2BS and EGFR^T790M/L858R kinase. The results indicated that the majority of the compounds exhibited promising antitumor activity and low toxicity. Specifically, compounds 4e and 4s displayed the highest efficacy, with IC₅₀ values of 0.55 μM and 0.47 μM, respectively. Moreover, compounds 4e and 4s demonstrated exceptional activity against EGFR^T790M/L858R, with IC₅₀ values of 12.04 and 28.79 nM. Additionally, further studies revealed that compounds 4e and 4s could induce apoptosis in NCI-H1975 cells and arrest the cells in the G2/M phase. Molecular docking studies revealed that compounds 4e and 4s could interact closely with EGFR. These findings lay the groundwork for further investigation of compounds 4e and 4s as potential EGFR inhibitors.

Hydrophobicity is crucial for the interaction between amphipathic antimicrobial peptides and microbial pathogens. However, it is difficult to fully understand the impact of this factor because the biological functions are also influenced by other structural properties, including peptide length, net charge, hydrophilicity, secondary structure, and hydrophobic moment. This study compares three natural antimicrobial peptides-mastoparan C, mastoparan-AF, and mastoparan L-where hydrophobicity varies but other structural features remain nearly identical. Mastoparan C, the most hydrophobic peptide, displays the highest helical content and hemolytic activity, whereas mastoparan-AF, with slightly lower hydrophobicity, demonstrates superior selectivity. In contrast, mastoparan L, the least hydrophobic peptide, exhibits the weakest antimicrobial potency and lowest hemolytic activity, despite showing the least self-assembly. Overall, this study suggests that optimal hydrophobicity, rather than the highest value, enhances antimicrobial efficacy while minimizing hemolytic activity.

HMGB1 mediated signalling pathway plays an important role in acute injury and fibrosis in lung tissues. Glycyrrhizic acid (GL) is a HMGB1 inhibitor, and its aglycone (glycyrrhetinic acid, GA) is the major pharmacophore and plays the main role during binding to HMGB1. To improve selectivity for these lung diseases, a series of novel glycyrrhetinic acid glycosides targeting mannose acceptors in the respiratory tract and lung tissues were synthesised, and their biological activities were evaluated in vitro and in vivo. For normal lung cell lines WI-38 and Beas-2B, all the compounds but c6 showed reduced cytotoxicity vs the positive controls (GA and GL), IC₅₀ values were > 800 µM. For three cancer cells, c1 exhibited high selectivity for lung cancer cells A549. In the inflammation assays, compound c1 displayed the strongest activity of NO inhibition, and c4 was next; both them not only down-regulated the expression levels of IL-1β and TNF-α in RAW264.7 cells, but also decreased the levels of TNF-α, IL-1β, HMGB1, RAGE and ROS in A549 cells in a dose-dependent manner. Noteworthy, compound c1 of 50 μM reduced the levels of HMGB1 and RAGE to 38.4 and 37.0% of the LPS group, and it showed much higher binding affinity with HMGB1 than GL, which confirmed by molecular docking; in addition, c1 also inhibited the deposition of α-SMA and Col-1 proteins in TGF-β1-activated A549 cells. In the bleomycin-induced lung fibrosis mouse model, c1 decreased fibrous protein production and deposition in the lung tissues; at a 30 mg/kg dose, it reduced the levels of α-SMA and Col-1 to 48.12 and 56.37% of the BLM group, respectively. The pharmacokinetics tests showed c1 relative distribution rate in lung tissue (at 1 h, 18.86%; at 2 h, 12.80%) is much higher than that of GA (at 1 h, 2.8%; at 2 h, 1.9%). These results show compound c1 is likely to be a candidate for acute lung injury and pulmonary fibrosis.

A series of chalcone derivatives containing 1,2,4-triazole and pyridine were designed and synthesized, and their antiviral activities against tobacco mosaic virus (TMV) were evaluated. Notably, S7 (EC₅₀ = 89.7 μg/mL) exhibited excellent curative activity against the TMV, which was superior to that of ningnanmycin (NNM: EC₅₀ = 201.7 μg/mL). Molecular docking showed that S7 exhibited satisfactory affinities for the TMV coat protein (TMV-CP), with four strong conventional hydrogen bonds with amino acid residues. Further, microscale thermophoresis (MST) showed that S7 (Kd = 0.5340 ± 0.2233 μmol/L) bound more strongly to TMV-CP than NNM (Kd = 5.1186 ± 1.9568 μmol/L). The results of chlorophyll content, malondialdehyde (MDA) content, and biological enzyme activity confirmed that S7 enhanced the disease resistance of tobacco plants by affecting the change of chlorophyll content, interfering with plant lipid peroxidation, and enhancing SOD activity in plants, respectively.

In the past, mechanochemical approaches in organic synthesis were largely overlooked, but their perception within the synthetic community has shifted in recent years, marking a trend toward becoming mainstream. Mechanochemical multicomponent organic synthesis has garnered significant interest from both the academic and industrial chemical sectors. The efficiency and environmental friendliness of procedures conducted through mechanical activation have established mechanical procedures as prominent green techniques. Notably, utilizing solid starting materials under mechanochemical conditions empowers the development of novel multicomponent reactions that are often unfeasible in traditional solution-based processes. This capability not only enhances the diversity of accessible organic compounds but also sparks new avenues for innovative synthetic strategies. This approach facilitates the effective fulfillment of sustainable chemistry goals. In this context, we emphasize the major progress and advancements in mechanochemical multicomponent reactions from 2017 to 2024. This article covers the foremost multicomponent mechanosynthesis for developing organic molecules through carbon-carbon and carbon-heteroatom coupling reactions and multicomponent mechanosynthesis for monocyclic and fused heterocycles.

The aberrant expression of proviral integration site for Moloney murine leukemia virus (PIM) kinases is closely related to various tumors and chemotherapy resistance, making them attractive targets for cancer therapy. However, due to the extremely high homology among the three PIM isoforms (PIM1, PIM2, PIM3) and the limited availability of existing bioactivity data, screening and designing selective PIM inhibitors remain a daunting challenge. To address this issue, this study constructed a multitask regression model that can simultaneously predict the half-maximal inhibitory concentration (IC₅₀ values). The model utilizes an attention mechanism to capture effects within local atomic groups and the interactions between different groups of atoms. Through weight sharing, the model enhances the accuracy of predicting PIM3 inhibitors by leveraging the rich and highly correlated data from PIM1 and PIM2 isoforms. Additionally, visualizing the weights of nodes (atoms in the molecule) in the model helps us to intuitively understand the relationship between molecular features and prediction outcomes, thereby enhancing the interpretability of the model. In summary, this work provides new insights and methods for performing activity prediction tasks for multiple similar targets in low-data scenarios.