Novel chiral matrine derivatives as potential antitumor agents: Design, synthesis and biological evaluation.

Since the thalidomide incident, research on chiral drugs has escalated immensely. Differences in drug configuration can lead to significant variations in therapeutic efficacy. Matrine, a natural product esteemed for its low toxicity and high water solubility, has garnered significant attention in research endeavors. Nonetheless, its precise target has proven elusive. In this study, we designed and synthesized a novel chiral matrine derivative. Their cytotoxicity against three types of tumor cells was assessed. Comparing the newly synthesized derivatives to the parent matrine, most compounds exhibited significantly enhanced inhibitory effects on cancer cells. Among them, Q12 exhibited the highest activity, with IC50 values of 8.31 µM against rat glioma cells C6, 6.3 µM against human liver cancer cells HepG2 and 7.14 µM against human gastric cancer cells HGC-27, meanwhile showing low toxicity. Based on IC50 values, we constructed a preliminary structure-activity relationship (SAR). Compound Q12 significantly suppressed the cloning and migration of HepG2 cells. Further mechanistic studies indicated that Q12 inhibited Topo I in HepG2 cells, leading to DNA damage, induction of G0/G1 cell cycle arrest and ultimately causing apoptosis. The molecular docking experiments provided a rational binding mode of Q12 with the Topo I-DNA complex. In vivo, experiments demonstrated that Q12 exhibited a higher tumor growth inhibition rate (TGI) compared to the positive control drug Lenvatinib, while maintaining good safety. In summary, it suggests that Topo I might be a potential target for matrine and Q12 represents a promising candidate for cancer treatment.

Design, synthesis and biological evaluation of matrine contains benzimidazole derivatives as dual TOPOI and PARP inhibitors for cancer therapy.

TOPOI inhibitors have long been a focal point in the research and development of antitumor drugs. PARP-1 plays a crucial role in repairing DNA damage induced by TOPOI inhibitors. Thus, concurrent inhibition of TOPOI and PARP-1 has the potential to augment drug activity. Matrine, characterized by low toxicity and good water solubility, offers advantageous properties. In this investigation, a series of benzimidazole matrine derivatives were designed and synthesized using matrine as the lead compound with the aim of developing dual inhibitors targeting both TOPOI and PARP-1. Among these derivatives, Compound B6 exhibited potent inhibitory effects on PARP-1 and TOPOI, effectively suppressing cancer cell proliferation and migration. Mechanistic assessments revealed that B6 induced DNA damage in HGC-27 cells, leading to G0/G1 cell cycle arrest and significant apoptosis. Molecular docking experiments demonstrated that B6 can effectively enter the active pocket of target proteins, where it forms stable hydrogen bonds with amino acid residues. In vivo, experiments demonstrated that B6 exhibited antitumor activity comparable to that of the positive control drug. The tumor growth inhibition rates (TGIs) for irinotecan, B6 and matrine were 87.0%, 75.4% and 9.7%, respectively. Importantly, B6 demonstrated lower toxicity than the positive control drug. Our findings suggest that TOPOI and PARP-1 may represent potential targets for matrine and B6 emerges as a promising candidate for cancer therapy.

Synthesis, antibacterial activity, and 3D-QASR studies of matrine-indole derivatives as potential antibiotics.

Matrine and indole have antibacterial, anticancer, and other biological activities, in order to develop new antibiotics to solve the problem of multi-drug resistant bacteria. In this paper, we synthesized a series of 29 novel matrine derivatives as potential drug candidates by combining indole analogs and matrine. The antibacterial activity of these compounds was evaluated through minimum inhibitory concentration (MIC) assays against five bacterial strains (S. aureus, C. albicans, P. acnes, P. aeruginosa, and E. coli). The obtained results demonstrated promising antibacterial efficacy, particularly for compounds A20 and A18, which exhibited MICs.au values of 0.021 and 0.031 mg/ml, respectively, against S. aureus. Moreover, compounds A20 and A27 displayed remarkable MICc.al values of 2.806 and 4.519 mg/ml, respectively, against C. albicans, surpassing the performance of the clinical antibiotic penicillin G sodium (0.0368 mg/ml) and fluconazole (4.849 mg/ml). These findings underscore the significant bacteriostatic activity of the matrine derivatives. Furthermore, to gain a deeper understanding 3D-QSAR modeling was employed, revealing the critical influence of steric structure, charge distribution, hydrophobic interactions, and hydrogen bonding within the molecular structure on the bacteriostatic activity of the compounds. Additionally, molecular docking simulations shed light on the interaction between compound A20 and bacterial proteins, highlighting the involvement of hydrogen bonding, hydrophobic interactions, and π-π conjugation in the formation of stable complexes that inhibit the normal functioning of the proteins. This comprehensive analysis provided valuable insights into the antibacterial mechanism of the novel matrine derivatives, offering theoretical support for their potential application as antibiotics.

Development of a novel hypochlorite ratio probe based on coumarin and its application in living cells.

Hypochlorous acid is a reactive oxygen species that is widely present in the body and has been found to exhibit an elevated concentration in tumors. As a result, fluorescent probes for tumor detection have recently gained significant attention. In this study, we designed and synthesized a novel ratiometric fluorescent probe, LW-1, using coumarin as a scaffold, and characterized its spectral properties. LW-1 displayed indigo blue fluorescence at low concentrations of hypochlorous acid. As the concentration of hypochlorous acid increased, the probe underwent a reaction, resulting in a red shift in its fluorescence peak and exhibiting green fluorescence. The fluorescence intensity ratio (green/blue) was a susceptible detection signal for HClO. LW-1 exhibited favorable characteristics, including a low detection limit, high sensitivity, good stability, and low background interference. The detection limit has reached 2.4642 nM. Moreover, we successfully employed LW-1 to image normal human liver and colon cancer cells in vitro, demonstrating its potential as a promising tool for tumor detection. Overall, our findings suggest that LW-1 could serve as a valuable addition to the current arsenal of fluorescent probes for tumor detection, with potential applications in the diagnosis and treatment of cancer.

Machine Learning and Quantum Calculation for Predicting Yield in Cu-Catalyzed P-H Reactions.

The paper discussed the use of machine learning (ML) and quantum chemistry calculations to predict the transition state and yield of copper-catalyzed P-H insertion reactions. By analyzing a dataset of 120 experimental data points, the transition state was determined using density functional theory (DFT). ML algorithms were then applied to analyze 16 descriptors derived from the quantum chemical transition state to predict the product yield. Among the algorithms studied, the Support Vector Machine (SVM) achieved the highest prediction accuracy of 97%, with over 80% correlation in Leave-One-Out Cross-Validation (LOOCV). Sensitivity analysis was performed on each descriptor, and a comprehensive investigation of the reaction mechanism was conducted to better understand the transition state characteristics. Finally, the ML model was used to predict reaction plans for experimental design, demonstrating strong predictive performance in subsequent experimental validation.

Predicting Drug Synergy and Discovering New Drug Combinations Based on a Graph Autoencoder and Convolutional Neural Network.

Drug synergy is a crucial component in drug reuse since it solves the problem of sluggish drug development and the absence of corresponding drugs for several diseases. Predicting drug synergistic relationships can screen drug combinations in advance and reduce the waste of laboratory resources. In this research, we proposed a model that utilizes graph autoencoder and convolutional neural networks to predict drug synergy (GAECDS). Our methods include a graph convolutional neural network as an encoder to encode drug features and use a matrix factorization method as a decoder. Multilayer perceptron (MLP) was applied to process cell line features and combine them with drug features. Furthermore, the latent vectors generated during the encoding process are being used to predict drug synergistic scores using a convolutional neural network. By measuring prediction performance using AUC, AUPR, and F1 score, GAECDS superior to other state-of-the-art models. In addition, four pairs of the predicted top 10 drug combinations were found to work well enough for evaluation. The case study shows that the GAECDS approach is useful for identifying potential drug synergy.

A Review of The Application of Spectroscopy to Flavonoids from Medicine and Food Homology Materials.

Medicinal and food homology materials are a group of drugs in herbal medicine that have nutritional value and can be used as functional food, with great potential for development and application. Flavonoids are one of the major groups of components in pharmaceutical and food materials that have been found to possess a variety of biological activities and pharmacological effects. More and more analytical techniques are being used in the study of flavonoid components of medicinal and food homology materials. Compared to traditional analytical methods, spectroscopic analysis has the advantages of being rapid, economical and free of chemical waste. It is therefore widely used for the identification and analysis of herbal components. This paper reviews the application of spectroscopic techniques in the study of flavonoid components in medicinal and food homology materials, including structure determination, content determination, quality identification, interaction studies, and the corresponding chemometrics. This review may provide some reference and assistance for future studies on the flavonoid composition of other medicinal and food homology materials.