Quinones from Cordia species from 1972 to 2023:isolation,structural diversity and pharmacological activities

Plants of the genus Cordia(Boraginaceae family)are widely distributed in the tropical regions of America,Africa,and Asia.They are extensively used in folk medicine due to their rich medicinal properties.This review presents a comprehensive analysis of the isolation,structure,biogenesis,and biological properties of quinones from Cordia species reported from 1972 to 2023.Meroterpenoids were identified as the major quinones in most Cordia species and are reported as a chemotaxonomic markers of the Cordia.In addition to this property,quinones are reported to display a wider and broader spectrum of activities,are efficient scaffold in biological activity,compared to other classes of compounds reported in Cordia,hence our focus on the study of quinones reported from Cordia species.About 70 types of quinones have been isolated,while others have been identified by phytochemical screening or gas chromatography.Although the biosynthesis of quinones from Cordia species is not yet fully understood,previous reports suggest that they may be derived from geranyl pyrophosphate and an aromatic precursor unit,followed by oxidative cyclization of the allylic methyl group.Studies have demonstrated that quinones from this genus exhibit antifungal,larvicidal,antileishmanial,anti-inflammatory,antibiofilm,antimycobacterial,antioxidant,antimalarial,neuroinhibitory,and hemolytic activities.In addition,they have been shown to exhibit remarkable cytotoxic effects against several cancer cell lines which is likely related to their ability to inhibit electron transport as well as oxidative phosphorylation,and generate reactive oxygen species(ROS).Their biological activities indicate potential utility in the development of new drugs,especially as active components in drug-carrier systems,against a broad spectrum of pathogens and ailments.

Photocatalytic degradation of antibiotic sulfamethizole by visible light activated perovskite LaZnO_(3)

In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light activation.SMZ was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO_(3) at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·OH.The integration of RP-HPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 intrusion.Corresponding toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation process.The visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.

Auto Machine Learning Assisted Preparation of Carboxylic Acid by TEMPO-Catalyzed Primary Alcohol Oxidation

Though alcohol oxidations were considered as well-established reactions,selecting productive conditions or predicting reaction yields for unseen alcohols remained as major challenges.Herein,an auto machine learning(ML)model for TEMPO-catalyzed oxida-tion of primary alcohols to the corresponding carboxylic acids is disclosed.A dataset of 3444 data,consisting of 282 primary alco-hols and 45 conditions,were generated using high-throughput experimentation(HTE).With the HTE data and 105 descriptors,a multi-label prediction was performed with AutoGluon(an open-source auto machine learning framework)and KNIME(an open-source data analytics platform).For the independent test of 240 reactions(a full matrix of 20 unseen alcohols and 12 condi-tions),AutoGluon with multi-label prediction for yield prediction(AGMP)gave excellent performance.For external test of 1308 re-actions(consisting of 84 alcohols and 45 conditions),AGMP still afforded good results with R2 as 0.767 and MAE as 4.9%.The model also revealed that the newly generated descriptor(Y/N,classification of the reaction reactivity)was the most relevant descriptor for yield prediction,offering a new perspective to integrate HTE and ML in organic synthesis.

Mechanism and selectivity of copper-catalyzed borocyanation of 1-aryl-1,3-butadienes:A computational study

Density functional theory calculations have been performed to investigate the copper-catalyzed borocyanation of 1-aryl-1,3-butadienes.The computations show that the regio-and enantioselectivity is determined by the borocupration step.The π-electron withdrawing aryl group at the C' atom makes the C4 atom more electrophilic than the other carbon atoms,which together with the steric repulsion around the forming C-B bond,re sults in the experimentally observed exclusive 4,3-regioselectivity.The origins of the enantioselectivity were attributed to the steric effect and π-π stacking interaction between the butadiene moiety and the ligand.