Design, synthesis and evaluation of 3-arylidene azetidin-2-ones as potential antifungal agents against Alternaria solani Sorauer

Design, Synthesis, and Fungicidal Activities of Indole-Modified Cinnamamide Derivatives

Dimethomorph is a kind of cinnamamide fungicide with high fungicidal activities for oomycete diseases. The commercially available dimethomorph is a mixture of two isomers, in which (Z)-dimethomorph possessing higher activity and (E)-dimethomorph possessing lower activity. Herein, we reported the design, synthesis and fungicidal activities of a series of novel indole-modified cinnamamide derivatives, which used the indole group to 'fix' the cis-styrene group in (Z)-dimethomorph. The modification of the molecular structure of cinnamamide compounds could be beneficial to improve its practical application performance. Tested the fungicidal activities, it was found that compounds 8j, 9a, 9e, 9i and 9j showed excellent in vivo fungicidal activities (80-100 %) against Pseudoperonospora cubensis at a concentration of 100 mg L^-1 , while dimethomorph and flumorph were noneffective. Moreover, parts of synthesized indole-modified cinnamamide derivatives 8 (8a, 8c, 8d and 8j) and 9 (9c and 9j) exhibited the same in vivo fungicidal activities against Phytophthora infestans with dimethomorph or flumorph at a concentration of 50 mg L^-1 with 100 % inhibition. The biological assay results indicated that indole-modified cinnamamide derivatives have promising applications in the prevention and treatment of Phytophthora infestans.

Synthesis of Arylidene-β-lactams via exo-Selective Matsuda-Heck Arylation of Methylene-β-lactams

exo-Methylene-β-lactams were synthesized in two steps from commercially available 3-bromo-2-(bromomethyl)propionic acid and reacted with arene diazonium salts in a Heck-type arylation in the presence of catalytic amounts of Pd(OAc)₂ under ligand-free conditions. The products, arylidene-β-lactams, were obtained in high yields as single isomers. The β-hydride elimination step of the Pd-catalyzed coupling reaction proceeds with high exo-regioselectivity and E-stereoselectivity. With aryl iodides, triflates, or bromides, the coupling products were isolated only in low yields, due to extensive decomposition of the starting material at elevated temperatures. This underlines that arene diazonium salts can be superior arylating reagents in Heck-type reactions and yield coupling products in synthetically useful yields and selectivities when conventional conditions fail.

Highlights on Steroidal Arylidene Derivatives as a Source of Pharmacologically Active Compounds: A Review

Steroids constitute a unique class of chemical compounds, playing an important role in physiopathological processes, and have high pharmacological interest. Additionally, steroids have been associated with a relatively low toxicity and high bioavailability. Nowadays, multiple steroidal derivatives are clinically available for the treatment of numerous diseases. Moreover, different structural modifications on their skeleton have been explored, aiming to develop compounds with new and improved pharmacological properties. Thus, steroidal arylidene derivatives emerged as a relevant example of these modifications. This family of compounds has been mainly described as 17β-hydroxysteroid dehydrogenase type 1 and aromatase inhibitors, as well as neuroprotective and anticancer agents. Besides, due to their straightforward preparation and intrinsic chemical reactivity, steroidal arylidene derivatives are important synthetic intermediates for the preparation of other compounds, particularly bearing heterocyclic systems. In fact, starting from arylidenesteroids, it was possible to develop bioactive steroidal pyrazolines, pyrazoles, pyrimidines, pyridines, spiro-pyrrolidines, amongst others. Most of these products have also been studied as anti-inflammatory and anticancer agents, as well as 5α-reductase and aromatase inhibitors. This work aims to provide a comprehensive overview of steroidal arylidene derivatives described in the literature, highlighting their bioactivities and importance as synthetic intermediates for other pharmacologically active compounds.

Machine learning for the prediction of molecular dipole moments obtained by density functional theory

Machine learning (ML) algorithms were explored for the fast estimation of molecular dipole moments calculated by density functional theory (DFT) by B3LYP/6-31G(d,p) on the basis of molecular descriptors generated from DFT-optimized geometries and partial atomic charges obtained by empirical or ML schemes. A database was used with 10,071 structures, new molecular descriptors were designed and the models were validated with external test sets. Several ML algorithms were screened. Random forest regression models predicted an external test set of 3368 compounds achieving mean absolute error up to 0.44 D. The results represent a significant improvement of the dipole moments calculated using empirical point charges located at the nucleus, even assuming the DFT-optimized geometry (root mean square error, RMSE, of 0.68 D vs. 1.53 D and R² = 0.87 vs. 0.66).