Discovery of New Benzohydrazide Derivatives Containing 4-Aminoquinazoline as Effective Agricultural Fungicides, the Related Mechanistic Study, and Safety Assessment

A total of 38 new benzohydrazide derivatives bearing the 4-aminoquinazoline moiety were designed and synthesized based on the active subunit combination approach and tested in detail for their inhibition activities against eight agricultural phytopathogenic fungi. The bioassay results indicated that many of the synthesized compounds exhibited extraordinary fungicidal activities in vitro against the tested fungi. For example, compounds A5, A6, A11, and A17 had EC50 (half-maximal effective concentration) values of 0.66, 0.71, 0.40, and 0.42 μg/mL against Colletotrichum gloeosporioides, respectively, comparable to that of boscalid (0.36 μg/mL) and much superior to that of carbendazim (6.96 μg/mL). Of particular importance was that compound A6 with a 3,4-difluorophenyl group was found to possess good broad-spectrum antifungal effects, with EC50 values ranging from 0.63 to 3.82 μg/mL against the tested eight fungi. In vivo antifungal assays also revealed that compound A6 had good curative and protective efficacies of 72.6% and 78.9% at 200 μg/mL against Rhizoctonia solani-caused rice sheath blight, higher than those of boscalid (70.7 and 65.2%, respectively). Moreover, the mechanism-of-action studies revealed that compound A6 disrupted the cell membrane integrity of R. solani, as proved by relative conductivity measurements, leakage of cellular contents, fluorescence microscopy, and scanning electron microscopy observations. Significantly, this compound also exhibited an effective inhibition of succinate dehydrogenase (SDH) from R. solani (half-maximal inhibitory concentration/IC50 = 11.02 μM), slightly weaker than that of the SDH inhibitor boscalid (5.17 μM). Further molecular docking analysis revealed that compound A6 could form strong interactions with the key residues of SDH enzyme via hydrogen bond, electrostatic, and π-cation interactions, holding promise for acting as new fungicide leads targeting SDH. Finally, the safety assessments indicated that compound A6 was safe for rice and honeybees.

HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors

Histone deacetylase 6 (HDAC6) is a promising drug target for the treatment of human diseases such as cancer, neurodegenerative diseases (in particular, Alzheimer's disease), and multiple sclerosis. Considerable attention is paid to the development of selective non-toxic HDAC6 inhibitors. To this end, we successfully form a set of 3854 compounds and proposed adequate regression QSAR models for HDAC6 inhibitors. The models have been developed using the PubChem, Klekota-Roth, 2D atom pair fingerprints, and RDkit descriptors and the gradient boosting, support vector machines, neural network, and k-nearest neighbours methods. The models are integrated into the developed HT_PREDICT application, which is freely available at https://htpredict.streamlit.app/. In vitro studies have confirmed the predictive ability of the proposed QSAR models integrated into the HT_PREDICT web application. In addition, the virtual screening performed with the HT_PREDICT web application allowed us to propose two promising inhibitors for further investigations.