Synthesis, Antifungal Activity, 3D-QSAR, and Molecular Docking Study of Novel Menthol-Derived 1,2,4-Triazole-thioether Compounds

High value-added application of natural forest product α-pinene: design, synthesis and 3D-QSAR study of novel α-campholenic aldehyde-based 4-methyl-1,2,4-triazole-thioether compounds with significant herbicidal activity

For exploring novel natural product-derived herbicides, 16 novel α-campholenic aldehyde-based 4-methyl-1,2,4-triazole-thioether compounds were designed, synthesized, and characterized by FT-IR, 1H NMR, 13C NMR, ESI-MS and elemental analysis. The preliminary bioassay showed that, at 100 µg/mL, most of the target compounds displayed significant inhibition activity against root-growth of rape(Brassica campestris L.), with inhibition rates of 85.0%～98.2%(A-class activity level), much better than that of the positive control flumioxazin. In addition, an effective and reasonable 3D-QSAR model was established by CoMFA method in SYBYL-X 2.1.1 software. It was found that, the steric field was the major factor towards the herbicidal activity of the target compounds against B. campestris L., and the introduction of bulky groups into m- and p-position of the benzene ring was favourable to increase the herbicidal activity. This kind of title compounds deserved further study as potential leading compounds for the discovery and development of novel herbicidal agents.

Recent advances in 1,2,3- and 1,2,4-triazole hybrids as antimicrobials and their SAR: A critical review

With the widespread use and sometimes even abuse of antibiotics, the problem of bacterial resistance to antibiotics has become very serious, and it is posing a great threat to global health. Therefore, development of new antibiotics is imperative. Triazoles are five-membered, nitrogen-containing aromatic heterocyclic scaffolds, with two isomeric forms, i.e. 1,2,3-triazole and 1,2,4-triazole. Triazole-containing compounds have a wide range of biological activities such as antibacterial, antifungal, anticancer, antioxidant, antitubercular, antimalarial, anti-HIV, anticonvulsant, anti-inflammatory, antiulcer, analgesic, and etc. The bioactivities and the diversity of triazole-containing drugs have attracted wide interest in these heterocycles. Various antibiotic triazole hybrids have been developed, and most of which have shown potent antimicrobial activities. In this review, we summarized the recent advances in triazole hybrids as potential antibacterial agents and their structure-activity relationships (SARs). The information gained through SAR studies will provide further insights into the development of new triazole antimicrobials.

Synthesis, Antifungal Activities, Molecular Docking and Molecular Dynamic Studies of Novel Quinoxaline-Triazole Compounds

Uncontrolled use of antifungal drugs affects the development of resistance to existing drugs. Azole antifungals constitute a large part of antifungal therapy. Therefore, there is a need for new azole antifungals. Within the scope of this study, 17 new triazole derivative compounds were synthesized. Structure determinations were clarified by spectroscopic analysis methods (¹H-NMR, ¹³C-NMR, HRMS). In addition, structure matching was completed using two-dimensional NMR techniques, HSQC, HMBC and NOESY. The antifungal effects of the compounds were evaluated on Candida strains by means of in vitro method. Compound 5d showed activity against Candida glabrata with a MIC₉₀ = 2 μg/mL. Compound 5d showed activity against Candida krusei with a MIC₉₀ = 2 μg/mL. This activity value, which is higher than fluconazole, is promising. In addition, the biofilm inhibition percentages of the compounds were calculated. Molecular docking and molecular dynamics simulations performed with compound 5d are in harmony with activity studies.

Synthesis and Antifungal Activity of Novel L-Menthol Hydrazide Derivatives as Potential Laccase Inhibitors

To discover novel laccase inhibitors as potential fungicides, twenty-six novel L-menthol hydrazide derivatives were designed and synthesized. In the in vitro antifungal assay, most of the target compounds displayed pronounced antifungal activity against Sclerotinia sclerotiorum, Fusarium graminearum, and Botryosphaeria dothidea. Especially, the EC50 of compounds 3 b and 3 q against B. dothidea was 0.465 and 0.622 mg/L, which was close to the positive compound fluxapyroxad (EC50 =0.322 mg/L). Scanning electron microscopy (SEM) analysis showed that compound 3 b could significantly damage the mycelial morphology of B. dothidea. In vivo antifungal experiments on apple fruits showed that 3 b exhibited excellent protective and curative effects. Furthermore, in the in vitro laccase inhibition assay, 3 b showed outstanding inhibitory activity with the IC50 value of 2.08 μM, which is much stronger than positive control cysteine and PMDD-5Y. These results indicated that this class of L-menthol derivatives could be promising leads for the discovery of laccase-targeting fungicides.

Synthesis, Antifungal Activity, 3D-QSAR and Controlled Release on Hydrotalcite Study of Longifolene-Derived Diphenyl Ether Carboxylic Acid Compounds

Twenty-two novel longifolene-derived diphenyl ether-carboxylic acid compounds 7a-7v were synthesized from renewable biomass resources longifolene, and their structures were confirmed by FT-IR, ¹H NMR, ¹³C NMR, and HRMS. The preliminary evaluation of in vitro antifungal activity displayed that compound 7b presented inhibition rates of 85.9%, 82.7%, 82.7%, and 81.4% against Alternaria solani, Cercospora arachidicola, Rhizoctonia solani, and Physalospora piricola, respectively, and compound 7l possessed inhibition rates of 80.7%, 80.4%, and 80.3% against R. solani, C. arachidicola, P. piricola, respectively, exhibiting excellent and broad-spectrum antifungal activities. Besides, compounds 7f and 7a showed significant antifungal activities with inhibition rates of 81.2% and 80.7% against A.solani, respectively. Meanwhile, a reasonable and effective 3D-QSAR mode (r² = 0.996, q² = 0.572) has been established by the CoMFA method. Furthermore, the drug-loading complexes 7b/MgAl-LDH were prepared and characterized. Their pH-responsive controlled-release behavior was investigated as well. As a result, complex 7b/MgAl-LDH-2 exhibited excellent controlled-releasing performance in the water/ethanol (10:1, v:v) and under a pH of 5.7.

Synthesis, Antifungal Activity and 3D-QSAR Study of Novel Anisaldehyde-Derived Amide-Thiourea Compounds

Succinate dehydrogenase (SDH) is an important target enzyme for designing agricultural chemical fungicides. In order to explore novel natural product-based antifungal agents, twenty-one unreported anisaldehyde-derived amide-thiourea compounds were designed and synthesized using the principle of active splicing, and structurally confirmed by ¹ H-NMR, ¹³ C-NMR, ESI-MS, FT-IR, and element analysis. In vitro antifungal activity of the target compounds was evaluated by the agar dilution method. The results showed that some target compounds exhibited better or comparable antifungal activity than that of the commercial fungicide chlorothalonil, in which compounds 5c, 5o, and 5r displayed excellent antifungal activity of 92.6 %, 92.6 % and 99.1 % against P. piricola, respectively, better than that of the positive control. In addition, 3D-QSAR analysis was carried out by the CoMFA method to reveal the relationship between the structures of the target compounds and their inhibitory activities. The simulative binding mode of the target compounds and SDH was also studied by molecular docking.

A Deep Learning-Based Quantitative Structure-Activity Relationship System Construct Prediction Model of Agonist and Antagonist with High Performance

Molecular design and evaluation for drug development and chemical safety assessment have been advanced by quantitative structure–activity relationship (QSAR) using artificial intelligence techniques, such as deep learning (DL). Previously, we have reported the high performance of prediction models molecular initiation events (MIEs) on the adverse toxicological outcome using a DL-based QSAR method, called DeepSnap-DL. This method can extract feature values from images generated on a three-dimensional (3D)-chemical structure as a novel QSAR analytical system. However, there is room for improvement of this system’s time-consumption. Therefore, in this study, we constructed an improved DeepSnap-DL system by combining the processes of generating an image from a 3D-chemical structure, DL using the image as input data, and statistical calculation of prediction-performance. Consequently, we obtained that the three prediction models of agonists or antagonists of MIEs achieved high prediction-performance by optimizing the parameters of DeepSnap, such as the angle used in the depiction of the image of a 3D-chemical structure, data-split, and hyperparameters in DL. The improved DeepSnap-DL system will be a powerful tool for computer-aided molecular design as a novel QSAR system.