Screening of Oxygenated Aromatic Compounds for Potential Antifungal Activity against Geotrichum citri-aurantii through Structure-Activity Relationship Analysis

Discovery of potential anti- Staphylococcus aureus natural products and their mechanistic studies using machine learning and molecular dynamic simulations

The structure-activity analysis (SAR) and machine learning were used to investigate potential anti-S. aureus agents in a faster method. In this study, 24 oxygenated benzene ring components with S. aureus inhibition capacity were confirmed by literature exploring and in-house experiments, and the SAR analysis suggested that the hydroxyl group position may affect the anti-S. aureus activity. The 2D-MLR-QSAR model with 9 descriptors was further evaluated as the best model among the 21 models. After that, hesperetic acid and 2-HTPA were further explored and evaluated as the potential anti-S. aureus agents screening in the natural product clustering library through the best QSAR model calculation. The antibacterial capacities of hesperetic acid and 2-HTPA had been investigated and proved the similar predictive pMIC value resulting from the QSAR model. Besides, the two novel components were able to inhibit the growth of S. aureus by disrupting the cell membrane through the molecular dynamics simulation (MD), which further evidenced by scanning electron microscopy (SEM) test and PI dye results. Overall, these results are highly suggested that QSAR can be used to predict the antibacterial agents targeting S. aureus, which provides a new paradigm to research the molecular structure-antibacterial capacity relationship.

Computation-Directed Molecular Design, Synthesis, and Fungicidal Activity of Succinate Dehydrogenase Inhibitors

Succinate dehydrogenase inhibitors (SDHIs) are a class of fungicides targeting the pathogenic fungi mitochondrial SDH. Here, molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular dynamics (MD) simulations were used to guide SDHI innovation. Molecular docking was performed to explore the binding modes of SDH and its inhibitors. 3D-QSAR models were carried out on 33 compounds with activity against Rhizoctonia cerealis (R. cerealis); their structure-activity relationships were analyzed using comparative molecular field analysis and comparative molecular similarity indices analysis. MD simulations were used to assess the stability of the complexes under physiological conditions, and the results were consistent with molecular docking. Binding free energy was calculated through the molecular mechanics generalized born surface area method, and the binding free energy was decomposed. The results are consistent with the activity of bioassay and indicate that van der Waals and lipophilic interactions contribute the most in the molecular binding process. Afterward, we designed and synthesized 12 compounds under the guidance of the above-mentioned analyses, bioassay found that F9 was active against R. cerealis with the EC50 value of 9.43 μg/mL, and F4, F5, and F9 were active against Botrytis cinerea with an EC50 values of 5.80, 3.17, and 1.63 μg/mL, respectively. They all showed good activity between positive controls of pydiflumetofen and thifluzamide. Our study provides new considerations for effective SDHIs discovery.

3D-QSAR Combination with Molecular Dynamics Simulations to Effectively Design the Active Ryanodine Receptor Agonists against Spodoptera frugiperda

Computer-aided molecular modeling was applied to design a series of Spodoptera frugiperda RyR agonists. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. MD simulations in the complex with S. frugiperda native, mutant RyR, and mammalian RyR1 under physiological conditions were used to validate the detailed binding mechanism. Binding free energy calculation by molecular mechanics generalized surface area (MM-GBSA) explained the role of key amino acid residues in ligand-receptor binding. Therefore, 14 new compounds were effectively designed and synthesized, and a bioassay indicated that compounds A-2 and A-3 showed comparable activity to that of chloranthraniliprole with LC50 values of 0.27, 0.18, and 0.20 mg L-1, respectively, against S. frugiperda. Most target compounds also displayed good activity against Mythinma separata at 0.1 mg L-1. Molecular docking and MM-GBSA calculations demonstrated that A-3 had a better binding capacity with native and mutant S. frugiperda RyRs.