Three-dimensional Quantitative Structure-activity Relationship Models Research Articles

Quantification- and structural-taste intensity of umami peptides from Agrocybe aegerita through quantitative structure-activity relationship

Agrocybe aegerita, one of the edible mushroom varieties, is popular among consumers for its umami taste. Umami peptides, including EV, EG, EY, ENG, ECG, DEL, DDL, PEG, PEEL, DGPL, and EDCS are the main umami compounds in A. aegerita. In this study, when the concentration of these 11 umami peptides was 5 mg/mL, the corresponding relative umami intensity (measured by MSG concentration) ranged from 4.457 to 5.240 mg/mL, with DDL being the highest. All umami peptides exhibited better umami taste under neutral and weakly acidic conditions (pH 6-7). EY and ENG, with a higher umami intensity at 70 °C, were more suitable for a wide application in thermally processed foods. Additionally, the relationship between the structure and strength of umami peptides was explored using a three-dimensional quantitative structure-activity relationship model with an R2 of 0.987. Overall, umami peptides in A. aegerita possess strong potential for application in food processing.

Design, Synthesis, and 3D-QASR of 2-Ar-1,2,3-triazole Derivatives Containing Hydrazide as Potential Fungicides.

A series of novel 2-Ar-1,2,3-triazole derivatives were designed and synthesized based on our previously discovered active compound 6d against Rhizoctonia solani. Most of these compounds exhibited good antifungal activity against R. solani at a concentration of 25 μg/mL. Based on the results of biological activity, we established a three-dimensional quantitative structure-activity relationship (3D-QSAR) model that guided the synthesis of compound 7y. Compound 7y exhibited superior activity against R. solani (EC50 = 0.47 μg/mL) compared to the positive controls hymexazol (EC50 = 12.80 μg/mL) and tebuconazole (EC50 = 0.87 μg/mL). Furthermore, compound 7y demonstrated better protective activity than the aforementioned two commercial fungicides in both detached leaf assays and greenhouse experiments, achieving 56.21% and 65.75% protective efficacy, respectively, at a concentration of 100 μg/mL. The ergosterol content was determined and molecular docking was performed to explore the mechanism of these active molecules. DFT calculation and MEP analysis were performed to illustrate the results of this study. These results suggest that compound 7y could serve as a novel 2-Ar-1,2,3-triazole lead compound for controlling R. solani.

Concurrent Optimizations of Efficacy and Blood-Brain Barrier Permeability in New Macrocyclic LRRK2 Inhibitors for Potential Parkinson's Disease Therapeutics.

The elevated activity of leucine-rich repeat kinase 2 (LRRK2) is implicated in the pathogenesis of Parkinson's disease (PD). The quest for effective LRRK2 inhibitors has been impeded by the formidable challenge of crossing the blood-brain barrier (BBB). We leveraged structure-based de novo design and developed robust three-dimensional quantitative structure-activity relationship (3D-QSAR) models to predict BBB permeability, enhancing the likelihood of the inhibitor's brain accessibility. Our strategy involved the synthesis of macrocyclic molecules by linking the two terminal nitrogen atoms of HG-10-102-01 with an alkyl chain ranging from 2 to 4 units, laying the groundwork for innovative LRRK2 inhibitor designs. Through meticulous computational and synthetic optimization of both biochemical efficacy and BBB permeability, 9 out of 14 synthesized candidates demonstrated potent low-nanomolar inhibition and significant BBB penetration. Further assessments of in vitro and in vivo effectiveness, coupled with pharmacological profiling, highlighted 8 as the promising new lead compound for PD therapeutics.

Discovery of Trisubstituted N-Phenylpyrazole Containing Diamides with Improved Insecticidal Activity.

To increase the structural diversity of insecticides and meet the needs of effective integrated insect management, the structure of chlorantraniliprole was modified based on a previously established three-dimensional quantitative structure-activity relationship (3D-QSAR) model. The pyridinyl moiety in the structure of chlorantraniliprole was replaced with a 4-fluorophenyl group. Further modifications of this 4-fluorophenyl group by introducing a halogen atom at position 2 and an electron-withdrawing group (e.g., iodine, cyano, and trifluoromethyl) at position 5 led to 34 compounds with good insecticidal efficacy against Mythimna separata, Plutella xylostella, and Spodoptera frugiperda. Among them, compound IV f against M. separata showed potency comparable to that of chlorantraniliprole. IV p against P. xylostella displayed a 4.5 times higher potency than chlorantraniliprole. In addition, IV d and chlorantraniliprole exhibited comparable potencies against S. frugiperda. Transcriptome analysis showed that the molecular target of compound IV f is the ryanodine receptor. Molecular docking was further performed to verify the mode of action and insecticidal activity against resistant P. xylostella.

Novel 5-Sulfonyl-1,3,4-thiadiazole-Substituted Flavonoids as Potential Bactericides and Fungicides: Design, Synthesis, Three-Dimensional Quantitative Structure-Activity Relationship Studies.

Flavonoids, ubiquitous natural products, provide sources for drug discovery owing to their structural diversity, broad-spectrum pharmacological activity, and excellent environmental compatibility. To develop antibacterial and antifungal agents with novel mechanisms of action and innovative structures, a series of novel 5-sulfonyl-1,3,4-thiadiazole-substituted flavonoids were designed and synthesized, and their biological activities against seven agriculturally common phytopathogenic microorganisms were evaluated. The results of the antimicrobial bioassay showed that most of the target compounds displayed excellent inhibitory effects against Xanthomonas oryzae, Rhizoctonia solani, and Colletotrichum orbiculare. Compounds 1, 3, 7, 9, 13, and 14 exhibited remarkable antibacterial activity against X. oryzae pv. oryzae with EC50 values below 10 μg/mL, which were superior to bismerthiazol (70.89 μg/mL). Compound 2 (EC50 = 0.41 μg/mL) displayed the most effective inhibitory potency against R. solani in vivo, comparable protective effects with the positive control carbendizam. Preliminary mechanistic studies indicated that compound 2 induced disordered entanglement of hyphae, shrinkage of hyphal surfaces, extravasation of cellular contents, and vacuole swelling and rupture, which disrupted normal hyphal growth. Subsequently, compounds 35-53 with good antifungal activity were designed and synthesized based on reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) models. Compound 49 showed high efficacy and superior antifungal activity against R. solani, with an EC50 value of 0.28 μg/mL and a half-maximal effective concentration of 0.46 μg/mL.

Strategic development and validation of Isoquinoline-Derived inhibitors targeting ROCK1 kinase

Rho-associated coiled-coil containing kinases (ROCKs) have emerged as pivotal downstream effectors of small guanosine triphosphatases. In recent years, isoquinoline derivatives have garnered substantial attention as potent inhibitors of ROCK1 (RKIs). To delve deeper into their pharmacological properties and to identify potential inhibitors, we conducted an in-depth exploration of a series of RKIs derived from isoquinoline derivatives. This exploration encompassed a multifaceted approach, combining three-dimensional quantitative structure–activity relationship modeling, induced fit docking, and virtual screening. Our comparative molecular field analysis model (q2 = 0.609, R2 = 0.991, ONC = 6, and r2pred = 0.973) and the most robust comparative molecular similarity indices analysis model (q2 = 0.712, R2 = 0.998, ONC = 7, and r2pred = 0.89) exhibited commendable predictive accuracy, bolstered by robust validation parameters. To gain deeper insights into the mechanism of action of isoquinoline-based RKIs, we harnessed precise docking techniques, including induced fit docking, structural interaction fingerprints, and binding pose metadynamics simulations. Employing the PRRR_2 pharmacophore, we meticulously screened Enamine's HLL-460 compound library, unearthing thousands of isoquinoline compounds that aligned with the desired profile. Subsequently, we identified three promising compounds (DS01, DS02, and DS03) through Glide docking, each assessed at varying precision levels. These compounds underwent comprehensive evaluation for their drug-like properties, leveraging QikProp and SwissADME, ultimately unveiling their potential as novel and efficacious RKIs. Furthermore, bolstered by molecular dynamics simulations and validated through activity assays, the bioactivity of the screened molecules DS02, and DS03 was corroborated. DS02 and DS03, previously unreported for their activity against ROCK1, delivered exceptionally promising results. This comprehensive study not only elucidates validated strategies for drug development but also imparts invaluable insights into the design of potent RKIs.

Design, Synthesis, Antifungal Activity, and 3D-QASR of Novel Oxime Ether-Containing Coumarin Derivatives as Potential Fungicides.

Structural modification of natural products is an effective approach for improving antifungal activity and has, therefore, been used extensively in the development of new agrochemical products. In this work, a series of novel coumarin derivatives containing oxime ether structures were designed, synthesized, and evaluated for antifungal activity. Some of the designed compounds exhibited promising antifungal activities against tested fungi, and compounds 4a, 4c, 5a, and 6b had EC50 values equivalent to those of commercial fungicides. Compound 6b was the most promising candidate fungicide against Rhizoctonia solani (EC50 = 0.46 μg/mL). In vivo antifungal bioassays suggested that compounds 5a and 6b could serve as novel agricultural antifungals. Furthermore, microscopy demonstrated that compound 6b induced the sprawling growth of hyphae, distorted the outline of cell walls, and reduced mitochondrial numbers. Additionally, the effects of the substituent steric, electrostatic, hydrophobic, and hydrogen-bond fields were elucidated using an accurate and reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) model. The results presented here will guide the discovery of potential novel fungicides for plant disease control in agriculture.

A Potential Fungicide against Pseudoperonospora Cubensis: Design, Synthesis and 3D-QSAR of New Pyrazole-5-Carboxamide Derivatives.

Downy mildew is one of the major fungi causing significant economic losses to crops. The resistance of this fungus to current fungicides is increasing and new fungicides with a unique mode of action are needed. To find a novel pyrazole amide derivative as a potential fungicide. A series of pyrazole-5-carboxamide derivatives containing a diaryl ether were designed and synthesized by the Intermediate derivatization method (IDM). Their fungicidal activities against Pseudoperonospora cubensis (P. cubensis, cucumber downy mildew) were evaluated in the greenhouse. Bioassays indicated that several compounds exhibited excellent fungicidal activity against P. cubensis in vivo. In particular, T24 (EC50 = 0.88 mg L-1) had the highest activity compared with Dimethomorph and Fluazinam and other analogues. The relationship between the activity and the structure of these derivatives was analyzed, and an accurate and reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established to determine that electrostatic and steric fields had important effects on the improvement of fungicidal activity. The novel pyrazole-5-carboxamide derivative T24 can be considered a potential fungicide for P. cubensis control.

3D-QSAR Studies on High-affinity Phosphodiestera.

Recent studies have found that Phosphodiesterase-4 (PDE4) is closely related to the pathogenesis of depression, cognitive impairment and neurological impairment. Our objective is to develop potent inhibitors of the high-affinity phosphodiesterase 4D isoform (PDE4D) that can serve as radioligands for Positron Emission Tomography (PET) imaging, thereby advancing research in the field of neurological diseases. We employed a multi-step approach combining three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, classification techniques, and CoMSIA analysis to investigate the conformational relationship of highaffinity PDE4D inhibitors as PET ligands. ADMET and Drug-likeness predictions were also conducted. By utilizing these methods, our aim was to identify more potent PDE4D inhibitors. The results showed that the CoMSIA model with the best principal component scores (n=7) had a cross-validated Q2 value of 0.602 and a non-cross-validated R2 value of 0.976. These results affirmed the excellent predictive capability of the established CoMSIA model. Analysis of the generated 3D-QSAR contour plots highlighted specific regions in the molecular structure of the compounds that can be further optimized and modified. Guided by the contour plots, we designed 100 novel PDE4D inhibitors, and molecular docking was performed for the top 4 compounds with high activity. The molecular docking scores were promising, and ADMET and drug similarity predictions yielded satisfactory results. Taking into consideration these factors, compound 51c was determined to be the optimal compound, laying a solid foundation for further research. For the continued development of PDE4D PET radioligand, these models and new compounds' developing methodology offer a theoretical foundation and crucial references.

Control list of high-priority chemicals based on 5-HT-RI functionality and the human health interference effects selective CNN-GRU deep learning model

The antidepressant drug known as 5-HT reuptake inhibitor (5-HT-RI) was commonly detected in biological tissues and result in significant adverse health effects. Homology modeling was used to characterize the functionalities (efficacy and resistance), and the adverse outcome pathway was used to characterize its human health interferences (olfactory toxicity, neurotoxicity, and gut microbial interference). The convolutional neural network coupled with the gated recurrent unit (CNN-GRU) deep learning method was used to construct a comprehensive model of 5-HT-RI functionality and human health interference effects selectivity with small sample data. The architecture with 2 SE, 320 neuronal nodes and 6-folds cross-validation showed the best applicability. The results showed that the confidence interval of the constructed model reached 90 % indicating that the model had reliable prediction ability and generalization ability. Based on the CNN-GRU deep learning model, seven high-priority chemicals with a weak comprehensive effect, including D-VEN, (1R,4S)-SER, S-FLX, CTP, S-CTP, NEF, and VEN, were screened. Based on the molecular three-dimensional structure information, a comprehensive-effect three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed to confirm the reliability of the constructed control list of 5-HT-RI high-priority chemicals. Analysis with the ranking of calculated values based on the molecular dynamics method and predicted values based on the CNN-GRU deep learning model, we found that the consistency of the three methods was above 85 %. Additionally, by analyzing the sensitivity, molecular electrostatic potential, polar surface area of the comprehensive-effect CNN-GRU deep learning model, and the electrostatic field of the 3D-QSAR models, we found that the significant effects of five key characteristics (DM, Qyy, Qxz, I, and BP), molecular electronegativity, and polarity significantly affected the high-priority degree of 5-HT-RI. In this study, we provided reasonable and reliable prediction tools and discussed theoretical methods for the risk assessment of functionality and human health interference of emerging pollutants such as 5-HT-RI.

Exploring Citrus sinensis Phytochemicals as Potential Inhibitors for Breast Cancer Genes BRCA1 and BRCA2 Using Pharmacophore Modeling, Molecular Docking, MD Simulations, and DFT Analysis.

Structure-activity relationship (SAR) is considered to be an effective in silico approach when discovering potential antagonists for breast cancer due to gene mutation. Major challenges are faced by conventional SAR in predicting novel antagonists due to the discovery of diverse antagonistic compounds. Methodologyand Results: In predicting breast cancer antagonists, a multistep screening of phytochemicals isolated from the seeds of the Citrus sinensis plant was applied using feasible complementary methodologies. A three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed through the Flare project, in which conformational analysis, pharmacophore generation, and compound alignment were done. Ten hit compounds were obtained through the development of the 3D-QSAR model. For exploring the mechanism of action of active compounds against cocrystal inhibitors, molecular docking analysis was done through Molegro software (MVD) to identify lead compounds. Three new proteins, namely, 1T15, 3EU7, and 1T29, displayed the best Moldock scores. The quality of the docking study was assessed by a molecular dynamics simulation. Based on binding affinities to the receptor in the docking studies, three lead compounds (stigmasterol P8, epoxybergamottin P28, and nobiletin P29) were obtained, and they passed through absorption, distribution, metabolism, and excretion (ADME) studies via the SwissADME online service, which proved that P28 and P29 were the most active allosteric inhibitors with the lowest toxicity level against breast cancer. Then, density functional theory (DFT) studies were performed to measure the active compound's reactivity, hardness, and softness with the help of Gaussian 09 software. This multistep screening of phytochemicals revealed high-reliability antagonists of breast cancer by 3D-QSAR using flare, docking analysis, and DFT studies. The present study helps in providing a proper guideline for the development of novel inhibitors of BRCA1 and BRCA2.

Molecular docking, 3D-QASR and molecular dynamics simulations of benzimidazole Pin1 inhibitors.

Pin1 (protein interacting with never-in-mitosis akinase-1) is a member of the family of peptidylprolyl cis-trans isomerases (PPIases) that specifically recognize and isomerize substrates containing phosphorylated Ser/Thr-Pro sequences. Pin1 is involved in many cellular processes and plays a key role in the cell cycle, transcriptional regulation, cell metabolism, proliferation and differentiation, and its abnormalities lead to degenerative and neoplastic diseases. Pin1 is highly expressed in human cancers and promotes the development of tumors by activating multiple oncogenes and inactivating multiple tumor suppressor genes, making it an attractive target for cancer therapy. In this study, we investigated the binding mechanism and conformational relationship between benzimidazole Pin1 inhibitors and Pin1 proteins by molecular docking, three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, binding free energy calculations and decomposition, and molecular dynamics simulations. Molecular docking and molecular dynamics simulations disclosed the most likely binding pose of benzimidazoles with the Pin1 protein. The results of 3D-QSAR modeling indicated that electrostatic fields, hydrophobic fields and hydrogen bonding play important roles in the binding process of inhibitors to proteins. The binding free energy calculations and energy decomposition indicated that Lys63, Arg69, Cys113, Leu122, Met130, and Ser154 may be key residues in the binding of benzimidazole-based inhibitors to the Pin1 protein. This study provides an important theoretical basis for the design and optimization of benzimidazole compounds.

Design, Synthesis, Structure-Activity Relationship, and Three-Dimensional Quantitative Structure-Activity Relationship of Fusarium Acid Derivatives and Analogues as Potential Fungicides.

In research related to fungicides, the development of compounds from natural products with high antifungal activity has attracted considerable attention. Fusaric acid (FA), an alkaloid isolated from the metabolites of Fusarium oxysporum, is an important precursor for developing pharmacologically active herbicides. In our previous work, we reported that FA has a wide range of inhibitory activities against 14 plant pathogenic fungi. In particular, it exhibited excellent antifugal effects on Colletotrichum higginsianum (EC50 = 31.7 μg/mL). Herein, to explore the practical application in the agricultural field, the design and synthesis of three series of FA derivatives and their inhibitory activities against plant pathogenic fungi were examined. Results demonstrated that the optimized FA derivatives had excellent inhibitory activities against C. higginsianum, Helminthosporium (Harpophora maydis), and Pyricularia grisea. In particular, the inhibitory activities were considerably improved when the 5-butyl groups of FA were substituted. The EC50 of C. higginsianum and P. grisea was only 1.2 and 12.0 μg/mL when 5-butylalkyl groups were substituted with 5-([1,1'-biphenyl]-4-yl) and 5-phenyl, respectively. Moreover, the safety index of target compounds, which was obtained from the treatment index of medicines, on rice seeds was evaluated. Finally, 16 leading compounds (H4, H22-H24, H27, H29, H30-H34, H37, H45, H50, H52, and H53) were obtained; they had considerable potential for additional modification and optimization as agricultural fungicides. Moreover, three-dimensional quantitative structure-activity relationship models were developed for obtaining a systematic structure-activity relationship profile to explore the possibility of more potent FA derivatives as novel fungicides.

Molecular design of environment-friendly amide herbicide substitutes with high efficacy, low phytotoxicity and medication safety

The primary goal of this investigation was to formulate an ecologically sustainable alternative to amide herbicides (AHs) characterized by robust herbicidal effectiveness, minimal corn phytotoxicity, and commendable pharmaceutical safety. We employed comparative molecular similarity index analysis (CoMSIA), a three-dimensional quantitative structure-activity relationship (3D-QSAR) model, which systematically outlined parameters such as herbicidal effectiveness, corn phytotoxicity, and AHs biodegradability. Subsequently, after thorough evaluation, we carefully selected a group of fourteen stable AH-substitute compounds known for their safety and environmental compatibility, considering aspects like pharmacokinetics, toxicokinetics, functional properties, and environmental friendliness. This resulted in a significant increase in herbicidal effectiveness, ranging from 21.64% to 34.07%, alongside a decrease in corn phytotoxicity within the range of 12.19–20.87%. Furthermore, we achieved an improvement in biodegradability, measured within the spectrum of 4.92–9.40%. Importantly, these changes also correlated with the reduction of hepatotoxicity, mutagenicity, and cutaneous health risks. Finally, we delved into the mechanisms underlying the improved herbicidal effectiveness, reduced corn phytotoxicity, and enhanced biodegradability of AHs substitutes through molecular docking and analysis of amino acid interactions. The investigation concluded that non-covalent forces governing the interaction between AHs substitutes and receptor proteins are crucial in determining herbicidal effectiveness, corn phytotoxicity, and biodegradability. Specifically, Van der Waals and electrostatic forces emerged as key factors governing the binding affinities of AH molecules with receptor proteins, both before and after modification. In summary, this study introduces innovative approaches in the field of agricultural chemical weeding technology and provides a theoretical framework for the environmentally responsible management of AHs herbicides.

In silico screening-based discovery of benzamide derivatives as inhibitors of Rho-associated kinase-1 (ROCK1)

As a pivotal node in modulating various cell behaviors, Rho-associated kinase-1 (ROCK1) has attracted significant attention as a promising therapeutic target in a variety of diseases. Benzamide has been widely reported as a ROCK1 inhibitors in recent years. To better understand its pharmacological properties and to explore its potential inhibitors, a series of ROCK1 inhibitors derived from N-methyl-4-(4-pyrazolidinyl) benzamides (MPBs) were investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) models, pharmacophore models, molecular docking, and molecular dynamics (MD) simulation. The comparative Molecular Field Analysis (CoMFA) model (q2 = 0.616, R2 = 0.972, ONC = 4, and r2 pred = 0.983) and the best Comparative Molecular Similarity Indices Analysis (CoMSIA) model (q2 = 0.740, R2 = 0.982, ONC = 6, and r2 pred = 0.824) exhibited reliable predictability with satisfactory validation parameters. In the subsequent virtual screening, VS03 and VS05 were identified to have superior predicted activities and higher docking scores, meanwhile they demonstrated to be reasonably stable in the binding pocket through MD simulations. These results provide a significant theoretical direction for the rational design and development of novel ROCK1 inhibitors. Communicated by Ramaswamy H. Sarma

Inactivating Activities and Mechanism of Imidazo[1,2-c]pyrimidin-5(6H)-one Nucleoside Derivatives Incorporating a Sulfonamide Scaffold.

Twenty-eight imidazo[1,2-c]pyrimidin-5(6H)-one nucleoside derivatives incorporating a sulfonamide scaffold with preferable inactivating activities on pepper mild mottle virus (PMMoV) were designed and synthesized. Then, compound B29 with illustrious inactivating activity against PMMoV was received on the basis of the three-dimensional quantitative structure-activity relationship (3D-QSAR) model, with the EC50 of 11.4 μg/mL, which was superior to ningnanmycin (65.8 μg/mL) and template molecule B16 (15.3 μg/mL). Furthermore, (1) transmission electron microscopy (TEM) indicated that B29 could cause severe fracture of virions; (2) microscale thermophoresis (MST) and molecular docking further demonstrated that B29 had faintish binding affinities with PMMoV CPR62A (Kd = 202.84 μM), PMMoV CPL144A (Kd = 141.57 μM), and PMMoV CPR62A,L144A (Kd = 332.06 μM) compared to PMMoV CP (Kd = 4.76 μM); and (3) western blot and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results of pCB-GFP-PMMoV CPR62A, pCB-GFP-PMMoV CPL144A, and pCB-GFP-PMMoV CPR62A,L144A were consistent with MST and confocal. In brief, the above results indicated that the amino acids at positions 62 and 144 of PMMoV CP might be the key amino acid sites of B29 acted on.

Synthesis of Pogostone-Inspired Dehydroacetic Acid Derivatives and Their Antifungal Activity against Sclerotinia sclerotiorum (Lib.) de Bary.

In an effort to exploit the natural antifungal pogostone, its simplified scaffold dehydroacetic acid (DHA) was used as a lead compound to semi-synthesize 56 DHA derivatives (I1-48, II, III, and IV1-6). Among them, compound IV4 exhibited the most potent antifungal activity with 11.0 μM EC50 against mycelial growth of Sclerotinia sclerotiorum (Lib.) de Bary whose sclerotia production was also completely suppressed at this concentration. Furthermore, IV4 could completely inhibit infection cushion formation of S. sclerotiorum on rape leaves and achieved a preventive efficacy of 90.2 % at 500 μM, which was on the same level as that of commercial boscalid at 30 μM (88.7 %). The results of physiological and ultrastructural studies indicated that IV4 might disrupt the cell membrane permeability or induce the imbalance of mitochondrial membrane potential homeostasis to exert the antifungal mode of action. Besides, the robust and predicative three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed and discussed herein.

Discovery of Novel Isoxazoline Derivatives Containing Diaryl Ether against Fall Armyworms

With the continuous evolution of insect resistance, it is a tremendous challenge to control the fall armyworm (Spodoptera frugiperda) with traditional insecticides. To solve this pending issue, a series of novel isoxazoline derivatives containing diaryl ether structures were designed and synthesized, and most of the target compounds exhibited excellent insecticidal activity. Based on the three-dimensional quantitative structure-activity relationship (3D-QSAR) model analysis, we further optimized the molecular structure with compound L35 obtained and tested for its activity. Compound L35 (LC50 = 1.69 mg/L) exhibited excellent insecticidal activity against S. frugiperda, which was better than those of commercial fipronil (LC50 = 70.78 mg/L) and indoxacarb (LC50 = 5.37 mg/L). The enzyme-linked immunosorbent assay showed that L35 could upregulate the levels of GABA in insects. In addition, molecular docking and transcriptomic results also indicated that compound L35 may affect the nervous system of S. frugiperda by acting on GABA receptors. Notably, through high-performance liquid chromatography (HPLC), we were able to obtain the two enantiomers of compound L35, and the insecticidal activity test revealed that S-(+)-L35 was 44 times more active than R-(-)-L35 against S. frugiperda. This study established the chemistry basis and mechanistic foundations for the future development of pesticide candidates against fall armyworms.

Discovery of a Novel Class of Acylthiourea-Containing Isoxazoline Insecticides against Plutella xylostella.

Isoxazoline structures are widely found in natural products and are rich in biological activities. This study discloses the development of a series of novel isoxazoline derivatives by introducing acylthiourea fragments to access insecticidal activity. All synthetic compounds were examined for their insecticidal activity against Plutella xylostella, with results showing moderate to strong activity. Based on this, the structure-activity relationship analysis was carried out via the constructed three-dimensional quantitative structure-activity relationship model to further guide the structure optimization, resulting in the optimal compound 32. The LC50 of compound 32 against Plutella xylostella was 0.26 mg/L, demonstrating better activity than the positive control, ethiprole (LC50 = 3.81 mg/L), avermectin (LC50 = 12.32 mg/L), and compounds 1-31. The insect GABA enzyme-linked immunosorbent assay demonstrated that compound 32 might act on the insect GABA receptor, and the molecular docking assay further illustrated the mode of action of compound 32 with the GABA receptor. In addition, the proteomics analysis indicated that the action of compound 32 on Plutella xylostella was multi-pathway.

Discovery of ANO1 Inhibitors based on Machine learning and molecule docking simulation approaches

Calcium-activated chloride channels (CaCCs) are chloride channels that are regulated according to intracellular calcium ion concentrations. The channel protein ANO1 is widely present in cells and is involved in physiological activities including cellular secretion, signaling, cell proliferation and vasoconstriction and diastole. In this study, the ANO1 inhibitors were investigated with machine learning and molecular simulation. Two-dimensional structure-activity relationship (2D-SAR) and three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for the qualitative and quantitative prediction of ANO1 inhibitors. The results showed that the prediction accuracies of the model were 85.9% and 87.8% for the training and test sets, respectively, and 85.9% and 87.8% for the rotating forest (RF) in the 2D-SAR model. The CoMFA and CoMSIA methods were then used for 3D QSAR modeling of ANO1 inhibitors, respectively. The q2 coefficients for model cross-validation were all greater than 0.5, implying that we were able to obtain a stable model for drug activity prediction. Molecular docking was further used to simulate the interactions between the five most promising compounds predicted by the model and the ANO1 protein. The total score for the docking results between all five compounds and the target protein was greater than 6, indicating that they interacted strongly in the form of hydrogen bonds. Finally, simulations of amino acid mutations around the docking cavity of the target proteins showed that each molecule had two or more sites of reduced affinity following a single mutation, indicating outstanding specificity of the screened drug molecules and their protein ligands.