SAR and QSAR in Environmental Research最新文献_第3页

QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm. 基于混沌斑鬣狗优化算法的离子液体酶抑制毒性 QSAR 模型。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-09-01 Epub Date: 2024-09-30 DOI: 10.1080/1062936X.2024.2404853

A M Alharthi, N A Al-Thanoon, A M Al-Fakih, Z Y Algamal

{"title":"QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm.","authors":"A M Alharthi, N A Al-Thanoon, A M Al-Fakih, Z Y Algamal","doi":"10.1080/1062936X.2024.2404853","DOIUrl":"10.1080/1062936X.2024.2404853","url":null,"abstract":"Ionic liquids (ILs) have attracted considerable interest due to their unique properties and prospective uses in various industries. However, their potential toxicity, particularly regarding enzyme inhibition, has become a growing concern. In this study, a QSAR model was proposed to predict the enzyme inhibition toxicity of ILs. A dataset of diverse ILs with corresponding toxicity data against three enzymes was compiled. Molecular descriptors that capture the physicochemical, structural, and topological properties of the ILs were calculated. To optimize the selection of descriptors and develop a robust QSAR model, the chaotic spotted hyena optimization algorithm, a novel nature-inspired metaheuristic, was employed. The proposed algorithm efficiently searches for an optimal subset of descriptors and model parameters, enhancing the predictive performance and interpretability of the QSAR model. The developed model exhibits excellent predictive capability, with high classification accuracy and low computation time. Sensitivity analysis and molecular interpretation of the selected descriptors provide insights into the critical structural features influencing the toxicity of ILs. This study showcases the successful application of the chaotic spotted hyena optimization algorithm in QSAR modelling and contributes to a better understanding of the toxicity mechanisms of ILs, aiding in the design of safer alternatives for industrial applications.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"757-770"},"PeriodicalIF":2.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142353052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deciphering Cathepsin K inhibitors: a combined QSAR, docking and MD simulation based machine learning approaches for drug design. 解密 Cathepsin K 抑制剂：基于 QSAR、对接和 MD 模拟的机器学习药物设计组合方法。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-09-01 Epub Date: 2024-10-09 DOI: 10.1080/1062936X.2024.2405626

S Ilyas, J Lee, Y Hwang, Y Choi, D Lee

{"title":"Deciphering Cathepsin K inhibitors: a combined QSAR, docking and MD simulation based machine learning approaches for drug design.","authors":"S Ilyas, J Lee, Y Hwang, Y Choi, D Lee","doi":"10.1080/1062936X.2024.2405626","DOIUrl":"10.1080/1062936X.2024.2405626","url":null,"abstract":"Cathepsin K (CatK), a lysosomal cysteine protease, contributes to skeletal abnormalities, heart diseases, lung inflammation, and central nervous system and immune disorders. Currently, CatK inhibitors are associated with severe adverse effects, therefore limiting their clinical utility. This study focuses on exploring quantitative structure-activity relationships (QSAR) on a dataset of CatK inhibitors (1804) compiled from the ChEMBL database to predict the inhibitory activities. After data cleaning and pre-processing, a total of 1568 structures were selected for exploratory data analysis which revealed physicochemical properties, distributions and statistical significance between the two groups of inhibitors. PubChem fingerprinting with 11 different machine-learning classification models was computed. The comparative analysis showed the ET model performed well with accuracy values for the training set (0.999), cross-validation (0.970) and test set (0.977) in line with OECD guidelines. Moreover, to gain structural insights on the origin of CatK inhibition, 15 diverse molecules were selected for molecular docking. The CatK inhibitors (1 and 2) exhibited strong binding energies of -8.3 and -7.2 kcal/mol, respectively. MD simulation (300 ns) showed strong structural stability, flexibility and interactions in selected complexes. This synergy between QSAR, docking, MD simulation and machine learning models strengthen our evidence for developing novel and resilient CatK inhibitors.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"771-793"},"PeriodicalIF":2.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142392951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Discovery of novel chemotype inhibitors targeting Anaplastic Lymphoma Kinase receptor through ligand-based pharmacophore modelling. 通过基于配体的药理模型，发现针对淋巴瘤激酶受体的新型化学抑制剂。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-09-01 Epub Date: 2024-10-09 DOI: 10.1080/1062936X.2024.2406398

I El-Jundi, S Daoud, M O Taha

{"title":"Discovery of novel chemotype inhibitors targeting Anaplastic Lymphoma Kinase receptor through ligand-based pharmacophore modelling.","authors":"I El-Jundi, S Daoud, M O Taha","doi":"10.1080/1062936X.2024.2406398","DOIUrl":"10.1080/1062936X.2024.2406398","url":null,"abstract":"Anaplastic Lymphoma Kinase (ALK) is a receptor tyrosine kinase within the insulin receptor superfamily. Alterations in ALK, such as rearrangements, mutations, or amplifications, have been detected in various tumours, including lymphoma, neuroblastoma, and non-small cell lung cancer. In this study, we outline a computational workflow designed to uncover new inhibitors of ALK. This process starts with a ligand-based exploration of the pharmacophoric space using 13 diverse sets of ALK inhibitors. Subsequently, quantitative structure-activity relationship (QSAR) modelling is employed in combination with a genetic function algorithm to identify the optimal combination of pharmacophores and molecular descriptors capable of elucidating variations in anti-ALK bioactivities within a compiled list of inhibitors. The successful QSAR model revealed three pharmacophores, two of which share three similar features, prompting their merger into a single pharmacophore model. The merged pharmacophore was used as a 3D search query to mine the National Cancer Institute (NCI) database for novel anti-ALK leads. Subsequent in vitro bioassay of the top 40 hits identified two compounds with low micromolar IC50 values. Remarkably, one of the identified leads possesses a novel chemotype compared to known ALK inhibitors.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"795-815"},"PeriodicalIF":2.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142392952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pinpointing prime structural attributes of potential MMP-2 inhibitors comprising alkyl/arylsulfonyl pyrrolidine scaffold: a ligand-based molecular modelling approach validated by molecular dynamics simulation analysis. 确定包含烷基/芳磺酰基吡咯烷支架的潜在 MMP-2 抑制剂的主要结构属性：一种通过分子动力学模拟分析验证的基于配体的分子建模方法。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-08-01 Epub Date: 2024-08-28 DOI: 10.1080/1062936X.2024.2389822

S K Baidya, S Banerjee, B Ghosh, T Jha, N Adhikari

{"title":"Pinpointing prime structural attributes of potential MMP-2 inhibitors comprising alkyl/arylsulfonyl pyrrolidine scaffold: a ligand-based molecular modelling approach validated by molecular dynamics simulation analysis.","authors":"S K Baidya, S Banerjee, B Ghosh, T Jha, N Adhikari","doi":"10.1080/1062936X.2024.2389822","DOIUrl":"10.1080/1062936X.2024.2389822","url":null,"abstract":"MMP-2 overexpression is strongly related to several diseases including cancer. However, none of the MMP-2 inhibitors have been marketed as drug candidates due to various adverse effects. Here, a set of sulphonyl pyrrolidines was subjected to validation of molecular modelling followed by binding mode analysis to explore the crucial structural features required for the discovery of promising MMP-2 inhibitors. This study revealed the importance of hydroxamate as a potential zinc-binding group compared to the esters. Importantly, hydrophobic and sterical substituents were found favourable at the terminal aryl moiety attached to the sulphonyl group. The binding interaction study revealed that the S1' pocket of MMP-2 similar to 'a basketball passing through a hoop' allows the aryl moiety for proper fitting and interaction at the active site to execute potential MMP-2 inhibition. Again, the sulphonyl pyrrolidine moiety can be a good fragment necessary for MMP-2 inhibition. Moreover, some novel MMP-2 inhibitors were also reported. They showed the significance of the 3rd position substitution of the pyrrolidine ring to produce interaction inside S2' pocket. The current study can assist in the design and development of potential MMP-2 inhibitors as effective drug candidates for the management of several diseases including cancers in the future.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"665-692"},"PeriodicalIF":2.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142081338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting repurposed drugs targeting the NS3 protease of dengue virus using machine learning-based QSAR, molecular docking, and molecular dynamics simulations. 利用基于机器学习的 QSAR、分子对接和分子动力学模拟预测针对登革热病毒 NS3 蛋白酶的再利用药物。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-08-01 Epub Date: 2024-08-30 DOI: 10.1080/1062936X.2024.2392677

Y Chongjun, A M S Nasr, M A M Latif, M B A Rahman, E Marlisah, B A Tejo

{"title":"Predicting repurposed drugs targeting the NS3 protease of dengue virus using machine learning-based QSAR, molecular docking, and molecular dynamics simulations.","authors":"Y Chongjun, A M S Nasr, M A M Latif, M B A Rahman, E Marlisah, B A Tejo","doi":"10.1080/1062936X.2024.2392677","DOIUrl":"10.1080/1062936X.2024.2392677","url":null,"abstract":"Dengue fever, prevalent in Southeast Asian countries, currently lacks effective pharmaceutical interventions for virus replication control. This study employs a strategy that combines machine learning (ML)-based quantitative-structure-activity relationship (QSAR), molecular docking, and molecular dynamics simulations to discover potential inhibitors of the NS3 protease of the dengue virus. We used nine molecular fingerprints from PaDEL to extract features from the NS3 protease dataset of dengue virus type 2 in the ChEMBL database. Feature selection was achieved through the low variance threshold, F-Score, and recursive feature elimination (RFE) methods. Our investigation employed three ML models - support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) - for classifier development. Our SVM model, combined with SVM-RFE, had the best accuracy (0.866) and ROC_AUC (0.964) in the testing set. We identified potent inhibitors on the basis of the optimal classifier probabilities and docking binding affinities. SHAP and LIME analyses highlighted the significant molecular fingerprints (e.g. ExtFP69, ExtFP362, ExtFP576) involved in NS3 protease inhibitory activity. Molecular dynamics simulations indicated that amphotericin B exhibited the highest binding energy of -212 kJ/mol and formed a hydrogen bond with the critical residue Ser196. This approach enhances NS3 protease inhibitor identification and expedites the discovery of dengue therapeutics.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"707-728"},"PeriodicalIF":2.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142111525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantitative structure-insecticidal activity of essential oils on the human head louse (Pediculus humanus capitis). 精油对人类头虱（Pediculus humanus capitis）的定量结构-杀虫活性。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-08-01 Epub Date: 2024-08-30 DOI: 10.1080/1062936X.2024.2394497

P R Duchowicz, D O Bennardi, S E Fioressi, D E Bacelo

{"title":"Quantitative structure-insecticidal activity of essential oils on the human head louse (Pediculus humanus capitis).","authors":"P R Duchowicz, D O Bennardi, S E Fioressi, D E Bacelo","doi":"10.1080/1062936X.2024.2394497","DOIUrl":"10.1080/1062936X.2024.2394497","url":null,"abstract":"In the search for natural and non-toxic products alternatives to synthetic pesticides, the fumigant and repellent activities of 35 essential oils are predicted in the human head louse (Pediculus humanus capitis) through the Quantitative Structure-Activity Relationships (QSAR) theory. The number of constituents of essential oils with weight percentage composition greater than 1% varies from 1 to 15, encompassing up to 213 structurally diverse compounds in the entire dataset. The 27,976 structural descriptors used to characterizing these complex mixtures are calculated as linear combinations of non-conformational descriptors for the components. This approach is considered simple enough to evaluate the effects that changes in the composition of each component could have on the studied bioactivities. The best linear regression models found, obtained through the Replacement Method variable subset selection method, are applied to predict 13 essential oils from a previous study with unknown property data. The results show that the simple methodology applied here could be useful for predicting properties of interest in complex mixtures such as essential oils.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"693-706"},"PeriodicalIF":2.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142111526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robustaflavone as a novel scaffold for inhibitors of native and auto-proteolysed human neutrophil elastase. 罗布麻黄酮作为一种新型支架，可用于抑制本地和自体蛋白水解的人类中性粒细胞弹性蛋白酶。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-08-01 Epub Date: 2024-09-09 DOI: 10.1080/1062936X.2024.2394498

V Singh, Y Kumar, S Bhatnagar

{"title":"Robustaflavone as a novel scaffold for inhibitors of native and auto-proteolysed human neutrophil elastase.","authors":"V Singh, Y Kumar, S Bhatnagar","doi":"10.1080/1062936X.2024.2394498","DOIUrl":"10.1080/1062936X.2024.2394498","url":null,"abstract":"Human neutrophil elastase (HNE) plays a key role in initiating inflammation in the cardiopulmonary and systemic contexts. Pathological auto-proteolysed two-chain (tc) HNE exhibits reduced binding affinity with inhibitors. Using AutoDock Vina v1.2.0, 66 flavonoid inhibitors, sivelestat and alvelestat were docked with single-chain (sc) HNE and tcHNE. Schrodinger PHASE v13.4.132 was used to generate a 3D-QSAR model. Molecular dynamics (MD) simulations were conducted with AMBER v18. The 3D-QSAR model for flavonoids with scHNE showed r2 = 0.95 and q2 = 0.91. High-activity compounds had hydrophobic A/A2 and C/C2 rings in the S1 subsite, with hydrogen bond donors at C5 and C7 positions of the A/A2 ring, and the C4' position of the B/B1 ring. All flavonoids except robustaflavone occupied the S1'-S2' subsites of tcHNE with decreased AutoDock binding affinities. During MD simulations, robustaflavone remained highly stable with both HNE forms. Principal Component Analysis suggested that robustaflavone binding induced structural stability in both HNE forms. Cluster analysis and free energy landscape plots showed that robustaflavone remained within the sc and tcHNE binding site throughout the 100 ns MD simulation. The robustaflavone scaffold likely inhibits both tcHNE and scHNE. It is potentially superior to sivelestat and alvelestat and can aid in developing therapeutics targeting both forms of HNE.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"35 8","pages":"729-756"},"PeriodicalIF":2.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142154857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Essential oil components interacting with insect odorant-binding proteins: a molecular modelling approach. 精油成分与昆虫气味结合蛋白的相互作用：分子建模方法。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-07-01 Epub Date: 2024-08-05 DOI: 10.1080/1062936X.2024.2382973

K Fuentes-Lopez, M Ahumedo-Monterrosa, J Olivero-Verbel, K Caballero-Gallardo

{"title":"Essential oil components interacting with insect odorant-binding proteins: a molecular modelling approach.","authors":"K Fuentes-Lopez, M Ahumedo-Monterrosa, J Olivero-Verbel, K Caballero-Gallardo","doi":"10.1080/1062936X.2024.2382973","DOIUrl":"10.1080/1062936X.2024.2382973","url":null,"abstract":"Essential oils (EOs) are natural products currently used to control arthropods, and their interaction with insect odorant-binding proteins (OBPs) is fundamental for the discovery of new repellents. This in silico study aimed to predict the potential of EO components to interact with odorant proteins. A total of 684 EO components from PubChem were docked against 23 odorant binding proteins from Protein Data Bank using AutoDock Vina. The ligands and proteins were optimized using Gaussian 09 and Sybyl-X 2.0, respectively. The nature of the protein-ligand interactions was characterized using LigandScout 4.0, and visualization of the binding mode in selected complexes was carried out by Pymol. Additionally, complexes with the best binding energy in molecular docking were subjected to 500 ns molecular dynamics simulations using Gromacs. The best binding affinity values were obtained for the 1DQE-ferutidine (-11 kcal/mol) and 2WCH-kaurene (-11.2 kcal/mol) complexes. Both are natural ligands that dock onto those proteins at the same binding site as DEET, a well-known insect repellent. This study identifies kaurene and ferutidine as possible candidates for natural insect repellents, offering a potential alternative to synthetic chemicals like DEET.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"591-610"},"PeriodicalIF":2.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141889978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods. 利用机器学习方法对 SARS-CoV-2 的 3CLpro 抑制剂进行 SAR 和 QSAR 研究。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-07-01 Epub Date: 2024-07-30 DOI: 10.1080/1062936X.2024.2375513

Y Zhang, Y Tian, A Yan

{"title":"A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods.","authors":"Y Zhang, Y Tian, A Yan","doi":"10.1080/1062936X.2024.2375513","DOIUrl":"10.1080/1062936X.2024.2375513","url":null,"abstract":"The 3C-like Proteinase (3CLpro) of novel coronaviruses is intricately linked to viral replication, making it a crucial target for antiviral agents. In this study, we employed two fingerprint descriptors (ECFP_4 and MACCS) to comprehensively characterize 889 compounds in our dataset. We constructed 24 classification models using machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), extreme Gradient Boosting (XGBoost), and Deep Neural Networks (DNN). Among these models, the DNN- and ECFP_4-based Model 1D_2 achieved the most promising results, with a remarkable Matthews correlation coefficient (MCC) value of 0.796 in the 5-fold cross-validation and 0.722 on the test set. The application domains of the models were analysed using dSTD-PRO calculations. The collected 889 compounds were clustered by K-means algorithm, and the relationships between structural fragments and inhibitory activities of the highly active compounds were analysed for the 10 obtained subsets. In addition, based on 464 3CLpro inhibitors, 27 QSAR models were constructed using three machine learning algorithms with a minimum root mean square error (RMSE) of 0.509 on the test set. The applicability domains of the models and the structure-activity relationships responded from the descriptors were also analysed.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"531-563"},"PeriodicalIF":2.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141793288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resveratrol analogues and metabolites selectively inhibit human and rat 11β-hydroxysteroid dehydrogenase 1 as the therapeutic drugs: structure-activity relationship and molecular dynamics analysis. 白藜芦醇类似物和代谢物选择性抑制人和大鼠 11β- 羟基类固醇脱氢酶 1 的治疗药物：结构-活性关系和分子动力学分析。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-07-01 Epub Date: 2024-08-14 DOI: 10.1080/1062936X.2024.2389817

C Hu, Y Zhai, H Lin, H Lu, J Zheng, C Wen, X Li, R S Ge, Y Liu, Q Zhu

{"title":"Resveratrol analogues and metabolites selectively inhibit human and rat 11β-hydroxysteroid dehydrogenase 1 as the therapeutic drugs: structure-activity relationship and molecular dynamics analysis.","authors":"C Hu, Y Zhai, H Lin, H Lu, J Zheng, C Wen, X Li, R S Ge, Y Liu, Q Zhu","doi":"10.1080/1062936X.2024.2389817","DOIUrl":"10.1080/1062936X.2024.2389817","url":null,"abstract":"Resveratrol is converted to various metabolites by gut microbiota. Human and rat liver 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) are critical for glucocorticoid activation, while 11β-HSD2 in the kidney does the opposite reaction. It is still uncertain whether resveratrol and its analogues selectively inhibit 11β-HSD1. In this study, the inhibitory strength, mode of action, structure-activity relationship (SAR), and docking analysis of resveratrol analogues on human, rat, and mouse 11β-HSD1 and 11β-HSD2 were performed. The inhibitory strength of these chemicals on human 11β-HSD1 was dihydropinosylvin (6.91 μM) > lunularin (45.44 μM) > pinostilbene (46.82 μM) > resveratrol (171.1 μM) > pinosylvin (193.8 μM) > others. The inhibitory strength of inhibiting rat 11β-HSD1 was pinostilbene (9.67 μM) > lunularin (17.39 μM) > dihydropinosylvin (19.83 μM) > dihydroresveratrol (23.07 μM) > dihydroxystilbene (27.84 μM) > others and dihydropinosylvin (85.09 μM) and pinostilbene (>100 μM) inhibited mouse 11β-HSD1. All chemicals did not inhibit human, rat, and mouse 11β-HSD2. It was found that dihydropinosylvin, lunularin, and pinostilbene were competitive inhibitors of human 11β-HSD1 and that pinostilbene, lunularin, dihydropinosylvin, dihydropinosylvin and dihydroxystilbene were mixed inhibitors of rat 11β-HSD1. Docking analysis showed that they bind to the steroid-binding site of human and rat 11β-HSD1. In conclusion, resveratrol and its analogues can selectively inhibit human and rat 11β-HSD1, and mouse 11β-HSD1 is insensitive to the inhibition of resveratrol analogues.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"641-663"},"PeriodicalIF":2.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141976460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0