SAR and QSAR in Environmental Research最新文献_第10页

Functionally substituted 2-aminothiazoles as antimicrobial agents: in vitro and in silico evaluation. 功能取代的2-氨基噻唑作为抗菌药物:体外和硅评价。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-05-01 DOI: 10.1080/1062936X.2023.2214869

A Petrou, V Kartsev, A Geronikaki, J Glamočlija, A Ciric, M Sokovic

{"title":"Functionally substituted 2-aminothiazoles as antimicrobial agents: in vitro and in silico evaluation.","authors":"A Petrou, V Kartsev, A Geronikaki, J Glamočlija, A Ciric, M Sokovic","doi":"10.1080/1062936X.2023.2214869","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2214869","url":null,"abstract":"Nine new functionally substituted derivatives of 2-aminothiazole were evaluated for antimicrobial activity using microdilution method against the panel of eight bacterial and eight fungal strains. Evaluation of antibacterial activity revealed that compounds are potent antibacterial agents, more active than ampicillin and streptomycin except of some compounds against B. cereus and En. cloacae. The best compound appeared to be compound 8. The most sensitive bacteria appeared to be En. cloacae, while L. monocytogenes was the most resistant. Compounds also exhibited good antifungal activity much better than two reference drugs, ketoconazole and bifonazole. Compound 1 exhibited the best antifungal activity. The most sensitive fungus was T. viride, while A. fumigatus was the most resistant. Bacteria as well as fungi in general showed different sensitivity towards compounds tested. Molecular docking studies revealed that MurB inhibition is probably involved in the mechanism of antibacterial activity, while CYP51 of C. albicans is responsible for the mechanism of antifungal activity. Finally, it should be mentioned that all compounds displayed very good druglikeness scores.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 5","pages":"395-414"},"PeriodicalIF":3.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9560670","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: 1

Molecular docking-based interaction studies on imidazo[1,2-a] pyridine ethers and squaramides as anti-tubercular agents. 咪唑[1,2-a]吡啶醚与角酰胺类抗结核药物分子对接相互作用研究。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2225872

S Ahmed, A E Prabahar, A K Saxena

{"title":"Molecular docking-based interaction studies on imidazo[1,2-a] pyridine ethers and squaramides as anti-tubercular agents.","authors":"S Ahmed, A E Prabahar, A K Saxena","doi":"10.1080/1062936X.2023.2225872","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2225872","url":null,"abstract":"Development of new anti-tubercular agents is required in the wake of resistance to the existing and newly approved drugs through novel-validated targets like ATP synthase, etc. The major limitation of poor correlation between docking scores and biological activity by SBDD was overcome by a novel approach of quantitatively correlating the interactions of different amino acid residues present in the target protein structure with the activity. This approach well predicted the ATP synthase inhibitory activity of imidazo[1,2-a] pyridine ethers and squaramides (r = 0.84) in terms of Glu65b interactions. Hence, the models were developed on combined (r = 0.78), and training (r = 0.82) sets of 52, and 27 molecules, respectively. The training set model well predicted the diverse dataset (r = 0.84), test set (r = 0.755), and, external dataset (rext = 0.76). This model predicted three compounds from a focused library generated by incorporating the essential features of the ATP synthase inhibition with the pIC50 values in the range of 0.0508-0.1494 µM. Molecular dynamics simulation studies ascertain the stability of the protein structure and the docked poses of the ligands. The developed model(s) may be useful in the identification and optimization of novel compounds against TB.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 6","pages":"435-457"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9885726","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

Development of binary classification models for grouping hydroxylated polychlorinated biphenyls into active and inactive thyroid hormone receptor agonists. 羟基化多氯联苯为活性和非活性甲状腺激素受体激动剂的二元分类模型的建立。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2207039

L K Akinola, A Uzairu, G A Shallangwa, S E Abechi

{"title":"Development of binary classification models for grouping hydroxylated polychlorinated biphenyls into active and inactive thyroid hormone receptor agonists.","authors":"L K Akinola, A Uzairu, G A Shallangwa, S E Abechi","doi":"10.1080/1062936X.2023.2207039","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2207039","url":null,"abstract":"Some adverse effects of hydroxylated polychlorinated biphenyls (OH-PCBs) in humans are presumed to be initiated via thyroid hormone receptor (TR) binding. Due to the trial-and-error approach adopted for OH-PCB selection in previous studies, experiments designed to test the TR binding hypothesis mostly utilized inactive OH-PCBs, leading to considerable waste of time, effort and other material resources. In this paper, linear discriminant analysis (LDA) and binary logistic regression (LR) were used to develop classification models to group OH-PCBs into active and inactive TR agonists using radial distribution function (RDF) descriptors as predictor variables. The classifications made by both LDA and LR models on the training set compounds resulted in an accuracy of 84.3%, sensitivity of 72.2% and specificity of 90.9%. The areas under the ROC curves, constructed with the training set data, were found to be 0.872 and 0.880 for LDA and LR models, respectively. External validation of the models revealed that 76.5% of the test set compounds were correctly classified by both LDA and LR models. These findings suggest that the two models reported in this paper are good and reliable for classifying OH-PCB congeners into active and inactive TR agonists.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 4","pages":"267-284"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9562006","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

Synthesis, antiproliferative and 4D-QSAR studies of thiadiazole derivatives bearing acrylamide moiety as EGFR inhibitors. 含丙烯酰胺部分的EGFR抑制剂噻二唑衍生物的合成、抗增殖及4D-QSAR研究。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2214870

B Y Cai, T S Zhao, D G Qin, G G Tu

引用次数: 0

Understanding mechanism governing the inflammatory potential of metal oxide nanoparticles using periodic table-based descriptors: a nano-QSAR approach. 利用基于元素周期表的描述符了解控制金属氧化物纳米颗粒炎症潜能的机制:纳米qsar方法。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2227557

J Roy, K Roy

{"title":"Understanding mechanism governing the inflammatory potential of metal oxide nanoparticles using periodic table-based descriptors: a nano-QSAR approach.","authors":"J Roy, K Roy","doi":"10.1080/1062936X.2023.2227557","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2227557","url":null,"abstract":"Metal oxide nanoparticles (MeOxNPs) can be made safer by understanding the interaction between the immune system and nanoparticles. A nano-quantitative structure-activity relationship (nano-QSAR) model can be used to evaluate nanoparticle risk quickly and conveniently. The present work attempts to develop nano-QSAR models to determine the inflammatory potential of MeOxNPs based on the THP-1 cell line. A comprehensive dataset comprising 32 MeOxNPs was used to develop a regression model with fold change (FC) of pro-inflammatory cytokine interleukin (IL)-1beta (IL-1b) release in the THP-1 cell line as the endpoint. Further, the same number of MeOx NPs with varying doses was modelled for the cell viability [-ln(p/(1-p))] endpoint. The results obtained from regression models were statistically significant. The descriptors obtained from the developed predictive models inferred that dose, electronegativity and the presence of metal ions and oxygen can be responsible for IL-1β leakage from the THP-1 cell line. Based on our results, we can conclude that periodic table-based descriptors, incorporated into the QSAR models, are reliable for modelling pro-inflammatory potential. Researchers can use these comprehensive results to design metal oxide nanoparticles with lower toxicity and determine the cause of pro-inflammatory conditions induced by MeOxNPs.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 6","pages":"459-474"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9831128","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

Exploration of structural alerts and fingerprints for novel anticancer therapeutics: a robust classification-QSAR dependent structural analysis of drug-like MMP-9 inhibitors. 探索新型抗癌疗法的结构警报和指纹图谱:药物样MMP-9抑制剂的强大分类- qsar依赖结构分析。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2209737

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

{"title":"Exploration of structural alerts and fingerprints for novel anticancer therapeutics: a robust classification-QSAR dependent structural analysis of drug-like MMP-9 inhibitors.","authors":"S Banerjee, S K Baidya, B Ghosh, T Jha, N Adhikari","doi":"10.1080/1062936X.2023.2209737","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2209737","url":null,"abstract":"Among various matrix metalloproteinases (MMPs), overexpression of MMP9 has been established as a key player in a variety of cancers. Therefore, MMP9 has emerged as a promising biomolecule that may be targeted to design potent inhibitors as novel anticancer therapeutics. In this study, a large database containing 1,123 drug-like MMP-9 inhibitors was considered for robust classification-dependent fragment-based QSAR study through SARpy, Bayesian classification, and recursive partitioning analyses and were validated by both internal and external validation techniques. In a nutshell, all these classification-dependent techniques revealed some common structural alerts and sub-structural fingerprints responsible for modulating MMP-9 inhibition. These observations are in agreement with the interactions obtained from the ligand-bound co-crystal structures of MMP-9 justifying the robustness of the current study. Finally, based on these crucial structural fragments, some new lead compounds were designed and further validated by the binding mode of interaction analysis. Therefore, these findings may be beneficial in designing novel and potential MMP-9 inhibitors in the future as a weapon to combat several cancers.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 4","pages":"299-319"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9516885","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

Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey. 利用机器学习技术预测马来西亚克卢卢蜂蜜中使用立法会tof - ms检测到的化合物的血脑屏障通透性。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2230868

R Edros, T W Feng, R H Dong

{"title":"Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey.","authors":"R Edros, T W Feng, R H Dong","doi":"10.1080/1062936X.2023.2230868","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2230868","url":null,"abstract":"Current in silico modelling techniques, such as molecular dynamics, typically focus on compounds with the highest concentration from chromatographic analyses for bioactivity screening. Consequently, they reduce the need for labour-intensive in vitro studies but limit the utilization of extensive chromatographic data and molecular diversity for compound classification. Compound permeability across the blood-brain barrier (BBB) is a key concern in central nervous system (CNS) drug development, and this limitation can be addressed by applying cheminformatics with codeless machine learning (ML). Among the four models developed in this study, the Random Forest (RF) algorithm with the most robust performance in both internal and external validation was selected for model construction, with an accuracy (ACC) of 87.5% and 86.9% and area under the curve (AUC) of 0.907 and 0.726, respectively. The RF model was deployed to classify 285 compounds detected using liquid chromatography quadrupole time-of-flight mass spectrometry (LCQTOF-MS) in Kelulut honey; of which, 140 compounds were screened with 94 descriptors. Seventeen compounds were predicted to permeate the BBB, revealing their potential as drugs for treating neurodegenerative diseases. Our results highlight the importance of employing ML pattern recognition to identify compounds with neuroprotective potential from the entire pool of chromatographic data.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 6","pages":"475-500"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9831155","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

Prediction of soil ecotoxicity against Folsomia candida using acute and chronic endpoints. 利用急性和慢性终点预测土壤对念珠菌的生态毒性。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2211350

R Paul, J Roy, K Roy

{"title":"Prediction of soil ecotoxicity against Folsomia candida using acute and chronic endpoints.","authors":"R Paul, J Roy, K Roy","doi":"10.1080/1062936X.2023.2211350","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2211350","url":null,"abstract":"Soil invertebrates serve as great biological indicators of soil quality. However, there are very few in silico models developed so far on the soil toxicity of chemicals against soil invertebrates due to paucity of data. In this study, three available soil ecotoxicity data (pLC50, pLOEL and pNOEL) against the soil invertebrate Folsomia candida were collected from the ECOTOX database (cfpub.epa.gov/ecotox) and subjected to quantitative structure-activity relationship (QSAR) analysis using 2D descriptors. The collected data for each endpoint were initially curated and used to develop a partial least squares (PLS) regression model based on the features selected through a genetic algorithm followed by the best subset selection. Both internal and external validation metrics of the models' predictions are well-balanced and within the acceptable range as per the Organization for the Economic Cooperation and Development (OECD) criteria. From the developed models, it has been found that molecular weight and presence of phosphate group, electron donor groups, and polyhalogen substitution have a significant impact on the soil ecotoxicity. The soil ecotoxicological risk assessment of organic chemicals can therefore be prioritized by these features. With the availability of additional data in the future, the models may be further refined for more precise predictions.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 4","pages":"321-340"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9881128","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

QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm. 基于二元土狼优化算法的多系列抗真菌药QSAR分类模型。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2208374

A M Al-Fakih, M K Qasim, Z Y Algamal, A M Alharthi, M H Zainal-Abidin

{"title":"QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm.","authors":"A M Al-Fakih, M K Qasim, Z Y Algamal, A M Alharthi, M H Zainal-Abidin","doi":"10.1080/1062936X.2023.2208374","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2208374","url":null,"abstract":"One of the recently developed metaheuristic algorithms, the coyote optimization algorithm (COA), has shown to perform better in a number of difficult optimization tasks. The binary form, BCOA, is used in this study as a solution to the descriptor selection issue in classifying diverse antifungal series. Z-shape transfer functions (ZTF) are evaluated to verify their efficiency in improving BCOA performance in QSAR classification based on classification accuracy (CA), the geometric mean of sensitivity and specificity (G-mean), and the area under the curve (AUC). The Kruskal-Wallis test is also applied to show the statistical differences between the functions. The efficacy of the best suggested transfer function, ZTF4, is further assessed by comparing it to the most recent binary algorithms. The results prove that ZTF, especially ZTF4, significantly improves the performance of the original BCOA. The ZTF4 function yields the best CA and G-mean of 99.03% and 0.992%, respectively. It shows the fastest convergence behaviour compared to other binary algorithms. It takes the fewest iterations to reach high classification performance and selects the fewest descriptors. In conclusion, the obtained results indicate the ability of the ZTF4-based BCOA to find the smallest subset of descriptors while maintaining the best classification accuracy performance.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 4","pages":"285-298"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9509448","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

Predictive profiling of gram-negative antibiotics in CagA oncoprotein inactivation: a molecular dynamics simulation approach. 革兰氏阴性抗生素在CagA癌蛋白失活中的预测分析:分子动力学模拟方法。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-04-01 DOI: 10.1080/1062936X.2023.2230876

N Varshney, D Kashyap, S K Behra, V Saini, A Chaurasia, S Kumar, H C Jha

{"title":"Predictive profiling of gram-negative antibiotics in CagA oncoprotein inactivation: a molecular dynamics simulation approach.","authors":"N Varshney, D Kashyap, S K Behra, V Saini, A Chaurasia, S Kumar, H C Jha","doi":"10.1080/1062936X.2023.2230876","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2230876","url":null,"abstract":"Gastric cancer (GC) is the fifth most prevalent form of cancer worldwide. CagA - positive Helicobacter pylori infects more than 60% of the human population. Moreover, chronic infection of CagA-positive H. pylori can directly affect GC incidence. In the current study, we have repurposed FDA-approved antibiotics that are viable alternatives to current regimens and can potentially be used as combination therapy against the CagA of H. pylori. The 100 FDA-approved gram negative antibiotics were screened against CagA protein using the AutoDock 4.2 tool. Further, top nine compounds were selected based on higher binding affinity with CagA. The trajectory analysis of MD simulations reflected that binding of these drugs with CagA stabilizes the system. Nonetheless, atomic density map and principal component analysis also support the notion of stable binding of antibiotics to the protein. The residues ASP96, GLN100, PRO184, and THR185 of compound cefpiramide, doxycycline, delafloxacin, metacycline, oxytetracycline, and ertapenem were involved in the binding with CagA protein. These residues are crucial for the CagA that aids in entry or pathogenesis of the bacterium. The screened FDA-approved antibiotics have a potential druggability to inhibit CagA and reduce the progression of H. pylori borne diseases.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 6","pages":"501-521"},"PeriodicalIF":3.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9853514","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