SAR and QSAR in Environmental Research最新文献_第8页

Optimal selection of learning data for highly accurate QSAR prediction of chemical biodegradability: a machine learning-based approach. 学习数据的优化选择用于化学生物降解性的高精度QSAR预测：一种基于机器学习的方法。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-07-01 Epub Date: 2023-09-07 DOI: 10.1080/1062936X.2023.2251889

K Takeda, K Takeuchi, Y Sakuratani, K Kimbara

{"title":"Optimal selection of learning data for highly accurate QSAR prediction of chemical biodegradability: a machine learning-based approach.","authors":"K Takeda, K Takeuchi, Y Sakuratani, K Kimbara","doi":"10.1080/1062936X.2023.2251889","DOIUrl":"10.1080/1062936X.2023.2251889","url":null,"abstract":"Prior to the manufacture of new chemicals, regulations mandate a thorough review of the chemicals under risk management. This review involves evaluating their effects on the environment and human health. To assess these effects, a review report that conforms to the OECD Test Guidelines must be submitted to the regulatory body. One of the essential components of the report is an assessment of the biodegradability of chemicals in the environment. In addition to conventional methods, quantitative structure-activity relationship (QSAR) models have been developed to predict the properties of chemicals based on their structural features. Although a greater number of chemicals in the learning set may enhance the prediction accuracy, it may also lead to a decrease in accuracy due to the mixing of different structural features and properties of the chemicals. To improve the prediction performance, it is recommended to use only the appropriate data for biodegradability prediction as a training set. In this study, we propose a novel approach for the optimal selection of training set that enables a highly accurate prediction of the biodegradability of chemicals by QSAR. Our findings indicate that the proposed method effectively reduces the root mean squared error and improves the prediction accuracy.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 9","pages":"729-743"},"PeriodicalIF":3.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10578224","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

Exploring the Traditional Chinese Medicine (TCM) database chemical space to target I7L protease from monkeypox virus using molecular screening and simulation approaches. 利用分子筛选和模拟方法，探索中药数据库化学空间，靶向猴痘病毒I7L蛋白酶。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-07-01 Epub Date: 2023-09-07 DOI: 10.1080/1062936X.2023.2250723

A Khan, M Shahab, F Nasir, Y Waheed, A Alshammari, A Mohammad, G Zichen, R Li, D Q Wei

{"title":"Exploring the Traditional Chinese Medicine (TCM) database chemical space to target I7L protease from monkeypox virus using molecular screening and simulation approaches.","authors":"A Khan, M Shahab, F Nasir, Y Waheed, A Alshammari, A Mohammad, G Zichen, R Li, D Q Wei","doi":"10.1080/1062936X.2023.2250723","DOIUrl":"10.1080/1062936X.2023.2250723","url":null,"abstract":"In the current study, we used molecular screening and simulation approaches to target I7L protease from monkeypox virus (mpox) from the Traditional Chinese Medicines (TCM) database. Using molecular screening, only four hits TCM27763, TCM33057, TCM34450 and TCM31564 demonstrated better pharmacological potential than TTP6171 (control). Binding of these molecules targeted Trp168, Asn171, Arg196, Cys237, Ser240, Trp242, Glu325, Ser326, and Cys328 residues and may affect the function of I7L protease in in vitro assay. Moreover, molecular simulation revealed stable dynamics, tighter structural packing and less flexible behaviour for all the complexes. We further reported that the average hydrogen bonds in TCM27763, TCM33057, TCM34450 and TCM31564I7L complexes remained higher than the control drug. Finally, the BF energy results revealed -62.60 ± 0.65 for the controlI7L complex, for the TCM27763I7L complex -71.92 ± 0.70 kcal/mol, for the TCM33057I7L complex the BF energy was -70.94 ± 0.70 kcal/mol, for the TCM34450I7L the BF energy was -69.94 ± 0.85 kcal/mol while for the TCM31564I7L complex the BF energy was calculated to be -69.16 ± 0.80 kcal/mol. Although, we used stateoftheart computational methods, these are theoretical insights that need further experimental validation.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 9","pages":"689-708"},"PeriodicalIF":2.3,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10231255","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

MDM-Pred: a freely available web application for predicting the metabolism of drug-like compounds by the gut microbiota. MDM-Pred:一个免费的网络应用程序，用于预测肠道微生物群对药物类化合物的代谢。

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.2023.2214375

A S Kolodnitsky, N S Ionov, A V Rudik, A A Lagunin, D A Filimonov, V V Poroikov

{"title":"MDM-Pred: a freely available web application for predicting the metabolism of drug-like compounds by the gut microbiota.","authors":"A S Kolodnitsky, N S Ionov, A V Rudik, A A Lagunin, D A Filimonov, V V Poroikov","doi":"10.1080/1062936X.2023.2214375","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2214375","url":null,"abstract":"The human gut microbiota (HGM) comprises a complex population of microorganisms that significantly affect human health, including their influence on xenobiotics metabolism. Many pharmaceuticals are taken orally and thus come into contact with HGM, which can metabolize them. Therefore, it is necessary to evaluate the effect of HGM on the fate of pharmaceuticals in the organism. We have collected information about over 600 compounds from more than eighty publications. At least half of them (329 compounds) are known to be metabolized by HGM. We have used PASS (Prediction of Activity Spectra for Substances) software to build three classification SAR models for HGM-mediated drug metabolism prediction. The first model with an accuracy of prediction 0.85 estimates whether compounds will be metabolized by HGM. The second model with an average accuracy of prediction 0.92 estimates which bacterial genera are responsible for the drug metabolism. The third model with an average accuracy of prediction 0.92 estimates the biotransformation reactions during HGM-mediated drug metabolism. The created models were used to develop the freely available web application MDM-Pred (http://www.way2drug.com/mdm-pred/).","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 5","pages":"383-393"},"PeriodicalIF":3.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9558658","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

Selection of optimal validation methods for quantitative structure-activity relationships and applicability domain. 定量构效关系最优验证方法的选择及适用范围。

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.2023.2214871

K Héberger

{"title":"Selection of optimal validation methods for quantitative structure-activity relationships and applicability domain.","authors":"K Héberger","doi":"10.1080/1062936X.2023.2214871","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2214871","url":null,"abstract":"This brief literature survey groups the (numerical) validation methods and emphasizes the contradictions and confusion considering bias, variance and predictive performance. A multicriteria decision-making analysis has been made using the sum of absolute ranking differences (SRD), illustrated with five case studies (seven examples). SRD was applied to compare external and cross-validation techniques, indicators of predictive performance, and to select optimal methods to determine the applicability domain (AD). The ordering of model validation methods was in accordance with the sayings of original authors, but they are contradictory within each other, suggesting that any variant of cross-validation can be superior or inferior to other variants depending on the algorithm, data structure and circumstances applied. A simple fivefold cross-validation proved to be superior to the Bayesian Information Criterion in the vast majority of situations. It is simply not sufficient to test a numerical validation method in one situation only, even if it is a well defined one. SRD as a preferable multicriteria decision-making algorithm is suitable for tailoring the techniques for validation, and for the optimal determination of the applicability domain according to the dataset in question.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 5","pages":"415-434"},"PeriodicalIF":3.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9552328","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

Hybrid descriptors-conjoint indices: a case study on imidazole-thiourea containing glutaminyl cyclase inhibitors for design of novel anti-Alzheimer's candidates. 混合描述符-联合指数:咪唑-硫脲含谷氨酰胺环化酶抑制剂用于设计新型抗阿尔茨海默病候选药物的案例研究。

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.2023.2212175

K Bagri, A Kapoor, P Kumar, A Kumar

{"title":"Hybrid descriptors-conjoint indices: a case study on imidazole-thiourea containing glutaminyl cyclase inhibitors for design of novel anti-Alzheimer's candidates.","authors":"K Bagri, A Kapoor, P Kumar, A Kumar","doi":"10.1080/1062936X.2023.2212175","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2212175","url":null,"abstract":"Clinical studies show that the pyroglutamate alteration of amyloid-β (Aβ) catalysed by metalloenzyme glutaminyl cyclase results in the formation of the more neurotoxic pGlu-Aβ, and inhibition of glutaminyl cyclase can bring down the load of pGlu-Aβ in the brain and reduces Alzheimer's disease pathology with improvement in cognition. The present study involves the identification of activity-modulating structural features of 188 inhibitors of glutaminyl cyclase under the influence of index of ideality of correlation (IIC) and correlation intensity index (CII) as prediction parameters. The QSAR models developed employing IIC and CII were found to be statistically better and had better predictability than the models developed without them. The best model (split 4) showed r2 values of 0.8155 and 0.8218 for calibration and validation sets, respectively. The structural features classified from QSAR models were used to design some new glutaminyl cyclase inhibitors. Among the designed ligands, ligand 5 possesses the highest pIC50 value (6.30) as well as binding affinity (-6.2 kcal/mol) and creates hydrogen bonds with TRP 329, π-alkyl interactions with ILE 303 and TYR 299, π-π stacking interaction with PHE 325 and interactions with ZN 391. All novel designed ligands have better pIC50 values and binding affinities.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 5","pages":"361-381"},"PeriodicalIF":3.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9615242","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

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