SAR and QSAR in Environmental Research最新文献_第9页

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

A multiple linear regression approach to the estimation of carboxylic acid ester and lactone alkaline hydrolysis rate constants. 羧酸酯和内酯碱性水解速率常数的多元线性回归估计方法。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-03-01 Epub Date: 2023-03-23 DOI: 10.1080/1062936X.2023.2188608

J Lazare, C Tebes-Stevens, E J Weber

{"title":"A multiple linear regression approach to the estimation of carboxylic acid ester and lactone alkaline hydrolysis rate constants.","authors":"J Lazare, C Tebes-Stevens, E J Weber","doi":"10.1080/1062936X.2023.2188608","DOIUrl":"10.1080/1062936X.2023.2188608","url":null,"abstract":"Pesticides, pharmaceuticals, and other organic contaminants often undergo hydrolysis when released into the environment; therefore, measured or estimated hydrolysis rates are needed to assess their environmental persistence. An intuitive multiple linear regression (MLR) approach was used to develop robust QSARs for predicting base-catalyzed rate constants of carboxylic acid esters (CAEs) and lactones. We explored various combinations of independent descriptors, resulting in four primary models (two for lactones and two for CAEs), with a total of 15 and 11 parameters included in the CAE and lactone QSAR models, respectively. The most significant descriptors include pKa, electronegativity, charge density, and steric parameters. Model performance is assessed using Drug Theoretics and Cheminformatics Laboratory's DTC-QSAR tool, demonstrating high accuracy for both internal validation (r2 = 0.93 and RMSE = 0.41-0.43 for CAEs; r2 = 0.90-0.93 and RMSE = 0.38-0.46 for lactones) and external validation (r2 = 0.93 and RMSE = 0.43-0.45 for CAEs; r2 = 0.94-0.98 and RMSE = 0.33-0.41 for lactones). The developed models require only low-cost computational resources and have substantially improved performance compared to existing hydrolysis rate prediction models (HYDROWIN and SPARC).","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 3","pages":"183-210"},"PeriodicalIF":2.3,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547131/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9382596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of 2-amino-6-methyl-pyrimidine benzoic acids as ATP competitive casein kinase-2 (CK2) inhibitors using structure- and fragment-based design, docking and molecular dynamic simulation studies. 基于结构和片段的设计、对接和分子动力学模拟研究，设计2-氨基-6-甲基嘧啶苯甲酸作为ATP竞争性酪蛋白激酶-2 (CK2)抑制剂。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-03-01 DOI: 10.1080/1062936X.2023.2196091

S Patel, S Patel, K Tulsian, P Kumar, V K Vyas, M Ghate

{"title":"Design of 2-amino-6-methyl-pyrimidine benzoic acids as ATP competitive casein kinase-2 (CK2) inhibitors using structure- and fragment-based design, docking and molecular dynamic simulation studies.","authors":"S Patel, S Patel, K Tulsian, P Kumar, V K Vyas, M Ghate","doi":"10.1080/1062936X.2023.2196091","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2196091","url":null,"abstract":"Overexpression of casein kinase-2 (CK2) has been implicated in several carcinomas, mainly lung, prostate and acute myeloid leukaemia. The smaller nucleotide pocket compared to related kinases provides a great opportunity to discover newer ATP-competitive CK2 inhibitors. In this study, we have employed an integrated structure- and fragment-based design strategy to design 2-amino-6-methyl-pyrimidine benzoic acids as ATP-competitive CK2 inhibitors. A statistically significant four features-based E-pharmacophore (ARRR) model was used to screen 780,092 molecules. Further, the retrieved hits were considered for molecular docking study to identify essential binding interactions. At the same time, fragment-based virtual screening was performed using a dataset of 1,542,397 fragments. The identified hits and fragments were used as structure templates to rationalize the design of 2-amino-6-methyl-pyrimidine benzoic acids as newer CK2 inhibitors. Finally, the binding interactions of the designed hits were identified using an induced fit docking (IFD) study, and their stability was estimated by a molecular dynamics (MD) simulation study of 100 ns.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 3","pages":"211-230"},"PeriodicalIF":3.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9736321","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

Study of two combined series of triketones with HPPD inhibitory activity by molecular modelling. 用分子模拟方法研究具有HPPD抑制活性的两个联合系列三酮。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-03-01 DOI: 10.1080/1062936X.2023.2192521

L R Capucho, E F F da Cunha, M P Freitas

{"title":"Study of two combined series of triketones with HPPD inhibitory activity by molecular modelling.","authors":"L R Capucho, E F F da Cunha, M P Freitas","doi":"10.1080/1062936X.2023.2192521","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2192521","url":null,"abstract":"Triketones are suitable compounds for 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibition and are important compounds for eliminating agricultural weeds. We report herein quantitative structure-activity relationship (QSAR) modelling and docking studies for a series of triketone-quinoline hybrids and 2-(aryloxyacetyl)cyclohexane-1,3-diones with the aim of proposing new chemical candidates that exhibit improved performance as herbicides. The QSAR models obtained were reliable and predictive (average r2, q2, and r2pred of 0.72, 0.51, and 0.71, respectively). Guided by multivariate image analysis of the PLS regression coefficients and variable importance in projection scores, the substituent effects could be analysed, and a promising derivative with R1 = H, R2 = CN, and R3 = 5,7,8-triCl at the triketone-quinoline scaffold (P18) was proposed. Docking studies demonstrated that π-π stacking interactions and specific interactions between the substituents and amino acid residues in the binding site of the Arabidopsis thaliana HPPD (AtHPPD) enzyme support the desired bioactivity. In addition, compared to a benchmark commercial triketone (mesotrione), the proposed compounds are more lipophilic and less mobile in soil rich in organic matter and are less prone to contaminate groundwater.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 3","pages":"231-246"},"PeriodicalIF":3.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9382599","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 QSAR study to predict the survival motor neuron promoter activity of candidate diaminoquinazoline derivatives for the potential treatment of spinal muscular atrophy. 一项预测脊髓性肌萎缩症候选二氨基喹唑啉衍生物的存活运动神经元启动子活性的QSAR研究。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-03-01 DOI: 10.1080/1062936X.2023.2200975

G Sabuncu Gürses, S S Erdem, M T Saçan

{"title":"A QSAR study to predict the survival motor neuron promoter activity of candidate diaminoquinazoline derivatives for the potential treatment of spinal muscular atrophy.","authors":"G Sabuncu Gürses, S S Erdem, M T Saçan","doi":"10.1080/1062936X.2023.2200975","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2200975","url":null,"abstract":"Spinal Muscular Atrophy is a genetic neuromuscular disease that leads to muscle weakness and atrophy and it is characterized by the loss of α-motor neurons in the spinal cord's anterior horn cells. The disease appears due to low levels of the survival motor neuron protein. There are continuing clinical trials for the treatment of Spinal Muscular Atrophy. Quinazoline-based compounds are promising since they were tested on fibroblasts derived from the patients and found to increase the survival motor neuron protein levels. In this study, using multiple linear regression, we generated robust and valid quantitative structure- activity relationship models to predict the survival motor neuron-2 promoter activity of the new candidate compounds using the experimental survival motor neuron-2 promoter activity values of 2,4-diaminoquinazoline derivatives taken from the literature. The novel compounds designed by combining the pyrido[1,2-α]pyrimidin-4-one moeity of the known drug Risdiplam with that of 2,4 - diaminoquinazoline scaffold were predicted to exhibit strong promoter activities.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 3","pages":"247-266"},"PeriodicalIF":3.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9763110","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

Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids. 无监督机器学习，QSAR建模和网络工具开发，以简化抗疟类黄酮的先导物识别过程。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2023-02-01 DOI: 10.1080/1062936X.2023.2169347

J H Zothantluanga, D Chetia, S Rajkhowa, A K Umar

{"title":"Unsupervised machine learning, QSAR modelling and web tool development for streamlining the lead identification process of antimalarial flavonoids.","authors":"J H Zothantluanga, D Chetia, S Rajkhowa, A K Umar","doi":"10.1080/1062936X.2023.2169347","DOIUrl":"https://doi.org/10.1080/1062936X.2023.2169347","url":null,"abstract":"Identification of lead compounds with the traditional laboratory approach is expensive and time-consuming. Nowadays, in silico techniques have emerged as a promising approach for lead identification. In this study, we aim to develop robust and predictive 2D-QSAR models to identify lead flavonoids by predicting the IC50 against Plasmodium falciparum. We applied machine learning algorithms (Principal component analysis followed by K-means clustering) and Pearson correlation analysis to select 9 molecular descriptors (MDs) for model building. We selected and validated the three best QSAR models after execution of multiple linear regression (MLR) 100 times with different combinations of MDs. The developed models have fulfilled the five principles for QSAR models as specified by the Organization for Economic Co-operation and Development. The outcome of the study is a reliable and sustainable in silico method of IC50 (Mean ± SD) prediction that will positively impact the antimalarial drug development process by reducing the money and time required to identify potential antimalarial lead compounds from the class of flavonoids. We also developed a web tool (JazQSAR, https://etflin.com/news/4) to offer an easily accessible platform for the developed QSAR models.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"34 2","pages":"117-146"},"PeriodicalIF":3.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10871660","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: 2