SAR and QSAR in Environmental Research最新文献_第4页

Antiepileptic potential of Jatropha integerrima Jacq. extracts: an exploratory study integrating in vivo seizure models and computational analysis. 麻疯树的抗癫痫作用。摘要：一项结合体内癫痫模型和计算分析的探索性研究。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-02-01 Epub Date: 2026-04-07 DOI: 10.1080/1062936X.2026.2640387

S Fatima, F Nasir, A Ahmed

{"title":"Antiepileptic potential of Jatropha integerrima Jacq. extracts: an exploratory study integrating in vivo seizure models and computational analysis.","authors":"S Fatima, F Nasir, A Ahmed","doi":"10.1080/1062936X.2026.2640387","DOIUrl":"10.1080/1062936X.2026.2640387","url":null,"abstract":"Epilepsy is a chronic neurological disorder characterized by recurrent seizures resulting from abnormal neuronal excitability and ion channel dysfunction. This study explored the antiepileptic potential of Jatropha integerrima using integrated in vivo and in silico approaches to identify safer alternatives to conventional therapies. Ethanolic extracts of the plant were fractionated into petroleum ether (PE) and ethyl acetate (EA) fractions and analyzed via LC-MS for tentative phytoconstituent identification. Anticonvulsant activity of both fractions was evaluated in Swiss albino mice using pentylenetetrazol (PTZ) and maximal electroshock seizure (MES) models. The PE fraction significantly reduced seizure frequency, duration, and mortality (p < 0.05), demonstrating effects comparable to diazepam. Molecular docking and MM/GBSA analyses revealed strong binding affinities of major compounds toward GABAA and Nav1.2 receptors. Notably, (-)-jatrointelignan A (C₃₁H₃₆O₁₁) exhibited the highest docking scores (-10.20 kcal/mol for GABAA and -11.47 kcal/mol for Nav1.2) and favorable binding free energies (-25.38 and -70.63 kcal/mol, respectively). ADME and toxicity predictions suggested good pharmacokinetic properties with low toxicity, while molecular dynamics simulations confirmed stable receptor ligand interactions. Overall, J. integerrima and its lead compound demonstrate promising antiepileptic potential via dual modulation of GABAergic and sodium channel pathways.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"131-165"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147628324","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

Systematic evaluation of data preprocessing and model selection strategies for reliable pIC₅₀ prediction of acetylcholinesterase inhibitors. 对乙酰胆碱酯酶抑制剂pIC50可靠预测的数据预处理和模型选择策略进行系统评估。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-02-01 Epub Date: 2026-04-10 DOI: 10.1080/1062936X.2026.2647204

E Delibaş, H I Güler

{"title":"Systematic evaluation of data preprocessing and model selection strategies for reliable pIC50 prediction of acetylcholinesterase inhibitors.","authors":"E Delibaş, H I Güler","doi":"10.1080/1062936X.2026.2647204","DOIUrl":"10.1080/1062936X.2026.2647204","url":null,"abstract":"Predicting acetylcholinesterase (AChE) inhibitory activity is important in drug discovery. This study evaluates molecular descriptor - based machine learning models to predict AChE activity as pIC50 values. The primary objective was to comparatively investigate the impact of different data preprocessing strategies on prediction performance and model selection under challenging chemical datasets exhibiting low correlation structures. Tree based gradient boosting algorithms, namely CatBoost and XGBoost, together with sensitive regression models including Support Vector Regression and Multilayer Perceptron, were examined, and model specific data preparation pipelines were applied according to their structural assumptions. The target variable was stabilized through logarithmic transformation and winsorization of IC50 values. Model performance was assessed using both a 70-15-15 train-validation-test split and a 10-fold cross validation protocol. Furthermore, stacking based ensemble learning strategies were explored to enhance generalization capability. The results demonstrate that predictive performance is predominantly constrained by intrinsic dataset characteristics rather than algorithmic selection. Optimized tree-based models achieved the highest accuracy, while stacking provided only marginal improvements over the best individual learners. To improve interpretability, SHAP based explainable artificial intelligence analysis was conducted, highlighting the contributions of biologically meaningful molecular descriptors, and offers guidance for future studies addressing comparable biochemical modelling challenges.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"185-204"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147646362","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

Decoding structural fingerprints to elucidate the mechanism of action of anti-apoptotic protein Mcl-1. 解码结构指纹以阐明抗凋亡蛋白Mcl-1的作用机制。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-02-01 Epub Date: 2026-03-26 DOI: 10.1080/1062936X.2026.2640394

S Goswami, R Tarafdar, P Manna, S A Amin

{"title":"Decoding structural fingerprints to elucidate the mechanism of action of anti-apoptotic protein Mcl-1.","authors":"S Goswami, R Tarafdar, P Manna, S A Amin","doi":"10.1080/1062936X.2026.2640394","DOIUrl":"10.1080/1062936X.2026.2640394","url":null,"abstract":"Overexpression of myeloid cell leukaemia-1 (Mcl-1) is commonly observed in numerous haematological malignancies and solid tumours, where it contributes to tumour progression, poor prognosis, and resistance to chemotherapy. Previous computational studies on Mcl-1 inhibitors (Mcl-1i) have predominantly focused on limited datasets with single scaffold, few modelling strategies, or structure-based analyses. In contrast, the present work presents a large-scale chemical space exploration integrated with fragment/fingerprint-based analysis and multiple machine learning approaches applied to a diverse Mcl-1i dataset. The current study characterizes scaffold diversity and Mcl-1 inhibitory activity trends within a large chemical space. Fragment-based QSAR modelling was implemented using Bayesian classification, thereby enabling the identification of both favourable and unfavourable fingerprints that regulate Mcl-1 inhibition. Furthermore, the significance of the identified fingerprints was validated through protein-ligand interaction analysis. In addition, statistically validated AI/ML models were developed that enable researchers to efficiently screen potential Mcl-1i. Positive fingerprints such as G9, G17, and G20 are consistently associated with low-nanomolar IC50 values, indicating that features combining aromaticity, flexible linkers, and heteroaromatic scaffolds strongly promote high-affinity binding. All these fingerprints as a collective offer mechanistically interpretable information on structure-activity correlations and act as useful leads to rational design and lead optimization of potent Mcl-1i.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"167-183"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147514473","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

Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity. 综合网络毒理学和分子对接初步探讨聚苯乙烯微塑料在儿童肥胖中的潜在作用。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-01-01 Epub Date: 2026-02-24 DOI: 10.1080/1062936X.2026.2629397

H Xiao, Y Huang, J Du

{"title":"Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity.","authors":"H Xiao, Y Huang, J Du","doi":"10.1080/1062936X.2026.2629397","DOIUrl":"10.1080/1062936X.2026.2629397","url":null,"abstract":"Childhood obesity is a severe global epidemic, and emerging evidence suggests environmental pollutants like polystyrene microplastics (PS-MPs) may disrupt metabolic homoeostasis though mechanistic insights remain limited. This study integrated cross-species transcriptomics (from zebrafish and human adipose datasets), network toxicology, machine learning, and molecular docking to explore this link. We identified 40 overlapping genes between childhood obesity related DEGs and PS-MPs related genes, enriched in lipid metabolic pathways such as cholesterol homoeostasis and insulin signalling. Topological and machine-learning analyses highlighted hub genes, which showed strong diagnostic accuracy. Molecular docking further revealed stable binding (energy < -5.0 kcal/mol) between PS-MPs and key targets (APOB、BUB1、CDC20 and PPARGC1A). Our integrative analysis suggests that PS-MPs may act as an environmental trigger that could disrupt conserved lipid and metabolic homoeostasis by targeting key hub genes (APOB、BUB1、CDC20 and PPARGC1A). These findings provide a novel molecular hypothesis linking PS-MPs exposure to childhood obesity and support precautionary measures.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"1-21"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147284939","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

Molecular docking and dynamics simulations identify marine sponge-derived Halenaquinone as a promising STAT4 modulator for rheumatic heart disease. 分子对接和动力学模拟确定海洋海绵衍生的Halenaquinone是一种有前途的STAT4调节剂，用于治疗风湿性心脏病。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-01-01 Epub Date: 2026-03-02 DOI: 10.1080/1062936X.2026.2631015

S Skariyachan, G K Mathamangalath, D Sebastian, K Sreejith

{"title":"Molecular docking and dynamics simulations identify marine sponge-derived Halenaquinone as a promising STAT4 modulator for rheumatic heart disease.","authors":"S Skariyachan, G K Mathamangalath, D Sebastian, K Sreejith","doi":"10.1080/1062936X.2026.2631015","DOIUrl":"10.1080/1062936X.2026.2631015","url":null,"abstract":"This study aimed to investigate the interaction potential of sponge metabolites towards signal transducer and activator of transcription 4 (STAT4), one of the potential targets related with rheumatic heart disease (RHD). Out of 100 sponge molecules screened, Halenaquinone demonstrated as potential inhibitor of STAT4 by modelling. Molecular docking revealed that Halenaquinone exhibited strong binding affinity with STAT4 (-10.2 kcal/mol) and favourable interactions, surpassing the binding of the reference drug Prednisolone-NR3C1complex. The interaction between STAT4 and Halenaquinone stabilized through hydrogen bonding and hydrophobic contacts involving several key residues, supporting its possible inhibitory mechanism. Molecular dynamics simulation studies indicated the stability of the STAT4-Halenaquinone complex, with some flexibility observed in the loop and terminal regions. Free energy decomposition revealed that van der Waals and electrostatic interaction were the main contributors to binding. Furthermore, principal component analysis, dynamic cross correlation and free energy landscape analyses suggested that Halenaquinone binding enhances the conformational adaptability of STAT4, consistent with its role as a potential mediator. The present study provides a computational model of STAT4 as a promising target in RHD and suggests Halenaquinone is a potential marine-sponge-derived compound with therapeutic potential.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"23-48"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147326785","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

Computational exploration and discovery of dual EGFR-CDK2 kinase inhibitors: AI-ML powered bioisosteric design, 3D QSAR, docking, DFT and ADMET analysis of novel phthalimide derivatives. 双EGFR-CDK2激酶抑制剂的计算探索和发现：AI-ML驱动的生物等构设计，3D QSAR，对接，DFT和ADMET分析新型邻苯二胺衍生物。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-01-01 Epub Date: 2026-03-02 DOI: 10.1080/1062936X.2026.2631024

B W Matore, A Murmu, P P Roy, J Singh

{"title":"Computational exploration and discovery of dual EGFR-CDK2 kinase inhibitors: AI-ML powered bioisosteric design, 3D QSAR, docking, DFT and ADMET analysis of novel phthalimide derivatives.","authors":"B W Matore, A Murmu, P P Roy, J Singh","doi":"10.1080/1062936X.2026.2631024","DOIUrl":"10.1080/1062936X.2026.2631024","url":null,"abstract":"AI-ML approaches emerged as transformative technologies in cancer drug discovery by accelerating the target identification and lead optimization. EGFR and CDK2 are crucial targets in cancer therapy which involved in cancer proliferation and metastasis. However, existing inhibitors face challenges like resistance, toxicity and poor pharmacokinetics. Phthalimide scaffolds possess dual or multi-target efficacy which serve a promising drug. This study explores phthalimide-based dual EGFR and CDK2 inhibitors addressing limitations of current anticancer agents. Initially, the 3D-QSAR model was developed and validated using 58 phthalimide derivatives (r2 = 0.998, Q2 = 0.852 and MAE = 0.299). The novel 3886 phthalimide derivatives were generated using the MolOpt server by bioisosteric replacements and screened over the 3D-QSAR model. Notably, 80 novel derivatives demonstrated exceptional anticancer potency (IC50 < 10 nM). Molecular docking, binding free energy, MM-PBSA and MM-GBSA confirmed strong binding affinities, stability and dual action of novel compounds (1472, 1486 and 1458) with EGFR and CDK2. DFT analysis revealed favourable electronic properties and supporting their reactivity. AI-driven ADMET predictions confirmed their drug-like characteristics. This study highlights the AI-ML driven methodologies in the discovery of novel phthalimide derivatives (1472, 1486 and 1458) as potent anticancer agents (IC50 = 3.6, 6.2 and 7.4 nM).","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"49-74"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147326870","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

Machine learning-driven drug discovery for the management of TNBC: focus on IDO1 and TDO targets. 机器学习驱动的TNBC药物发现：重点关注IDO1和TDO靶点。

IF 2.8 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2026-01-01 Epub Date: 2026-03-17 DOI: 10.1080/1062936X.2026.2641184

P Priyanga, K Ramanathan, V Shanthi

{"title":"Machine learning-driven drug discovery for the management of TNBC: focus on IDO1 and TDO targets.","authors":"P Priyanga, K Ramanathan, V Shanthi","doi":"10.1080/1062936X.2026.2641184","DOIUrl":"10.1080/1062936X.2026.2641184","url":null,"abstract":"Tryptophan catabolism through the kynurenine pathway produces the oncometabolite kynurenine, which is strongly implicated in cancers such as triple-negative breast cancer (TNBC). The enzymes indoleamine 2,3-dioxygenase (IDO1) and tryptophan 2,3-dioxygenase (TDO) drive this pathway and promote an immunosuppressive tumour microenvironment, making them an attractive therapeutic target. However, no approved drug currently inhibits both enzymes simultaneously. In this study, we employed a machine learning (ML)-driven virtual screening pipeline to identify potent dual IDO1 and TDO inhibitors. Initially, an in-house ML classification model was developed using IC50 values from 1,037 distinct dual inhibitors sourced from the ChEMBL and BindingDB databases. Among the various models evaluated, the eXtreme Gradient Boosting with Random Forest (XGBRF) classifier achieved the highest performance (95% accuracy) and was selected to screen the MEGxp database. Subsequent molecular docking, MM-GBSA calculations, rescoring, and ADMET profiling identified two promising candidates, NP000319 and NP003833. Both compounds also showed predicted anticancer potential against MDA-MB-231 TNBC cells. Furthermore, the stability of the protein-ligand complexes was confirmed through 100 ns molecular dynamics simulations. Overall, the study highlights the value of ML-driven dual-inhibition strategies and provides strong leads for future experimental validation and potential therapeutic development for TNBC.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"37 1","pages":"75-103"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147475060","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

EGFR affinity and selectivity for the phosphorylation codes of pseudo triad tyrosine (YYY) motif and its extensions in lung cancer-related substrate-inhibitor alignment: an integrated molecular simulation-QSAR modelling-in vitro assay approach. EGFR对肺癌相关底物-抑制剂比对中伪三联体酪氨酸（YYY）基序及其延伸磷酸化编码的亲和力和选择性：综合分子模拟- qsar模型-体外测定方法

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2025-12-01 Epub Date: 2026-01-06 DOI: 10.1080/1062936X.2025.2599971

Z Wang, L Dong, H Liu, Y Song

{"title":"EGFR affinity and selectivity for the phosphorylation codes of pseudo triad tyrosine (YYY) motif and its extensions in lung cancer-related substrate-inhibitor alignment: an integrated molecular simulation-QSAR modelling-in vitro assay approach.","authors":"Z Wang, L Dong, H Liu, Y Song","doi":"10.1080/1062936X.2025.2599971","DOIUrl":"https://doi.org/10.1080/1062936X.2025.2599971","url":null,"abstract":"Human epidermal growth factor receptor (EGFR) has been approved as a well-established druggable target of lung carcinoma. The binding peptide segments of both substrate and inhibitory proteins contain a phosphorylatable tandem YY motif but interact with EGFR kinase domain in different manners. Here, the two tandem substrate Y0Y+1 and inhibitor Y+1Y+2 motifs were aligned to define a new pseudo triad tyrosine Y0Y+1Y+2 (PtriY) motif, in which the Y0, Y+1 and Y+2 residues bind to catalytic, priming and priming pockets on EGFR kinase domain surface, respectively. Here, we examined the effects of different PtriY phosphorylation codes on EGFR binding and created a systematic single-point substitution-binding energy change profile of its N- and C-terminal extensions, which was then used to develop and validate quantitative structure-activity relationship (QSAR) models. The best model was utilized to guide rational peptidic inhibitor design, from which more than 40 promising hits were selected to perform affinity and/or kinase assays. The QSAR-designed PH2[Y0pY+1pY+2] peptide (ENGHY0pY+1pY+2AL) was identified to have the strongest binding potency (Kd = 0.26 ± 0.07 μM) and the highest inhibitory activity (IC50 = 5.8 ± 0.9 nM), which consists of an amphiphilic N-terminal extension, a double-phosphorylated PtriYmotif and hydrophobic C-terminal extension.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"36 12","pages":"1263-1282"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145912796","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

Search for acetylcholinesterase inhibitors by computerized screening of approved drug compounds. 通过计算机筛选批准的药物化合物来寻找乙酰胆碱酯酶抑制剂。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2025-12-01 Epub Date: 2025-12-03 DOI: 10.1080/1062936X.2025.2592855

T A Materova, A V Sulimov, I S Ilin, S D Varfolomeev, V B Sulimov

{"title":"Search for acetylcholinesterase inhibitors by computerized screening of approved drug compounds.","authors":"T A Materova, A V Sulimov, I S Ilin, S D Varfolomeev, V B Sulimov","doi":"10.1080/1062936X.2025.2592855","DOIUrl":"10.1080/1062936X.2025.2592855","url":null,"abstract":"This article presents the results of computational screening of approved drug compounds to find new inhibitors of acetylcholinesterase (AChE), an enzyme that plays a key role in the regulation of neurotransmission and cognitive functions. Using molecular docking and quantum chemical postprocessing methods, the authors conducted a virtual screening of a library of 2909 drug compounds approved for clinical use from two ZINC database libraries. The screening process employed the SOL docking program with MMFF94 force field and genetic algorithms for global optimization, targeting the human AChE structure (PDB ID: 6O4W). As a result of the docking, 211 of the most promising ligands were selected for calculating their enthalpy of binding to AChE using quantum chemical calculations. Based on the analysis of the free energy of binding estimated by docking score and the enthalpy of binding calculated using the quantum-chemical PM7 method with the COSMO solvent model, 16 of the most promising candidates for the role of AChE inhibitors were identified. Notable candidates include Pixantrone, Guanfacine and Hydroxystilbamidine. These compounds, although not previously known as AChE inhibitors, represent diverse chemical classes including substituted thiophenes, pyridines, and fused nitrogen-containing heterocycles, showing high potential for treating neurodegenerative diseases such as Alzheimer's disease.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"1161-1179"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145661878","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

Warfarin derivatives as free radical scavengers: a coumarin scaffold-based linear regression model with in vitro validation. 华法林衍生物自由基清除剂：香豆素支架为基础的线性回归模型与体外验证。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2025-12-01 Epub Date: 2025-12-04 DOI: 10.1080/1062936X.2025.2591659

E Goya-Jorge, M Pedraza-Beltrán, R T Pareja-Rodríguez, C D Torres-Zulueta, Y Cañizares-Carmenate, M E Jorge Rodríguez, M Sylla-Iyarreta Veitía

{"title":"Warfarin derivatives as free radical scavengers: a coumarin scaffold-based linear regression model with in vitro validation.","authors":"E Goya-Jorge, M Pedraza-Beltrán, R T Pareja-Rodríguez, C D Torres-Zulueta, Y Cañizares-Carmenate, M E Jorge Rodríguez, M Sylla-Iyarreta Veitía","doi":"10.1080/1062936X.2025.2591659","DOIUrl":"10.1080/1062936X.2025.2591659","url":null,"abstract":"Antioxidant agents that efficiently scavenge reactive oxygen species (ROS) are of great interest in medicinal chemistry for their potential to mitigate oxidative stress-related pathologies. In this work, we developed an interpretable Multiple Linear Regression (MLR) QSAR model using seven molecular descriptors (D/Dr05, MATS2v, MATS8p, Mor24m, L2s, HATS3u, H8m) to predict the free radical scavenging activity of coumarin-based compounds as measured by the IC50 in the DPPH assay. The MLR-QSAR model showed strong goodness-of-fit and robust internal and external validation parameters (r2 = 81.04, Q2LOO = 77.93, Q2boot = 76.78, r2ext = 75.38, yscrambler2 = 0.25), supporting its predictive reliability. We applied the model to predict the antiradical potential of a novel set of Warfarin derivatives, a class of molecules historically known for anticoagulant properties but with unexplored antioxidant potential. Experimental in vitro DPPH assays on the seven Warfarin derivatives (WD) revealed a positive correlation (r = 0.63) with the predictions, validating the MLR-QSAR as a screening tool. Furthermore, all WD exhibited significant DPPH radical scavenging activity, demonstrating the chemical antioxidant potential of an anticoagulant-derived scaffold. This dual in silico-in vitro strategy highlights the value of interpretable QSAR models for guiding compound prioritization and structural optimization towards new coumarin-based antioxidants.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"1105-1116"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145669451","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