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

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

IF 2.3 3区环境科学与生态学

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

Y Zhang, Y Tian, A Yan

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

引用次数: 0

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

IF 2.3 3区环境科学与生态学

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

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

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

引用次数: 0

Combining QSAR and SSD to predict aquatic toxicity and species sensitivity of pyrethroid and organophosphate pesticides. 结合 QSAR 和 SSD 预测拟除虫菊酯和有机磷农药的水生毒性和物种敏感性。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-07-01 Epub Date: 2024-09-04 DOI: 10.1080/1062936X.2024.2389818

H Untersteiner, B Rippey, A Gromley, R Douglas

{"title":"Combining QSAR and SSD to predict aquatic toxicity and species sensitivity of pyrethroid and organophosphate pesticides.","authors":"H Untersteiner, B Rippey, A Gromley, R Douglas","doi":"10.1080/1062936X.2024.2389818","DOIUrl":"https://doi.org/10.1080/1062936X.2024.2389818","url":null,"abstract":"The widespread use of pyrethroid and organophosphate pesticides necessitates accurate toxicity predictions for regulatory compliance. In this study QSAR and SSD models for six pyrethroid and four organophosphate compounds using QSAR Toolbox and SSD Toolbox have been developed. The QSAR models, described by the formula 48 h-EC50 or 96 h-LC50 = x + y * log Kow, were validated for predicting 48 h-EC50 values for acute Daphnia toxicity and 96 h-LC50 values for acute fish toxicity, meeting criteria of n ≥10, r2 ≥0.7, and Q2 >0.5. Predicted 48 h-EC50 values for pyrethroids ranged from 3.95 × 10-5 mg/L (permethrin) to 8.21 × 10-3 mg/L (fenpropathrin), and 96 h-LC50 values from 3.89 × 10-5 mg/L (permethrin) to 1.68 × 10-2 mg/L (metofluthrin). For organophosphates, 48 h-EC50 values ranged from 2.00 × 10-5 mg/L (carbophenothion) to 3.76 × 10-2 mg/L (crufomate) and 96 h-LC50 values from 3.81 × 10-3 mg/L (carbophenothion) to 12.3 mg/L (crufomate). These values show a good agreement with experimental data, though some, like Carbophenothion, overestimated toxicity. HC05 values, indicating hazardous concentrations for 5% of species, range from 0.029 to 0.061 µg/L for pyrethroids and 0.030 to 0.072 µg/L for organophosphates. These values aid in establishing environmental quality standards (EQS). Compared to existing EQS, HC05 values for pyrethroids were less conservative, while those for organophosphates were comparable.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"35 7","pages":"611-640"},"PeriodicalIF":2.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142126578","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

Modelling lethality and teratogenicity of zebrafish (Danio rerio) due to β-lactam antibiotics employing the QSTR approach. 利用 QSTR 方法模拟β-内酰胺类抗生素对斑马鱼（Danio rerio）的致死率和致畸性。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-07-01 Epub Date: 2024-07-29 DOI: 10.1080/1062936X.2024.2378797

A Nath, P K Ojha, K Roy

{"title":"Modelling lethality and teratogenicity of zebrafish (Danio rerio) due to β-lactam antibiotics employing the QSTR approach.","authors":"A Nath, P K Ojha, K Roy","doi":"10.1080/1062936X.2024.2378797","DOIUrl":"10.1080/1062936X.2024.2378797","url":null,"abstract":"Nowadays, β-lactam antibiotics are one of the most consumed OTC (over-the-counter) medicines in the world. Its frequent use against several infectious diseases leads to the development of antibiotic resistance. Another unavoidable risk factor of β-lactam antibiotics is environmental toxicity. Numerous terrestrial as well as aquatic species have suffered due to the excessive use of these pharmaceuticals. In this present study, we have performed a toxicity assessment employing a novel in silico technique like quantitative structure-toxicity relationships (QSTRs) to explore toxicity against zebrafish (Danio rerio). We have developed single as well as inter-endpoint QSTR models for the β-lactam compounds to explore important structural attributes responsible for their toxicity, employing median lethal (LC50) and median teratogenic concentration (TC50) as the endpoints. We have shown how an inter-endpoint model can extrapolate unavailable endpoint values with the help of other available endpoint values. To verify the models' robustness, predictivity, and goodness-of-fit, several universally popular metrics for both internal and external validation were extensively employed in model validation (single endpoint models: r2 = 0.631 - 0.75, Q2F1 = 0.607 - 0.684; inter-endpoint models: r2 = 0.768 - 0.84, Q2F1 = 0.678 - 0.76). Again, these models were engaged in the prediction of these two responses for a true external set of β-lactam molecules without response values to prove the reproducibility of these models.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"565-589"},"PeriodicalIF":2.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141789011","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

Potent inhibition of human and rat 17β-hydroxysteroid dehydrogenase 1 by curcuminoids and the metabolites: 3D QSAR and in silico docking analysis. 姜黄素及其代谢物对人类和大鼠 17β- 羟类固醇脱氢酶 1 的强效抑制作用：三维 QSAR 和硅学对接分析。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-06-01 Epub Date: 2024-05-24 DOI: 10.1080/1062936X.2024.2355529

J He, Z Ji, J Sang, H Quan, H Zhang, H Lu, J Zheng, S Wang, R S Ge, X Li

{"title":"Potent inhibition of human and rat 17β-hydroxysteroid dehydrogenase 1 by curcuminoids and the metabolites: 3D QSAR and in silico docking analysis.","authors":"J He, Z Ji, J Sang, H Quan, H Zhang, H Lu, J Zheng, S Wang, R S Ge, X Li","doi":"10.1080/1062936X.2024.2355529","DOIUrl":"10.1080/1062936X.2024.2355529","url":null,"abstract":"Curcumin, an extensively utilized natural pigment in the food industry, has attracted considerable attention due to its potential therapeutic effects, such as anti-tumorigenic and anti-inflammatory activities. The enzyme 17β-Hydroxysteroid dehydrogenase 1 (17β-HSD1) holds a crucial position in oestradiol production and exhibits significant involvement in oestrogen-responsive breast cancers and endometriosis. This study investigated the inhibitory effects of curcuminoids, metabolites, and analogues on 17β-HSD1, a key enzyme in oestradiol synthesis. Screening 10 compounds, including demethoxycurcumin (IC50, 3.97 μM) and dihydrocurcumin (IC50, 5.84 μM), against human and rat 17β-HSD1 revealed varying inhibitory potencies. These compounds suppressed oestradiol secretion in human BeWo cells at ≥ 5-10 μM. 3D-Quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses elucidated the interaction mechanisms. Docking studies and Gromacs simulations suggested competitive or mixed binding to the steroid or NADPH/steroid binding sites of 17β-HSD1. Predictive 3D-QSAR models highlighted the importance of hydrophobic regions and hydrogen bonding in inhibiting 17β-HSD1 activity. In conclusion, this study provides valuable insights into the inhibitory effects and mode of action of curcuminoids, metabolites, and analogues on 17β-HSD1, which may have implications in the field of hormone-related disorders.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"433-456"},"PeriodicalIF":2.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088725","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

Identification of inhibitors for neurodegenerative diseases targeting dual leucine zipper kinase through virtual screening and molecular dynamics simulations. 通过虚拟筛选和分子动力学模拟鉴定针对神经退行性疾病的双亮氨酸拉链激酶抑制剂。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-06-01 Epub Date: 2024-06-10 DOI: 10.1080/1062936X.2024.2363195

S Koirala, S Samanta, P Kar

{"title":"Identification of inhibitors for neurodegenerative diseases targeting dual leucine zipper kinase through virtual screening and molecular dynamics simulations.","authors":"S Koirala, S Samanta, P Kar","doi":"10.1080/1062936X.2024.2363195","DOIUrl":"10.1080/1062936X.2024.2363195","url":null,"abstract":"Neurodegenerative diseases lead to a gradual decline in cognitive and motor functions due to the progressive loss of neurons in the central nervous system. The role of dual leucine zipper kinase (DLK) in regulating stress responses and neuronal death pathways highlights its significance as a target against neurodegenerative diseases. The non-availability of FDA-approved drugs emphasizes a need to identify novel DLK-inhibitors. We screened NPAtlas (Natural products) and MedChemExpress (FDA-approved) libraries to identify potent ATP-competitive DLK inhibitors. ADMET analyses identified four compounds (two natural products and two FDA-approved) with favourable features. Subsequently, we performed molecular dynamics simulations to examine the binding-stability and ligand-induced conformational dynamics. Molecular mechanics Poisson Boltzmann surface area (MM-PBSA) calculations demonstrated CID139591660, dithranol, and danthron having greater affinity, while CID156581477 showed lower affinity than control sunitinib. PCA and network analysis results indicated structural and network alteration post-ligand binding. Furthermore, we identified an analogue of CID156581477 using the deep learning-based web server DeLA Drug which demonstrated a higher affinity than its parent compound and the control and identified several crucial interacting residues. Overall, our study provides significant theoretical guidance for designing potent novel DLK inhibitors and compounds that could emerge as promising drug candidates against DLK following laboratory validation.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"457-482"},"PeriodicalIF":2.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141296640","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

Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management. 基于片段的 QSAR 研究探索 DPP-4 抑制剂的结构要求：改善 2 型糖尿病管理的踏脚石。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-06-01 Epub Date: 2024-06-21 DOI: 10.1080/1062936X.2024.2366886

P K Dey, R Dutta, M Ray, P Jakkula, S Banerjee, I A Qureshi, S Gayen, S A Amin

{"title":"Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management.","authors":"P K Dey, R Dutta, M Ray, P Jakkula, S Banerjee, I A Qureshi, S Gayen, S A Amin","doi":"10.1080/1062936X.2024.2366886","DOIUrl":"10.1080/1062936X.2024.2366886","url":null,"abstract":"Dipeptidyl peptidase-4 (DPP-4) inhibitors belong to a prominent group of pharmaceutical agents that are used in the governance of type 2 diabetes mellitus (T2DM). They exert their antidiabetic effects by inhibiting the incretin hormones like glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide which, play a pivotal role in the regulation of blood glucose homoeostasis in our body. DPP-4 inhibitors have emerged as an important class of oral antidiabetic drugs for the treatment of T2DM. Surprisingly, only a few 2D-QSAR studies have been reported on DPP-4 inhibitors. Here, fragment-based QSAR (Laplacian-modified Bayesian modelling and Recursive partitioning (RP) approaches have been utilized on a dataset of 108 DPP-4 inhibitors to achieve a deeper understanding of the association among their molecular structures. The Bayesian analysis demonstrated satisfactory ROC values for the training as well as the test sets. Meanwhile, the RP analysis resulted in decision tree 3 with 2 leaves (Tree 3: 2 leaves). This present study is an effort to get an insight into the pivotal fragments modulating DPP-4 inhibition.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"483-504"},"PeriodicalIF":2.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141432666","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

HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors. HT_PREDICT：基于机器学习的计算开源工具，用于筛选 HDAC6 抑制剂。

IF 2.3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-06-01 Epub Date: 2024-07-15 DOI: 10.1080/1062936X.2024.2371155

O V Tinkov, V N Osipov, A V Kolotaev, D S Khachatryan, V Y Grigorev

引用次数: 0

Anti-inflammatory action of new hybrid N-acyl-[1,2]dithiolo-[3,4-c]quinoline-1-thione. 新型混合 N-酰基-[1,2]二硫环戊-[3,4-c]喹啉-1-硫酮的抗炎作用。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-05-01 Epub Date: 2024-05-22 DOI: 10.1080/1062936X.2024.2347965

S M Medvedeva, A Petrou, M Fesatidou, A Gavalas, A A Geronikaki, P I Savosina, D S Druzhilovskiy, V V Poroikov, K S Shikhaliev, V G Kartsev

{"title":"Anti-inflammatory action of new hybrid N-acyl-[1,2]dithiolo-[3,4-c]quinoline-1-thione.","authors":"S M Medvedeva, A Petrou, M Fesatidou, A Gavalas, A A Geronikaki, P I Savosina, D S Druzhilovskiy, V V Poroikov, K S Shikhaliev, V G Kartsev","doi":"10.1080/1062936X.2024.2347965","DOIUrl":"10.1080/1062936X.2024.2347965","url":null,"abstract":"Most of pharmaceutical agents display a number of biological activities. It is obvious that testing even one compound for thousands of biological activities is not practically possible. A computer-aided prediction is therefore the method of choice in this case to select the most promising bioassays for particular compounds. Using the PASS Online software, we determined the probable anti-inflammatory action of the 12 new hybrid dithioloquinolinethiones derivatives. Chemical similarity search in the World-Wide Approved Drugs (WWAD) and DrugBank databases did not reveal close structural analogues with the anti-inflammatory action. Experimental testing of anti-inflammatory activity of the synthesized compounds in the carrageenan-induced inflammation mouse model confirmed the computational predictions. The anti-inflammatory activity of the studied compounds (2a, 3a-3k except for 3j) varied between 52.97% and 68.74%, being higher than the reference drug indomethacin (47%). The most active compounds appeared to be 3h (68.74%), 3k (66.91%) and 3b (63.74%) followed by 3e (61.50%). Thus, based on the in silico predictions a novel class of anti-inflammatory agents was discovered.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"343-366"},"PeriodicalIF":3.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141081520","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 different classification-dependent QSAR modelling strategies for HDAC3 inhibitors in search of meaningful structural contributors. 探索 HDAC3 抑制剂的不同分类依赖 QSAR 建模策略，寻找有意义的结构贡献者。

IF 3 3区环境科学与生态学

SAR and QSAR in Environmental Research Pub Date : 2024-05-01 Epub Date: 2024-05-17 DOI: 10.1080/1062936X.2024.2350504

T Jha, R Jana, S Banerjee, S K Baidya, S A Amin, S Gayen, B Ghosh, N Adhikari

{"title":"Exploring different classification-dependent QSAR modelling strategies for HDAC3 inhibitors in search of meaningful structural contributors.","authors":"T Jha, R Jana, S Banerjee, S K Baidya, S A Amin, S Gayen, B Ghosh, N Adhikari","doi":"10.1080/1062936X.2024.2350504","DOIUrl":"10.1080/1062936X.2024.2350504","url":null,"abstract":"Histone deacetylase 3 (HDAC3), a Zn2+-dependent class I HDACs, contributes to numerous disorders such as neurodegenerative disorders, diabetes, cardiovascular disease, kidney disease and several types of cancers. Therefore, the development of novel and selective HDAC3 inhibitors might be promising to combat such diseases. Here, different classification-based molecular modelling studies such as Bayesian classification, recursive partitioning (RP), SARpy and linear discriminant analysis (LDA) were conducted on a set of HDAC3 inhibitors to pinpoint essential structural requirements contributing to HDAC3 inhibition followed by molecular docking study and molecular dynamics (MD) simulation analyses. The current study revealed the importance of hydroxamate function for Zn2+ chelation as well as hydrogen bonding interaction with Tyr298 residue. The importance of hydroxamate function for higher HDAC3 inhibition was noticed in the case of Bayesian classification, recursive partitioning and SARpy models. Also, the importance of substituted thiazole ring was revealed, whereas the presence of linear alkyl groups with carboxylic acid function, any type of ester function, benzodiazepine moiety and methoxy group in the molecular structure can be detrimental to HDAC3 inhibition. Therefore, this study can aid in the design and discovery of effective novel HDAC3 inhibitors in the future.","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"367-389"},"PeriodicalIF":3.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140959029","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