Pub Date : 2024-08-14DOI: 10.1007/s11030-024-10943-4
Jinping Sun, Di Xiao, Ming Lang, Xuetao Xu
A series of novel sulfonyl hydrazide based β-carboline derivatives (SX1-SX32) were designed and synthesized, and their structures were characterized on NMR and HRMS. Their α-glucosidase inhibitory screening results found that compounds (SX1-SX32) presented potential α-glucosidase inhibitory: IC50 values being 2.12 ± 0.33-19.37 ± 1.49 μM. Compound SX29 with a para-phenyl (IC50: 2.12 ± 0.33 μM) presented the strongest activity and was confirmed as a noncompetitive inhibitor. Fluorescence spectra, CD spectra and molecular docking were conducted to describe the inhibition mechanism of SX29 against α-glucosidase. Cells cytotoxicity indicated SX29 (0-32 μM) had no cytotoxicity on 293T cells. In particular, in vivo experiments revealed that oral administration of SX29 could regulate hyperglycemia and glucose tolerance of diabetic mice. These achieved findings indicated that sulfonyl hydrazide based β-carboline derivatives bore promising potential for discovering new α-glucosidase inhibitors with hypoglycemic activity.
{"title":"Novel sulfonyl hydrazide based β-carboline derivatives as potential α-glucosidase inhibitors: design, synthesis, and biological evaluation.","authors":"Jinping Sun, Di Xiao, Ming Lang, Xuetao Xu","doi":"10.1007/s11030-024-10943-4","DOIUrl":"https://doi.org/10.1007/s11030-024-10943-4","url":null,"abstract":"<p><p>A series of novel sulfonyl hydrazide based β-carboline derivatives (SX1-SX32) were designed and synthesized, and their structures were characterized on NMR and HRMS. Their α-glucosidase inhibitory screening results found that compounds (SX1-SX32) presented potential α-glucosidase inhibitory: IC<sub>50</sub> values being 2.12 ± 0.33-19.37 ± 1.49 μM. Compound SX29 with a para-phenyl (IC<sub>50</sub>: 2.12 ± 0.33 μM) presented the strongest activity and was confirmed as a noncompetitive inhibitor. Fluorescence spectra, CD spectra and molecular docking were conducted to describe the inhibition mechanism of SX29 against α-glucosidase. Cells cytotoxicity indicated SX29 (0-32 μM) had no cytotoxicity on 293T cells. In particular, in vivo experiments revealed that oral administration of SX29 could regulate hyperglycemia and glucose tolerance of diabetic mice. These achieved findings indicated that sulfonyl hydrazide based β-carboline derivatives bore promising potential for discovering new α-glucosidase inhibitors with hypoglycemic activity.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rheumatoid Arthritis (RA) is a persistent autoimmune disease affecting approximately 0.5-1 percent of the world population. RA prevalence is higher in woman aged between 35 and 50 years than in age matched men, though this difference is less evident among elderly patients. The profound immune specific effects of disrupted JAK 3 (Janus kinase 3) signaling highlight the possibility of therapeutic targeting of JAK3 as a highly specific mode of immune system suppression. To address the above problem which is unendurable to patients and in the hope to cater some respite to such suffering we have targeted JAK 3 protein and JAK/STAT signaling pathway with compounds downloaded from FDA database, and performed screening of all available compounds docked against JAK3 protein. The difference between the target protein and other proteins of the same family was studied using cross docking and the compounds having higher binding affinity to JAK3 protein also showed more selectivity towards the particular protein. Density functional theory and molecular dynamics simulation study was done to study the compounds at their atomic level to know more about their drug likeliness. At the end of the study and based on our analysis we have come up with three FDA approved drugs that can be proposed as a treatment option for Rheumatoid Arthritis.
类风湿性关节炎(RA)是一种顽固的自身免疫性疾病,约占世界总人口的 0.5%-1%。35至50岁女性的类风湿关节炎发病率高于年龄匹配的男性,但这一差异在老年患者中并不明显。JAK 3(Janus 激酶 3)信号传导紊乱会产生深远的免疫特异性影响,这凸显了以 JAK3 为治疗靶点作为高度特异性免疫系统抑制模式的可能性。为了解决上述令患者难以忍受的问题,并希望为这种痛苦提供一些喘息的机会,我们从 FDA 数据库中下载了针对 JAK 3 蛋白和 JAK/STAT 信号通路的化合物,并对所有与 JAK3 蛋白对接的可用化合物进行了筛选。利用交叉对接法研究了目标蛋白与同族其他蛋白之间的差异,结果表明,与 JAK3 蛋白结合亲和力较高的化合物对该特定蛋白具有更高的选择性。密度泛函理论和分子动力学模拟研究从原子水平对化合物进行了研究,以进一步了解它们的药物相容性。研究结束后,根据我们的分析,我们得出了三种经 FDA 批准的药物,可作为类风湿关节炎的治疗方案。
{"title":"Computational drug repositioning for IL6 triggered JAK3 in rheumatoid arthritis using FDA database.","authors":"Kaushani Banerjee, Bavya Chandrasekar, Sruthy Sathish, Honglae Sohn, Thirumurthy Madhavan","doi":"10.1007/s11030-024-10958-x","DOIUrl":"https://doi.org/10.1007/s11030-024-10958-x","url":null,"abstract":"<p><p>Rheumatoid Arthritis (RA) is a persistent autoimmune disease affecting approximately 0.5-1 percent of the world population. RA prevalence is higher in woman aged between 35 and 50 years than in age matched men, though this difference is less evident among elderly patients. The profound immune specific effects of disrupted JAK 3 (Janus kinase 3) signaling highlight the possibility of therapeutic targeting of JAK3 as a highly specific mode of immune system suppression. To address the above problem which is unendurable to patients and in the hope to cater some respite to such suffering we have targeted JAK 3 protein and JAK/STAT signaling pathway with compounds downloaded from FDA database, and performed screening of all available compounds docked against JAK3 protein. The difference between the target protein and other proteins of the same family was studied using cross docking and the compounds having higher binding affinity to JAK3 protein also showed more selectivity towards the particular protein. Density functional theory and molecular dynamics simulation study was done to study the compounds at their atomic level to know more about their drug likeliness. At the end of the study and based on our analysis we have come up with three FDA approved drugs that can be proposed as a treatment option for Rheumatoid Arthritis.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tuberculosis (TB) caused by the bacteria Mycobacterium tuberculosis (M. tb), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique cell wall of M. tb provides an extra layer of protection for the bacteria and hence only compounds that can penetrate this barrier can reach their targets within the bacterial cell wall. The creation of a reliable machine learning (ML) model to predict the mycobacterial cell wall permeability of small molecules is presented in this work and four ML algorithms, including Random Forest, Support Vector Machines (SVM), k-nearest Neighbour (k-NN) and Logistic Regression were trained on a dataset of 5368 compounds. RDKit and Mordred toolkits were used to calculate features. To determine the most effective model, various performance metrics were used such as accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve. The best-performing model was further refined with hyperparameter tuning and tenfold cross-validation. The SVM model with filtering outperformed the other machine learning models and demonstrated 80.26% and 81.13% accuracy on the test and validation datasets, respectively. The study also provided insights into the molecular descriptors that play the most important role in predicting the ability of a molecule to pass the M. tb cell wall, which could guide future compound design. The model is available at https://github.com/PGlab-NIPER/MTB_Permeability.
{"title":"Prediction of Mycobacterium tuberculosis cell wall permeability using machine learning methods","authors":"Aritra Banerjee, Anju Sharma, Pradnya Kamble, Prabha Garg","doi":"10.1007/s11030-024-10952-3","DOIUrl":"10.1007/s11030-024-10952-3","url":null,"abstract":"<div><p>Tuberculosis (TB) caused by the bacteria <i>Mycobacterium tuberculosis</i> (<i>M. tb</i>), continues to pose a significant worldwide health threat. The advent of drug-resistant strains of the disease highlights the critical need for novel treatments. The unique cell wall of <i>M. tb</i> provides an extra layer of protection for the bacteria and hence only compounds that can penetrate this barrier can reach their targets within the bacterial cell wall. The creation of a reliable machine learning (ML) model to predict the mycobacterial cell wall permeability of small molecules is presented in this work and four ML algorithms, including Random Forest, Support Vector Machines (SVM), k-nearest Neighbour (k-NN) and Logistic Regression were trained on a dataset of 5368 compounds. RDKit and Mordred toolkits were used to calculate features. To determine the most effective model, various performance metrics were used such as accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve. The best-performing model was further refined with hyperparameter tuning and tenfold cross-validation. The SVM model with filtering outperformed the other machine learning models and demonstrated 80.26% and 81.13% accuracy on the test and validation datasets, respectively. The study also provided insights into the molecular descriptors that play the most important role in predicting the ability of a molecule to pass the <i>M. tb</i> cell wall, which could guide future compound design. The model is available at https://github.com/PGlab-NIPER/MTB_Permeability.</p></div>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":"28 4","pages":"2317 - 2329"},"PeriodicalIF":3.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Given the critical necessity for the development of more potent anti-cancer drugs, a series of novel compounds incorporating trifluoromethyl groups within the privileged 2-anilinoquinoline scaffold was designed, synthesized, and subjected to biological evaluation through a pharmacophore hybridization strategy. Upon evaluating the in vitro anti-cancer characteristics of the target compounds, it became clear that compound 8b, which contains a (4-(piperazin-1-yl)phenyl)amino substitution at the 2-position of the quinoline skeleton, displayed superior efficacy against four cancer cell lines by inducing apoptosis and cell cycle arrest. Following research conducted in a PC3 xenograft mouse model, it was found that compound 8b exhibited significant anti-cancer efficacy while demonstrating minimal toxicity. Additionally, the analysis of a 217-kinase panel pinpointed SGK1 as a potential target for this compound class with anti-cancer capabilities. This finding was further verified through molecular docking analysis and cellular thermal shift assays. To conclude, our results emphasize that compound 8b can be used as a lead compound for the development of anti-cancer drugs that target SGK1.
{"title":"Discovery of novel 4-trifluoromethyl-2-anilinoquinoline derivatives as potential anti-cancer agents targeting SGK1.","authors":"Guangcan Xu, Lanlan Li, Mengfan Lv, Cheng Li, Jia Yu, Xiaoping Zeng, Xueling Meng, Gang Yu, Kun Liu, Sha Cheng, Heng Luo, Bixue Xu","doi":"10.1007/s11030-024-10951-4","DOIUrl":"https://doi.org/10.1007/s11030-024-10951-4","url":null,"abstract":"<p><p>Given the critical necessity for the development of more potent anti-cancer drugs, a series of novel compounds incorporating trifluoromethyl groups within the privileged 2-anilinoquinoline scaffold was designed, synthesized, and subjected to biological evaluation through a pharmacophore hybridization strategy. Upon evaluating the in vitro anti-cancer characteristics of the target compounds, it became clear that compound 8b, which contains a (4-(piperazin-1-yl)phenyl)amino substitution at the 2-position of the quinoline skeleton, displayed superior efficacy against four cancer cell lines by inducing apoptosis and cell cycle arrest. Following research conducted in a PC3 xenograft mouse model, it was found that compound 8b exhibited significant anti-cancer efficacy while demonstrating minimal toxicity. Additionally, the analysis of a 217-kinase panel pinpointed SGK1 as a potential target for this compound class with anti-cancer capabilities. This finding was further verified through molecular docking analysis and cellular thermal shift assays. To conclude, our results emphasize that compound 8b can be used as a lead compound for the development of anti-cancer drugs that target SGK1.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141905435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A multicomponent synthesis of 1,8-naphthyridine with high yields utilizing benzaldehydes, malononitrile, phenol, and acetylenic esters in aqueous solution at room temperature in the presence of SiO2/Fe3O4 as a reusable catalyst is reported. Using the MTT test, the cytotoxic properties of all the produced compounds were assessed in vitro against cancer cell lines (MCF-7 and A549) and normal cell lines (BEAS-2B). It was discovered that the most effective cytotoxic agent, doxorubicin-like in its lack of selectivity, was the derivative 5h. On the other hand, the compound 5c might be regarded as an equipotent molecule with greater selectivity in relation to doxorubicin. Also, this study investigates the antioxidant effects of 1,8-naphthyridine carboxylates, along with other studies conducted in this study.
{"title":"Green synthesis and cytotoxic activity of functionalized naphthyridine.","authors":"Somayeh Soleimani-Amiri, Mahsa Hojjati, Zinatossadat Hossaini","doi":"10.1007/s11030-024-10929-2","DOIUrl":"https://doi.org/10.1007/s11030-024-10929-2","url":null,"abstract":"<p><p>A multicomponent synthesis of 1,8-naphthyridine with high yields utilizing benzaldehydes, malononitrile, phenol, and acetylenic esters in aqueous solution at room temperature in the presence of SiO<sub>2</sub>/Fe<sub>3</sub>O<sub>4</sub> as a reusable catalyst is reported. Using the MTT test, the cytotoxic properties of all the produced compounds were assessed in vitro against cancer cell lines (MCF-7 and A549) and normal cell lines (BEAS-2B). It was discovered that the most effective cytotoxic agent, doxorubicin-like in its lack of selectivity, was the derivative 5h. On the other hand, the compound 5c might be regarded as an equipotent molecule with greater selectivity in relation to doxorubicin. Also, this study investigates the antioxidant effects of 1,8-naphthyridine carboxylates, along with other studies conducted in this study.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141905436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1007/s11030-024-10953-2
Saud O Alshammari, Qamar A Alshammari
Anaplastic lymphoma kinase (ALK)-driven lung cancer represents a critical therapeutic target, demanding innovative approaches for the identification of effective inhibitors. Anaplastic lymphoma kinase (ALK), a key protein involved in the pathogenesis of ALK-driven lung cancers, has been the focus of extensive drug discovery efforts. This study employed a comprehensive computational drug discovery approach, integrating virtual screening with the Lipinski filter, re-docking, molecular dynamics (MD) simulations, and free energy calculations to identify potential inhibitors from a natural compound library. Utilizing the MTiOpenScreen web server, we screened for compounds that exhibit favorable interactions with ALK, resulting in 1227 compounds with virtual screening scores ranging from - 10.2 to - 3.7 kcal/mol. Subsequent re-docking of three selected compounds (ZINC000059779788, ZINC000043552589, and ZINC000003594862) and one reference compound against ALK yielded docking scores - 10.4, - 10.2, - 10.2, and - 10.1 kcal/mol, respectively. These compounds demonstrated promising interactions with ALK, suggesting potential inhibitory effects. Advanced analyses, including MD simulation and binding free energy calculations, further supported the potential efficacy of these compounds. MD simulations, particularly the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses, revealed that compounds ZINC000059779788 and ZINC000003594862 achieved better stability compared to compound ZINC000043552589. These stable conformations suggest effective binding over time. Free energy calculations using the MM/GBSA method showed that ZINC000059779788 had the most favorable binding energy, indicating a strong and stable interaction with the ALK protein. The promising computational findings from this study emphasize the necessity for additional experimental testing to verify the therapeutic efficacy of these natural compounds for treating lung cancers.
{"title":"Natural product-derived ALK inhibitors for treating ALK-driven lung cancers: an in silico study.","authors":"Saud O Alshammari, Qamar A Alshammari","doi":"10.1007/s11030-024-10953-2","DOIUrl":"https://doi.org/10.1007/s11030-024-10953-2","url":null,"abstract":"<p><p>Anaplastic lymphoma kinase (ALK)-driven lung cancer represents a critical therapeutic target, demanding innovative approaches for the identification of effective inhibitors. Anaplastic lymphoma kinase (ALK), a key protein involved in the pathogenesis of ALK-driven lung cancers, has been the focus of extensive drug discovery efforts. This study employed a comprehensive computational drug discovery approach, integrating virtual screening with the Lipinski filter, re-docking, molecular dynamics (MD) simulations, and free energy calculations to identify potential inhibitors from a natural compound library. Utilizing the MTiOpenScreen web server, we screened for compounds that exhibit favorable interactions with ALK, resulting in 1227 compounds with virtual screening scores ranging from - 10.2 to - 3.7 kcal/mol. Subsequent re-docking of three selected compounds (ZINC000059779788, ZINC000043552589, and ZINC000003594862) and one reference compound against ALK yielded docking scores - 10.4, - 10.2, - 10.2, and - 10.1 kcal/mol, respectively. These compounds demonstrated promising interactions with ALK, suggesting potential inhibitory effects. Advanced analyses, including MD simulation and binding free energy calculations, further supported the potential efficacy of these compounds. MD simulations, particularly the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses, revealed that compounds ZINC000059779788 and ZINC000003594862 achieved better stability compared to compound ZINC000043552589. These stable conformations suggest effective binding over time. Free energy calculations using the MM/GBSA method showed that ZINC000059779788 had the most favorable binding energy, indicating a strong and stable interaction with the ALK protein. The promising computational findings from this study emphasize the necessity for additional experimental testing to verify the therapeutic efficacy of these natural compounds for treating lung cancers.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141900555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Induction of autophagic death in cancer cells is one of the promising strategies for the development of anti-cancer therapeutics. In the present study, we designed and synthesized a series of isatin Schiff base derivatives containing thioether structures. After discovering the highly active target compound H13 (IC50 = 4.83 μM) based on in vitro antiproliferation, we also found it had a high safety against normal cells HEK293 with CC50 of 69.01 μM, indicating a sufficient therapeutic window. In addition, to provide reference for subsequent studies, a model was successfully constructed by Sybyl software. Preliminary mechanistic studies suggested that H13-induced apoptosis may be closely related to ROS accumulation and mitochondrial dysfunction. Subsequent studies revealed that H13 inhibited cell proliferation by inducing cellular autophagy mainly through blocking signal of the PI3K/AKT/mTOR pathway. Altogether, these results suggested that H13 was potentially valuable as a lead compound.
{"title":"Synthesis of novel 4-substituted isatin Schiff base derivatives as potential autophagy inducers and evaluation of their antitumour activity.","authors":"Huayuan Tan, Guanglong Zhang, Chenlu Xu, Xue Lei, Jiayi Chen, Haitao Long, Xuemei Qiu, Wenhang Wang, Yue Zhou, Danping Chen, Chengpeng Li, Zhurui Li, Zhenchao Wang","doi":"10.1007/s11030-024-10954-1","DOIUrl":"https://doi.org/10.1007/s11030-024-10954-1","url":null,"abstract":"<p><p>Induction of autophagic death in cancer cells is one of the promising strategies for the development of anti-cancer therapeutics. In the present study, we designed and synthesized a series of isatin Schiff base derivatives containing thioether structures. After discovering the highly active target compound H13 (IC<sub>50</sub> = 4.83 μM) based on in vitro antiproliferation, we also found it had a high safety against normal cells HEK293 with CC<sub>50</sub> of 69.01 μM, indicating a sufficient therapeutic window. In addition, to provide reference for subsequent studies, a model was successfully constructed by Sybyl software. Preliminary mechanistic studies suggested that H13-induced apoptosis may be closely related to ROS accumulation and mitochondrial dysfunction. Subsequent studies revealed that H13 inhibited cell proliferation by inducing cellular autophagy mainly through blocking signal of the PI3K/AKT/mTOR pathway. Altogether, these results suggested that H13 was potentially valuable as a lead compound.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141896438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-05DOI: 10.1007/s11030-024-10940-7
R Divya Mohan, Naveen V Kulkarni
Edaravone, a pyrazalone derivative, is an antioxidant and free radical scavenger used to treat oxidative stress-related diseases. It is a proven drug to mitigate conditions prevailing to oxidative stress by inhibiting lipid peroxidation, reducing inflammation, and thereby preventing endothelial cell death. In recent years, considerable interest has been given by researchers in the derivatization of edaravone by adding varieties of substituents of versatile steric and functional properties to improve its antioxidant and pharmacological activity. This review accounts all the important methods developed for the derivatization of edaravone and the impacts of the structural modifications on the antioxidant activity of the motif.
{"title":"Recent developments in the design of functional derivatives of edaravone and exploration of their antioxidant activities.","authors":"R Divya Mohan, Naveen V Kulkarni","doi":"10.1007/s11030-024-10940-7","DOIUrl":"https://doi.org/10.1007/s11030-024-10940-7","url":null,"abstract":"<p><p>Edaravone, a pyrazalone derivative, is an antioxidant and free radical scavenger used to treat oxidative stress-related diseases. It is a proven drug to mitigate conditions prevailing to oxidative stress by inhibiting lipid peroxidation, reducing inflammation, and thereby preventing endothelial cell death. In recent years, considerable interest has been given by researchers in the derivatization of edaravone by adding varieties of substituents of versatile steric and functional properties to improve its antioxidant and pharmacological activity. This review accounts all the important methods developed for the derivatization of edaravone and the impacts of the structural modifications on the antioxidant activity of the motif.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141888107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The deep molecular generative model has recently become a research hotspot in pharmacy. This paper analyzes a large number of recent reports and reviews these models. In the central part of this paper, four compound databases and two molecular representation methods are compared. Five model architectures and applications for deep molecular generative models are emphatically introduced. Three evaluation metrics for model evaluation are listed. Finally, the limitations and challenges in this field are discussed to provide a reference and basis for developing and researching new models published in future.
Graphical abstract
Artificial intelligence has made significant leaps with the rapid development of big data and high-performance computing technology. As a technical means, artificial intelligence and deep learning have been deeply applied in all aspects of drug research, equipping researchers with innovative solutions and insights.