{"title":"通过计算方法揭示artopetelin类黄酮作为过氧化物酶体增殖物激活受体- δ (PPARδ)激动剂的治疗潜力","authors":"Ram Lal Swagat Shrestha , Ashika Tamang , Manila Poudel , M.C. Shiva , Nirmal Parajuli , Aakar Shrestha , Timila Shrestha , Samjhana Bharati , Binita Maharjan , Bishnu P. Marasini , Jhashanath Adhikari Subin","doi":"10.1016/j.jmgm.2025.109105","DOIUrl":null,"url":null,"abstract":"<div><div>Diabetes mellitus is a growing global health concern, with peroxisome proliferator-activated receptor-delta (PPARδ) emerging as a promising therapeutic target due to its role in glucose regulation. Flavonoids, a class of plant-derived bioactive compounds, are known for their anti-diabetic properties. The present study aims to explore the potential of artopetelin flavonoids as PPARδ activators using a range of computational approaches. Molecular docking (MD) calculations identified six artopetelin ligands with binding affinities surpassing those of the native ligand (−10.4 kcal/mol) and the reference drugs such as elafibranor (−10.0 kcal/mol) and seladelpar (−9.8 kcal/mol). The highest binding affinity was obtained for artopetelin A, with a value of −11.8 kcal/mol. All candidates, except artopetelin B, were bound at the receptor's catalytic site, suggesting potential for competitive activation. Molecular dynamics simulations (MDS) of the top five complexes revealed structural stability, with consistent root mean square deviation (RMSD) profiles and stable hydrogen bonding patterns. Gibbs free energy changes (ΔG<sub>BFE</sub> < 0) confirmed the sustained thermodynamic spontaneity of complex formation reactions where the values ranged from −39.88 to −26.66 kcal/mol. Pharmacokinetic predictions <em>via</em> pkCSM indicated favorable drug-likeness and ADMET profiles. These preliminary <em>in silico</em> findings highlight the strong potential of top five artopetelin flavonoids as PPARδ activators for type 2 diabetes management, underscoring their promise as plant-derived therapeutic agents and warranting further experimental validation.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"140 ","pages":"Article 109105"},"PeriodicalIF":3.0000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unveiling the therapeutic potential of artopetelin flavonoids through computational approaches as peroxisome proliferator-activated receptor-delta (PPARδ) agonists\",\"authors\":\"Ram Lal Swagat Shrestha , Ashika Tamang , Manila Poudel , M.C. Shiva , Nirmal Parajuli , Aakar Shrestha , Timila Shrestha , Samjhana Bharati , Binita Maharjan , Bishnu P. Marasini , Jhashanath Adhikari Subin\",\"doi\":\"10.1016/j.jmgm.2025.109105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Diabetes mellitus is a growing global health concern, with peroxisome proliferator-activated receptor-delta (PPARδ) emerging as a promising therapeutic target due to its role in glucose regulation. Flavonoids, a class of plant-derived bioactive compounds, are known for their anti-diabetic properties. The present study aims to explore the potential of artopetelin flavonoids as PPARδ activators using a range of computational approaches. Molecular docking (MD) calculations identified six artopetelin ligands with binding affinities surpassing those of the native ligand (−10.4 kcal/mol) and the reference drugs such as elafibranor (−10.0 kcal/mol) and seladelpar (−9.8 kcal/mol). The highest binding affinity was obtained for artopetelin A, with a value of −11.8 kcal/mol. All candidates, except artopetelin B, were bound at the receptor's catalytic site, suggesting potential for competitive activation. Molecular dynamics simulations (MDS) of the top five complexes revealed structural stability, with consistent root mean square deviation (RMSD) profiles and stable hydrogen bonding patterns. Gibbs free energy changes (ΔG<sub>BFE</sub> < 0) confirmed the sustained thermodynamic spontaneity of complex formation reactions where the values ranged from −39.88 to −26.66 kcal/mol. Pharmacokinetic predictions <em>via</em> pkCSM indicated favorable drug-likeness and ADMET profiles. These preliminary <em>in silico</em> findings highlight the strong potential of top five artopetelin flavonoids as PPARδ activators for type 2 diabetes management, underscoring their promise as plant-derived therapeutic agents and warranting further experimental validation.</div></div>\",\"PeriodicalId\":16361,\"journal\":{\"name\":\"Journal of molecular graphics & modelling\",\"volume\":\"140 \",\"pages\":\"Article 109105\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of molecular graphics & modelling\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1093326325001652\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of molecular graphics & modelling","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1093326325001652","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Unveiling the therapeutic potential of artopetelin flavonoids through computational approaches as peroxisome proliferator-activated receptor-delta (PPARδ) agonists
Diabetes mellitus is a growing global health concern, with peroxisome proliferator-activated receptor-delta (PPARδ) emerging as a promising therapeutic target due to its role in glucose regulation. Flavonoids, a class of plant-derived bioactive compounds, are known for their anti-diabetic properties. The present study aims to explore the potential of artopetelin flavonoids as PPARδ activators using a range of computational approaches. Molecular docking (MD) calculations identified six artopetelin ligands with binding affinities surpassing those of the native ligand (−10.4 kcal/mol) and the reference drugs such as elafibranor (−10.0 kcal/mol) and seladelpar (−9.8 kcal/mol). The highest binding affinity was obtained for artopetelin A, with a value of −11.8 kcal/mol. All candidates, except artopetelin B, were bound at the receptor's catalytic site, suggesting potential for competitive activation. Molecular dynamics simulations (MDS) of the top five complexes revealed structural stability, with consistent root mean square deviation (RMSD) profiles and stable hydrogen bonding patterns. Gibbs free energy changes (ΔGBFE < 0) confirmed the sustained thermodynamic spontaneity of complex formation reactions where the values ranged from −39.88 to −26.66 kcal/mol. Pharmacokinetic predictions via pkCSM indicated favorable drug-likeness and ADMET profiles. These preliminary in silico findings highlight the strong potential of top five artopetelin flavonoids as PPARδ activators for type 2 diabetes management, underscoring their promise as plant-derived therapeutic agents and warranting further experimental validation.
期刊介绍:
The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design.
As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.