P K Dey, R Dutta, M Ray, P Jakkula, S Banerjee, I A Qureshi, S Gayen, S A Amin
{"title":"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。","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":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":" ","pages":"483-504"},"PeriodicalIF":2.3000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":21446,\"journal\":{\"name\":\"SAR and QSAR in Environmental Research\",\"volume\":\" \",\"pages\":\"483-504\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SAR and QSAR in Environmental Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1080/1062936X.2024.2366886\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/21 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAR and QSAR in Environmental Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/1062936X.2024.2366886","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/21 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management.
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.
期刊介绍:
SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.