Discovery of novel 5-oxa-2,6-diazaspiro[3.4]oct-6-ene derivatives as potent, selective, and orally available somatostatin receptor subtype 5 (SSTR5) antagonists for treatment of type 2 diabetes mellitus

Hirose, Hideki; Yamasaki, Takahiro; Ogino, Masao; Mizojiri, Ryo; Tamura-Okano, Yumiko; Yashiro, Hiroaki; Muraki, Yo; Nakano, Yukiko I.; Sugama, Jun; Hata, Akito; Iwasaki, Shinji; Watanabe, Masanori; Maekawa, Taira; Kasai, Shizuo

doi:10.1016/j.bmc.2017.06.007

Cited by 22 publications

(24 citation statements)

References 32 publications

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“…In the past few years, orally available and subtype-selective SST agonists and antagonists have been synthesized. Some of these substances may become lead compounds for potential new therapeutic indications directed toward individual SSTs ( He et al, 2014 ; Hirose et al, 2017 ).…”

Section: Introduction and Historical Perspectivementioning

confidence: 99%

International Union of Basic and Clinical Pharmacology. CV. Somatostatin Receptors: Structure, Function, Ligands, and New Nomenclature

et al. 2018

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Somatostatin, also known as somatotropin-release inhibitory factor, is a cyclopeptide that exerts potent inhibitory actions on hormone secretion and neuronal excitability. Its physiologic functions are mediated by five G protein–coupled receptors (GPCRs) called somatostatin receptor (SST)1–5. These five receptors share common structural features and signaling mechanisms but differ in their cellular and subcellular localization and mode of regulation. SST2 and SST5 receptors have evolved as primary targets for pharmacological treatment of pituitary adenomas and neuroendocrine tumors. In addition, SST2 is a prototypical GPCR for the development of peptide-based radiopharmaceuticals for diagnostic and therapeutic interventions. This review article summarizes findings published in the last 25 years on the physiology, pharmacology, and clinical applications related to SSTs. We also discuss potential future developments and propose a new nomenclature.

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Section: Introduction and Historical Perspectivementioning

confidence: 99%

International Union of Basic and Clinical Pharmacology. CV. Somatostatin Receptors: Structure, Function, Ligands, and New Nomenclature

et al. 2018

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“…More specifically, keywords including “aryl,” “heteroaryl,” and “phenyl” indicate that chemical drugs are a main focus of those patent documents [41]. The top 10 topic keywords also evolved over time; for example, “propionic acid” only appeared during 1995-2000 [42], “valeric acid” appeared during 2004-2006 [43], “indole” appeared during 2008-2009 [43,44], “naphthalen” appeared in 2015 [45], and “diazaspiro” appeared during 2016-2017 [46]. These keywords highlighted the significance of different chemical compounds or functional groups in the development of antidiabetic drugs over years.…”

Section: Resultsmentioning

confidence: 99%

Technological Innovations in Disease Management: Text Mining US Patent Data From 1995 to 2017

Huang¹,

Zolnoori²,

Balls-Berry³

et al. 2019

J Med Internet Res

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Background Patents are important intellectual property protecting technological innovations that inspire efficient research and development in biomedicine. The number of awarded patents serves as an important indicator of economic growth and technological innovation. Researchers have mined patents to characterize the focuses and trends of technological innovations in many fields. Objective To expand patent mining to biomedicine and facilitate future resource allocation in biomedical research for the United States, we analyzed US patent documents to determine the focuses and trends of protected technological innovations across the entire disease landscape. Methods We analyzed more than 5 million US patent documents between 1995 and 2017, using summary statistics and dynamic topic modeling. More specifically, we investigated the disease coverage and latent topics in patent documents over time. We also incorporated the patent data into the calculation of our recently developed Research Opportunity Index (ROI) and Public Health Index (PHI), to recalibrate the resource allocation in biomedical research. Results Our analysis showed that protected technological innovations have been primarily focused on socioeconomically critical diseases such as “other cancers” (malignant neoplasm of head, face, neck, abdomen, pelvis, or limb; disseminated malignant neoplasm; Merkel cell carcinoma; and malignant neoplasm, malignant carcinoid tumors, neuroendocrine tumor, and carcinoma in situ of an unspecified site), diabetes mellitus, and obesity. The United States has significantly improved resource allocation to biomedical research and development over the past 17 years, as illustrated by the decreasing PHI. Diseases with positive ROI, such as ankle and foot fracture, indicate potential research opportunities for the future. Development of novel chemical or biological drugs and electrical devices for diagnosis and disease management is the dominating topic in patented inventions. Conclusions This multifaceted analysis of patent documents provides a deep understanding of the focuses and trends of technological innovations in disease management in patents. Our findings offer insights into future research and innovation opportunities and provide actionable information to facilitate policy makers, payers, and investors to make better evidence-based decisions regarding resource allocation in biomedicine.

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“…Hou et al [44] and Olesen et al [45] demonstrated that DACT2 and KCND3 were found to be substantially related to atrial fibrillation. Ge and Concannon [46], Ferjeni et al [47], Anquetil et al [48], Glawe et al [49], Kawabata et al [50], Li et al [51], Buraczynska et al [52], Amini et al [53], Yang et al [54], Du Toit et al [55], Hirose et al [56], Zhang et al [57], Griffin et al [58], Zouidi et al [59], Trombetta et al [60], Alharbi et al [61], Ikarashi et al [62], Dharmadhikari et al [63], Sutton et al [64] and Deng et al [65] reported that UBASH3A, ZAP70, IDO1, ITGAL (integrin subunit alpha L). ITGB7, RASGRP1, CNR1, SLC2A1, SLC11A1, GPR84, SSTR5, KCNB1, GLUL (glutamate-ammonia ligase), BANK1, CACNA1E, LGR5, AQP3, SIGLEC7, SSTR2 and DNER (delta/notch like EGF repeat containing) could be an index for diabetes, but these genes might be responsible for progression of HF.…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

Vastrad¹,

Tengli

Vastrad³

2021

Preprint

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Heart failure (HF) is a heterogeneous clinical syndrome and affects millions of people all over the world. HF occurs when the cardiac overload and injury, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental HF as well as to explore active drug molecules. The expression profiling by high throughput sequencing of GSE141910 dataset was downloaded from the Gene Expression Omnibus (GEO) database, which contained 366 samples, including 200 heart failure samples and 166 non heart failure samples. The raw data was integrated to find differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. Gene ontology (GO) and REACTOME enrichment analyses were performed via ToppGene; protein-protein interaction (PPI) networks of the DEGs was constructed based on data from the HiPPIE interactome database; modules analysis was performed; target gene - miRNA regulatory network and target gene - TF regulatory network were constructed and analyzed; hub genes were validated; molecular docking studies was performed. A total of 881 DEGs, including 442 up regulated genes and 439 down regulated genes were observed. Most of the DEGs were significantly enriched in biological adhesion, extracellular matrix, signaling receptor binding, secretion, intrinsic component of plasma membrane, signaling receptor activity, extracellular matrix organization and neutrophil degranulation. The top hub genes ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 were identified from the PPI network. Module analysis revealed that HF was associated with adaptive immune system and neutrophil degranulation. The target genes, miRNAs and TFs were identified from the target gene - miRNA regulatory network and target gene - TF regulatory network. Furthermore, receiver operating characteristic (ROC) curve analysis and RT-PCR analysis revealed that ESR1, PYHIN1, PPP2R2B, LCK, TP63, PCLAF, CFTR, TK1, ECT2 and FKBP5 might serve as prognostic, diagnostic biomarkers and therapeutic target for HF. The predicted targets of these active molecules were then confirmed. The current investigation identified a series of key genes and pathways that might be involved in the progression of HF, providing a new understanding of the underlying molecular mechanisms of HF.

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Discovery of novel 5-oxa-2,6-diazaspiro[3.4]oct-6-ene derivatives as potent, selective, and orally available somatostatin receptor subtype 5 (SSTR5) antagonists for treatment of type 2 diabetes mellitus

Cited by 22 publications

References 32 publications

International Union of Basic and Clinical Pharmacology. CV. Somatostatin Receptors: Structure, Function, Ligands, and New Nomenclature

International Union of Basic and Clinical Pharmacology. CV. Somatostatin Receptors: Structure, Function, Ligands, and New Nomenclature

Technological Innovations in Disease Management: Text Mining US Patent Data From 1995 to 2017

Identification of candidate biomarkers and therapeutic agents for heart failure by bioinformatics analysis

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