Pub Date : 2024-07-03DOI: 10.2174/0115743624311471240703071345
Arya Moftakhar, S. E. Khoshnam, Maryam Farzaneh, Mahrokh Abouali Gale Dari
Long non-coding RNAs (lncRNAs), characterized by their length exceeding 200 nucleotides and lack of protein-coding capacity, are intricately associated with a wide array of cellular processes, encompassing cell invasion, differentiation, proliferation, migration, apoptosis, and regeneration. Perturbations in lncRNA expression have been observed in numerous diseases and have emerged as pivotal players in the pathogenesis of diverse tumor types. Glioblastoma, a highly malignant primary tumor of the central nervous system (CNS), remains a formidable challenge even with the advent of novel therapeutic interventions, as primary glioblastomas invariably exhibit therapy resistance and aggressive behavior. Glioblastomas can arise from progenitor cells or neuroglial stem cells, revealing profound cellular heterogeneity, notably in the form of glioblastoma stem cells (GSCs) possessing stem-like properties. Glioblastomas comprise neural precursors that harbor essential characteristics of neural stem cells (NSCs). Several signaling pathways have been implicated in the regulation of self-renewal in both cancer cells and stem cells. In addition to their involvement in therapy resistance and survival of glioblastoma, lncRNAs are implicated in the modulation of GSC behaviors through diverse pathways and the intricate regulation of various genes and proteins. This review aims to comprehensively discuss the interplay between lncRNAs, their associated pathways, and GSCs, shedding light on their potential implications in glioblastoma.
{"title":"Functional Roles of Long Non-coding RNAs on Stem Cell-related Pathways in Glioblastoma","authors":"Arya Moftakhar, S. E. Khoshnam, Maryam Farzaneh, Mahrokh Abouali Gale Dari","doi":"10.2174/0115743624311471240703071345","DOIUrl":"https://doi.org/10.2174/0115743624311471240703071345","url":null,"abstract":"\u0000\u0000Long non-coding RNAs (lncRNAs), characterized by their length exceeding 200 nucleotides\u0000and lack of protein-coding capacity, are intricately associated with a wide array of cellular\u0000processes, encompassing cell invasion, differentiation, proliferation, migration, apoptosis,\u0000and regeneration. Perturbations in lncRNA expression have been observed in numerous diseases\u0000and have emerged as pivotal players in the pathogenesis of diverse tumor types. Glioblastoma, a\u0000highly malignant primary tumor of the central nervous system (CNS), remains a formidable\u0000challenge even with the advent of novel therapeutic interventions, as primary glioblastomas invariably\u0000exhibit therapy resistance and aggressive behavior. Glioblastomas can arise from progenitor\u0000cells or neuroglial stem cells, revealing profound cellular heterogeneity, notably in the\u0000form of glioblastoma stem cells (GSCs) possessing stem-like properties. Glioblastomas comprise\u0000neural precursors that harbor essential characteristics of neural stem cells (NSCs). Several\u0000signaling pathways have been implicated in the regulation of self-renewal in both cancer cells\u0000and stem cells. In addition to their involvement in therapy resistance and survival of glioblastoma,\u0000lncRNAs are implicated in the modulation of GSC behaviors through diverse pathways and\u0000the intricate regulation of various genes and proteins. This review aims to comprehensively discuss\u0000the interplay between lncRNAs, their associated pathways, and GSCs, shedding light on\u0000their potential implications in glioblastoma.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"83 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-24DOI: 10.2174/0115743624282326240418104054
Anuradha Mehra, Aryan Mehra
Deficiency of insulin signaling in type 2 diabetes results from insulin resistance or defective insulin secretion and induced hyperglycemia. By reducing glycated hemoglobin, SGLT2 inhibitors improve hyperuricemia, blood lipids, and weight loss without increasing the risk of hypoglycemia. By targeting this pathway, SGLT2 inhibitors can become a prominent target in the management of type 2 diabetes. This study aimed to carry out the molecular docking and ADMET prediction of novel imidazo(2,1-b)-1,3,4 thiadiazole derivatives as SGLT2 inhibitors. The chemical structures of 108 molecules were drawn by using ChemDraw Professional 15.0. Further, their energy minimization was also carried out by using Chem Bio Draw three-dimensional (3D) Ultra 12.0. Molecular docking was also carried out using a Molegro Virtual Docker to identify the best-fitting molecules and to identify the potential leads on the basis of dock score. The predicted parameters of drug-likeness according to Lipinski’s rule of five, such as molecular weight, log P, hydrogen bond acceptor, hydrogen bond donors, and number of rotatable bonds of the selected compounds, were predicted using pKCSM software. About 108 molecules were designed by employing different substitutions on imidazothiadiazole nucleus as SGLT2 inhibitors. Out of these, 10 compounds were found to have better interactions with the active site of SGLT2 protein and the highest dock scores compared to canagliflozin. Compounds 39a and 39b demonstrated good interactions and the highest docking scores of -155.428 and -142.786, respectively. The in silico physicochemical properties of the best compounds were also determined. Additionally, these compounds suggested a good pharmacokinetic profile as per Lipinski's rule of five (orally active drugs). Novel imidazo (2,1-b)-1,3,4 thiadiazole derivatives were strategically designed, and their binding affinity was meticulously evaluated against the SGLT2 protein. This endeavor yielded pioneering lead compounds characterized by ultimate binding affinity, coupled with optimal ADMET properties in adherence to Lipinski's rule of five and favourable noncarcinogenic profile.
{"title":"Antidiabetic Advancements In Silico: Pioneering Novel Heterocyclic\u0000Derivatives through Computational Design","authors":"Anuradha Mehra, Aryan Mehra","doi":"10.2174/0115743624282326240418104054","DOIUrl":"https://doi.org/10.2174/0115743624282326240418104054","url":null,"abstract":"\u0000\u0000Deficiency of insulin signaling in type 2 diabetes results from insulin\u0000resistance or defective insulin secretion and induced hyperglycemia. By reducing glycated hemoglobin,\u0000SGLT2 inhibitors improve hyperuricemia, blood lipids, and weight loss without increasing\u0000the risk of hypoglycemia. By targeting this pathway, SGLT2 inhibitors can become a\u0000prominent target in the management of type 2 diabetes.\u0000\u0000\u0000\u0000This study aimed to carry out the molecular docking and ADMET prediction of novel\u0000imidazo(2,1-b)-1,3,4 thiadiazole derivatives as SGLT2 inhibitors.\u0000\u0000\u0000\u0000The chemical structures of 108 molecules were drawn by using ChemDraw Professional\u000015.0. Further, their energy minimization was also carried out by using Chem Bio Draw\u0000three-dimensional (3D) Ultra 12.0. Molecular docking was also carried out using a Molegro Virtual\u0000Docker to identify the best-fitting molecules and to identify the potential leads on the basis\u0000of dock score. The predicted parameters of drug-likeness according to Lipinski’s rule of five,\u0000such as molecular weight, log P, hydrogen bond acceptor, hydrogen bond donors, and number of\u0000rotatable bonds of the selected compounds, were predicted using pKCSM software.\u0000\u0000\u0000\u0000About 108 molecules were designed by employing different substitutions on imidazothiadiazole\u0000nucleus as SGLT2 inhibitors. Out of these, 10 compounds were found to have better\u0000interactions with the active site of SGLT2 protein and the highest dock scores compared to\u0000canagliflozin. Compounds 39a and 39b demonstrated good interactions and the highest docking\u0000scores of -155.428 and -142.786, respectively. The in silico physicochemical properties of the\u0000best compounds were also determined. Additionally, these compounds suggested a good pharmacokinetic\u0000profile as per Lipinski's rule of five (orally active drugs).\u0000\u0000\u0000\u0000Novel imidazo (2,1-b)-1,3,4 thiadiazole derivatives were strategically designed,\u0000and their binding affinity was meticulously evaluated against the SGLT2 protein. This endeavor\u0000yielded pioneering lead compounds characterized by ultimate binding affinity, coupled with optimal\u0000ADMET properties in adherence to Lipinski's rule of five and favourable noncarcinogenic\u0000profile.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"60 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140664228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}