{"title":"通过对锌天然产物数据库的计算机筛选,获得了针对2型糖尿病肾衰竭的新发现","authors":"Neda Shakour , Saeideh Hoseinpoor , Saghi Sepehri , Mehrdad Iranshahi , Mohaddeseh Badpeyma , Farzin Hadizadeh","doi":"10.1016/j.jocs.2024.102497","DOIUrl":null,"url":null,"abstract":"<div><div>Renal dysfunction is a common and potentially fatal consequence often noticed in persons who have been diagnosed with type 2 diabetes mellitus (T2DM). The gravity of this complication is underscored by the heightened likelihood of death linked to its advancement. Therefore, it is crucial to prioritize the prevention of the progress of renal impairment. The efficacy of sodium-glucose cotransporter 2 (SGLT2) inhibitors in retarding the advancement of renal dysfunction and albuminuria has been demonstrated, underscoring their potential utility in the management of renal problems. In a quest to unearth natural SGLT2 inhibitors, a comprehensive study was undertaken, encompassing structure-based virtual screening and a range of tools deployed to separate through the extensive ZINC database. Through the application of a pharmacophore model, a cohort of 11,336 natural compounds were discerned from the ZINC database that could potentially serve as SGLT2 inhibitors. Amid this collection, two compounds were singled out via a rigorous assessment of ADME (absorption, distribution, metabolism, and excretion) attributes, oral bioavailability, molecular dynamics parameters, and akin docking affinities to approved inhibitors. Compound <strong>580</strong> emerged as a promising candidate, validated by its congruence with metabolic processes and the absence of proclivities toward cardiotoxic effects. The findings from this investigation serve to reinforce the validation of SGLT2 inhibitors, thus paving the way for comprehensive in vitro and in vivo experimentation. Concurrently, these outcomes act as a catalyst for the innovation of novel inhibitors, heralding a new era of possibilities.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"85 ","pages":"Article 102497"},"PeriodicalIF":3.1000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel hits for targeting kidney failure in type 2 diabetes derived via in silico screening of the ZINC natural product database\",\"authors\":\"Neda Shakour , Saeideh Hoseinpoor , Saghi Sepehri , Mehrdad Iranshahi , Mohaddeseh Badpeyma , Farzin Hadizadeh\",\"doi\":\"10.1016/j.jocs.2024.102497\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Renal dysfunction is a common and potentially fatal consequence often noticed in persons who have been diagnosed with type 2 diabetes mellitus (T2DM). The gravity of this complication is underscored by the heightened likelihood of death linked to its advancement. Therefore, it is crucial to prioritize the prevention of the progress of renal impairment. The efficacy of sodium-glucose cotransporter 2 (SGLT2) inhibitors in retarding the advancement of renal dysfunction and albuminuria has been demonstrated, underscoring their potential utility in the management of renal problems. In a quest to unearth natural SGLT2 inhibitors, a comprehensive study was undertaken, encompassing structure-based virtual screening and a range of tools deployed to separate through the extensive ZINC database. Through the application of a pharmacophore model, a cohort of 11,336 natural compounds were discerned from the ZINC database that could potentially serve as SGLT2 inhibitors. Amid this collection, two compounds were singled out via a rigorous assessment of ADME (absorption, distribution, metabolism, and excretion) attributes, oral bioavailability, molecular dynamics parameters, and akin docking affinities to approved inhibitors. Compound <strong>580</strong> emerged as a promising candidate, validated by its congruence with metabolic processes and the absence of proclivities toward cardiotoxic effects. The findings from this investigation serve to reinforce the validation of SGLT2 inhibitors, thus paving the way for comprehensive in vitro and in vivo experimentation. Concurrently, these outcomes act as a catalyst for the innovation of novel inhibitors, heralding a new era of possibilities.</div></div>\",\"PeriodicalId\":48907,\"journal\":{\"name\":\"Journal of Computational Science\",\"volume\":\"85 \",\"pages\":\"Article 102497\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Science\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1877750324002904\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Science","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877750324002904","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Novel hits for targeting kidney failure in type 2 diabetes derived via in silico screening of the ZINC natural product database
Renal dysfunction is a common and potentially fatal consequence often noticed in persons who have been diagnosed with type 2 diabetes mellitus (T2DM). The gravity of this complication is underscored by the heightened likelihood of death linked to its advancement. Therefore, it is crucial to prioritize the prevention of the progress of renal impairment. The efficacy of sodium-glucose cotransporter 2 (SGLT2) inhibitors in retarding the advancement of renal dysfunction and albuminuria has been demonstrated, underscoring their potential utility in the management of renal problems. In a quest to unearth natural SGLT2 inhibitors, a comprehensive study was undertaken, encompassing structure-based virtual screening and a range of tools deployed to separate through the extensive ZINC database. Through the application of a pharmacophore model, a cohort of 11,336 natural compounds were discerned from the ZINC database that could potentially serve as SGLT2 inhibitors. Amid this collection, two compounds were singled out via a rigorous assessment of ADME (absorption, distribution, metabolism, and excretion) attributes, oral bioavailability, molecular dynamics parameters, and akin docking affinities to approved inhibitors. Compound 580 emerged as a promising candidate, validated by its congruence with metabolic processes and the absence of proclivities toward cardiotoxic effects. The findings from this investigation serve to reinforce the validation of SGLT2 inhibitors, thus paving the way for comprehensive in vitro and in vivo experimentation. Concurrently, these outcomes act as a catalyst for the innovation of novel inhibitors, heralding a new era of possibilities.
期刊介绍:
Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory.
The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation.
This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.
Computational science typically unifies three distinct elements:
• Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous);
• Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;
• Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).