Arka Das , Gurubasavaraja Swamy Purawarga Matada , Prasad Sanjay Dhiwar , Nulgumnalli Manjunathaiah Raghavendra , Nahid Abbas , Ekta Singh , Abhishek Ghara , Ganesh Prasad Shenoy
{"title":"基于药物相似性、分子对接和分子动力学的虚拟筛选策略对一些新型mTOR激酶抑制剂的分子识别以开发抗癌线索","authors":"Arka Das , Gurubasavaraja Swamy Purawarga Matada , Prasad Sanjay Dhiwar , Nulgumnalli Manjunathaiah Raghavendra , Nahid Abbas , Ekta Singh , Abhishek Ghara , Ganesh Prasad Shenoy","doi":"10.1016/j.comtox.2022.100257","DOIUrl":null,"url":null,"abstract":"<div><p>Cancer is the second leading cause of death worldwide. Among various anticancer drug targets, mTOR is noteworthy. Numerous first-generation mTOR inhibitors are already approved and few second-generation mTOR inhibitors targeting the kinase domain are in the clinical trials, but yet to reach the market, and many lead to serious toxicities. Here we are focused to discover some novel kinase inhibitors from the ZINC database which may effectively inhibit mTOR kinase. For this, computational chemistry and pharmacophore-based ZINC database search has been adopted. Series of virtual screening analysis lead to the discovery of 5 active hits. Among these 5, compound 4 (<strong>ZINC79476038</strong>) having binding energy of −8.9 Kcal/mol shows maximum interactions within the binding pocket. Study proved that all these compounds can potentially inhibit mTOR kinase and can be successfully developed as anticancer agents. We further proved that these compounds are not only active for general cancers like lung, breast, colon, and other peripheral cancers but also equally active in CNS, targeting numerous brain cancers.</p></div>","PeriodicalId":72666,"journal":{"name":"","volume":"25 ","pages":"Article 100257"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Molecular recognition of some novel mTOR kinase inhibitors to develop anticancer leads by drug-likeness, molecular docking and molecular dynamics based virtual screening strategy\",\"authors\":\"Arka Das , Gurubasavaraja Swamy Purawarga Matada , Prasad Sanjay Dhiwar , Nulgumnalli Manjunathaiah Raghavendra , Nahid Abbas , Ekta Singh , Abhishek Ghara , Ganesh Prasad Shenoy\",\"doi\":\"10.1016/j.comtox.2022.100257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Cancer is the second leading cause of death worldwide. Among various anticancer drug targets, mTOR is noteworthy. Numerous first-generation mTOR inhibitors are already approved and few second-generation mTOR inhibitors targeting the kinase domain are in the clinical trials, but yet to reach the market, and many lead to serious toxicities. Here we are focused to discover some novel kinase inhibitors from the ZINC database which may effectively inhibit mTOR kinase. For this, computational chemistry and pharmacophore-based ZINC database search has been adopted. Series of virtual screening analysis lead to the discovery of 5 active hits. Among these 5, compound 4 (<strong>ZINC79476038</strong>) having binding energy of −8.9 Kcal/mol shows maximum interactions within the binding pocket. Study proved that all these compounds can potentially inhibit mTOR kinase and can be successfully developed as anticancer agents. We further proved that these compounds are not only active for general cancers like lung, breast, colon, and other peripheral cancers but also equally active in CNS, targeting numerous brain cancers.</p></div>\",\"PeriodicalId\":72666,\"journal\":{\"name\":\"\",\"volume\":\"25 \",\"pages\":\"Article 100257\"},\"PeriodicalIF\":0.0,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111322000457\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111322000457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Molecular recognition of some novel mTOR kinase inhibitors to develop anticancer leads by drug-likeness, molecular docking and molecular dynamics based virtual screening strategy
Cancer is the second leading cause of death worldwide. Among various anticancer drug targets, mTOR is noteworthy. Numerous first-generation mTOR inhibitors are already approved and few second-generation mTOR inhibitors targeting the kinase domain are in the clinical trials, but yet to reach the market, and many lead to serious toxicities. Here we are focused to discover some novel kinase inhibitors from the ZINC database which may effectively inhibit mTOR kinase. For this, computational chemistry and pharmacophore-based ZINC database search has been adopted. Series of virtual screening analysis lead to the discovery of 5 active hits. Among these 5, compound 4 (ZINC79476038) having binding energy of −8.9 Kcal/mol shows maximum interactions within the binding pocket. Study proved that all these compounds can potentially inhibit mTOR kinase and can be successfully developed as anticancer agents. We further proved that these compounds are not only active for general cancers like lung, breast, colon, and other peripheral cancers but also equally active in CNS, targeting numerous brain cancers.