Priyanka Shah, Sumit Kumar, Sunita Tiwari, Mohammad Imran Siddiqi
{"title":"采用分子动力学、对接和基于遗传算法的方法,对恶性疟原虫二氢烟酸脱氢酶抑制剂的三唑并嘧啶衍生物进行 3D-QSAR 研究。","authors":"Priyanka Shah, Sumit Kumar, Sunita Tiwari, Mohammad Imran Siddiqi","doi":"10.1007/s12154-012-0072-3","DOIUrl":null,"url":null,"abstract":"<p><p>A series of 35 triazolopyrimidine analogues reported as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors were optimized using quantum mechanics methods, and their binding conformations were studied by docking and 3D quantitative structure-activity relationship studies. Genetic algorithm-based criteria was adopted for selection of training and test sets while maintaining structural diversity of training and test sets, which is also very crucial for model development and validation. Both the comparative molecular field analyses ([Formula: see text], [Formula: see text]) and comparative molecular similarity indices analyses ([Formula: see text], [Formula: see text]) show excellent correlation and high predictive power. Furthermore, molecular dynamics simulations were performed to explore the binding mode of the two of the most active compounds of the series, 10 and 14. Harmonization in the two simulation results validate the analysis and therefore applicability of docking parameters based on crystallographic conformation of compound 14 bound to receptor molecule. This work provides useful information about the inhibition mechanism of this class of molecules and will assist in the design of more potent inhibitors of PfDHODH.</p>","PeriodicalId":15296,"journal":{"name":"Journal of Chemical Biology","volume":"5 3","pages":"91-103"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3375378/pdf/12154_2012_Article_72.pdf","citationCount":"0","resultStr":"{\"title\":\"3D-QSAR studies of triazolopyrimidine derivatives of Plasmodium falciparum dihydroorotate dehydrogenase inhibitors using a combination of molecular dynamics, docking, and genetic algorithm-based methods.\",\"authors\":\"Priyanka Shah, Sumit Kumar, Sunita Tiwari, Mohammad Imran Siddiqi\",\"doi\":\"10.1007/s12154-012-0072-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A series of 35 triazolopyrimidine analogues reported as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors were optimized using quantum mechanics methods, and their binding conformations were studied by docking and 3D quantitative structure-activity relationship studies. Genetic algorithm-based criteria was adopted for selection of training and test sets while maintaining structural diversity of training and test sets, which is also very crucial for model development and validation. Both the comparative molecular field analyses ([Formula: see text], [Formula: see text]) and comparative molecular similarity indices analyses ([Formula: see text], [Formula: see text]) show excellent correlation and high predictive power. Furthermore, molecular dynamics simulations were performed to explore the binding mode of the two of the most active compounds of the series, 10 and 14. Harmonization in the two simulation results validate the analysis and therefore applicability of docking parameters based on crystallographic conformation of compound 14 bound to receptor molecule. This work provides useful information about the inhibition mechanism of this class of molecules and will assist in the design of more potent inhibitors of PfDHODH.</p>\",\"PeriodicalId\":15296,\"journal\":{\"name\":\"Journal of Chemical Biology\",\"volume\":\"5 3\",\"pages\":\"91-103\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3375378/pdf/12154_2012_Article_72.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Chemical Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s12154-012-0072-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2012/2/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12154-012-0072-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2012/2/5 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
3D-QSAR studies of triazolopyrimidine derivatives of Plasmodium falciparum dihydroorotate dehydrogenase inhibitors using a combination of molecular dynamics, docking, and genetic algorithm-based methods.
A series of 35 triazolopyrimidine analogues reported as Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors were optimized using quantum mechanics methods, and their binding conformations were studied by docking and 3D quantitative structure-activity relationship studies. Genetic algorithm-based criteria was adopted for selection of training and test sets while maintaining structural diversity of training and test sets, which is also very crucial for model development and validation. Both the comparative molecular field analyses ([Formula: see text], [Formula: see text]) and comparative molecular similarity indices analyses ([Formula: see text], [Formula: see text]) show excellent correlation and high predictive power. Furthermore, molecular dynamics simulations were performed to explore the binding mode of the two of the most active compounds of the series, 10 and 14. Harmonization in the two simulation results validate the analysis and therefore applicability of docking parameters based on crystallographic conformation of compound 14 bound to receptor molecule. This work provides useful information about the inhibition mechanism of this class of molecules and will assist in the design of more potent inhibitors of PfDHODH.