Denilson F. Oliveira, Alan R. T. Machado, Mariana G. Aguilar, Abraão J. S. Viana
{"title":"通过对奎宁环的 13C NMR 分析区分辛可宁和辛可尼丁衍生物","authors":"Denilson F. Oliveira, Alan R. T. Machado, Mariana G. Aguilar, Abraão J. S. Viana","doi":"10.1007/s00723-024-01687-3","DOIUrl":null,"url":null,"abstract":"<div><p>With a view to developing a procedure for the differentiation of cinchonine derivatives from cinchonidine derivatives by NMR analysis, experimental data on cinchonine and cinchonidine, after their dissolution in different solvents (CDCl<sub>3</sub>, CD<sub>3</sub>OD and DMSO-<i>d</i><sub><i>6</i></sub>), were compared with theoretical data, originating from different methodologies: DP4, DP4+ , <i>J</i>-DP4 and ANN. Taking into account the lower computational consumption, as well as the greater efficiency in differentiation, the method selected was the trained artificial neural networks (ANN), which considered only the <sup>13</sup>C data from the quinuclidine ring. The method successfully differentiated derivatives originating from OH group protection in ester and ether forms; replacement of the OH group by F and NH<sub>2</sub>; insertions of N<sub>3</sub>, 1<i>H</i>-1,2,3-triazol-1-yl and CH<sub>3</sub>O groups, linked to the quinoline ring; conversion of the vinyl group to the 1-benzyl-1<i>H</i>-1,2,3-triazol-4-yl; and of hydrogenation, dehydrogenation, and bromination of the vinyl group. In all cases the application of the ANN method succeeded in differentiation of cinchonine from cinchonidine derivatives.</p></div>","PeriodicalId":469,"journal":{"name":"Applied Magnetic Resonance","volume":"55 11","pages":"1377 - 1388"},"PeriodicalIF":1.1000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differentiation of Cinchonine and Cinchonidine Derivatives Through 13C NMR Analysis of the Quinuclidine Ring\",\"authors\":\"Denilson F. Oliveira, Alan R. T. Machado, Mariana G. Aguilar, Abraão J. S. Viana\",\"doi\":\"10.1007/s00723-024-01687-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>With a view to developing a procedure for the differentiation of cinchonine derivatives from cinchonidine derivatives by NMR analysis, experimental data on cinchonine and cinchonidine, after their dissolution in different solvents (CDCl<sub>3</sub>, CD<sub>3</sub>OD and DMSO-<i>d</i><sub><i>6</i></sub>), were compared with theoretical data, originating from different methodologies: DP4, DP4+ , <i>J</i>-DP4 and ANN. Taking into account the lower computational consumption, as well as the greater efficiency in differentiation, the method selected was the trained artificial neural networks (ANN), which considered only the <sup>13</sup>C data from the quinuclidine ring. The method successfully differentiated derivatives originating from OH group protection in ester and ether forms; replacement of the OH group by F and NH<sub>2</sub>; insertions of N<sub>3</sub>, 1<i>H</i>-1,2,3-triazol-1-yl and CH<sub>3</sub>O groups, linked to the quinoline ring; conversion of the vinyl group to the 1-benzyl-1<i>H</i>-1,2,3-triazol-4-yl; and of hydrogenation, dehydrogenation, and bromination of the vinyl group. In all cases the application of the ANN method succeeded in differentiation of cinchonine from cinchonidine derivatives.</p></div>\",\"PeriodicalId\":469,\"journal\":{\"name\":\"Applied Magnetic Resonance\",\"volume\":\"55 11\",\"pages\":\"1377 - 1388\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Magnetic Resonance\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00723-024-01687-3\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHYSICS, ATOMIC, MOLECULAR & CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Magnetic Resonance","FirstCategoryId":"101","ListUrlMain":"https://link.springer.com/article/10.1007/s00723-024-01687-3","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, ATOMIC, MOLECULAR & CHEMICAL","Score":null,"Total":0}
Differentiation of Cinchonine and Cinchonidine Derivatives Through 13C NMR Analysis of the Quinuclidine Ring
With a view to developing a procedure for the differentiation of cinchonine derivatives from cinchonidine derivatives by NMR analysis, experimental data on cinchonine and cinchonidine, after their dissolution in different solvents (CDCl3, CD3OD and DMSO-d6), were compared with theoretical data, originating from different methodologies: DP4, DP4+ , J-DP4 and ANN. Taking into account the lower computational consumption, as well as the greater efficiency in differentiation, the method selected was the trained artificial neural networks (ANN), which considered only the 13C data from the quinuclidine ring. The method successfully differentiated derivatives originating from OH group protection in ester and ether forms; replacement of the OH group by F and NH2; insertions of N3, 1H-1,2,3-triazol-1-yl and CH3O groups, linked to the quinoline ring; conversion of the vinyl group to the 1-benzyl-1H-1,2,3-triazol-4-yl; and of hydrogenation, dehydrogenation, and bromination of the vinyl group. In all cases the application of the ANN method succeeded in differentiation of cinchonine from cinchonidine derivatives.
期刊介绍:
Applied Magnetic Resonance provides an international forum for the application of magnetic resonance in physics, chemistry, biology, medicine, geochemistry, ecology, engineering, and related fields.
The contents include articles with a strong emphasis on new applications, and on new experimental methods. Additional features include book reviews and Letters to the Editor.