{"title":"一个全面的Python模块,用于模拟核磁共振中的松弛和动态。","authors":"Albert A Smith,Kai Zumpfe","doi":"10.1038/s41467-025-65091-6","DOIUrl":null,"url":null,"abstract":"Nuclear magnetic resonance is a powerful method for characterizing dynamics of biological systems in a native-like environment. Accurate dynamics characterization, however, often requires simulations of complex NMR experiments. While a number of simulation programs exist for NMR simulation (SIMPSON, Spinach, SpinEvolution), none of these are focused on easy simulation of motional effects on NMR experiments. The SLEEPY Python module makes it straightforward to simulate arbitrary pulse sequences while including both relaxation and exchange processes. SLEEPY furthermore allows simulation of solid-state (static and spinning) and solution NMR experiments, using both truncated and full Hamiltonians (rotating frame/lab frame). We demonstrate its application to a wide variety of experiments, including transverse (T1ρ), and longitudinal relaxation (T1), nuclear Overhauser effect magnetization transfers, recoupling, and paramagnetic effects. We also provide an extensive online tutorial that explains how to use the various capabilities of SLEEPY. This tool can then be used for both better understanding of the impact of dynamics on NMR and in reproduction of experimental results.","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"12 1","pages":"9278"},"PeriodicalIF":15.7000,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SLEEPY: a comprehensive Python module for simulating relaxation and dynamics in nuclear magnetic resonance.\",\"authors\":\"Albert A Smith,Kai Zumpfe\",\"doi\":\"10.1038/s41467-025-65091-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nuclear magnetic resonance is a powerful method for characterizing dynamics of biological systems in a native-like environment. Accurate dynamics characterization, however, often requires simulations of complex NMR experiments. While a number of simulation programs exist for NMR simulation (SIMPSON, Spinach, SpinEvolution), none of these are focused on easy simulation of motional effects on NMR experiments. The SLEEPY Python module makes it straightforward to simulate arbitrary pulse sequences while including both relaxation and exchange processes. SLEEPY furthermore allows simulation of solid-state (static and spinning) and solution NMR experiments, using both truncated and full Hamiltonians (rotating frame/lab frame). We demonstrate its application to a wide variety of experiments, including transverse (T1ρ), and longitudinal relaxation (T1), nuclear Overhauser effect magnetization transfers, recoupling, and paramagnetic effects. We also provide an extensive online tutorial that explains how to use the various capabilities of SLEEPY. This tool can then be used for both better understanding of the impact of dynamics on NMR and in reproduction of experimental results.\",\"PeriodicalId\":19066,\"journal\":{\"name\":\"Nature Communications\",\"volume\":\"12 1\",\"pages\":\"9278\"},\"PeriodicalIF\":15.7000,\"publicationDate\":\"2025-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Communications\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41467-025-65091-6\",\"RegionNum\":1,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-65091-6","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
SLEEPY: a comprehensive Python module for simulating relaxation and dynamics in nuclear magnetic resonance.
Nuclear magnetic resonance is a powerful method for characterizing dynamics of biological systems in a native-like environment. Accurate dynamics characterization, however, often requires simulations of complex NMR experiments. While a number of simulation programs exist for NMR simulation (SIMPSON, Spinach, SpinEvolution), none of these are focused on easy simulation of motional effects on NMR experiments. The SLEEPY Python module makes it straightforward to simulate arbitrary pulse sequences while including both relaxation and exchange processes. SLEEPY furthermore allows simulation of solid-state (static and spinning) and solution NMR experiments, using both truncated and full Hamiltonians (rotating frame/lab frame). We demonstrate its application to a wide variety of experiments, including transverse (T1ρ), and longitudinal relaxation (T1), nuclear Overhauser effect magnetization transfers, recoupling, and paramagnetic effects. We also provide an extensive online tutorial that explains how to use the various capabilities of SLEEPY. This tool can then be used for both better understanding of the impact of dynamics on NMR and in reproduction of experimental results.
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.