GōMartini 3:从蛋白质的大构象变化到环境偏差修正

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Paulo C. T. Souza, Luís Borges-Araújo, Christopher Brasnett, Rodrigo A. Moreira, Fabian Grünewald, Peter Park, Liguo Wang, Hafez Razmazma, Ana C. Borges-Araújo, Luis Fernando Cofas-Vargas, Luca Monticelli, Raúl Mera-Adasme, Manuel N. Melo, Sangwook Wu, Siewert J. Marrink, Adolfo B. Poma, Sebastian Thallmair
{"title":"GōMartini 3:从蛋白质的大构象变化到环境偏差修正","authors":"Paulo C. T. Souza, Luís Borges-Araújo, Christopher Brasnett, Rodrigo A. Moreira, Fabian Grünewald, Peter Park, Liguo Wang, Hafez Razmazma, Ana C. Borges-Araújo, Luis Fernando Cofas-Vargas, Luca Monticelli, Raúl Mera-Adasme, Manuel N. Melo, Sangwook Wu, Siewert J. Marrink, Adolfo B. Poma, Sebastian Thallmair","doi":"10.1038/s41467-025-58719-0","DOIUrl":null,"url":null,"abstract":"<p>Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the reparametrized version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"12 1","pages":""},"PeriodicalIF":15.7000,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GōMartini 3: From large conformational changes in proteins to environmental bias corrections\",\"authors\":\"Paulo C. T. Souza, Luís Borges-Araújo, Christopher Brasnett, Rodrigo A. Moreira, Fabian Grünewald, Peter Park, Liguo Wang, Hafez Razmazma, Ana C. Borges-Araújo, Luis Fernando Cofas-Vargas, Luca Monticelli, Raúl Mera-Adasme, Manuel N. Melo, Sangwook Wu, Siewert J. Marrink, Adolfo B. Poma, Sebastian Thallmair\",\"doi\":\"10.1038/s41467-025-58719-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the reparametrized version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.</p>\",\"PeriodicalId\":19066,\"journal\":{\"name\":\"Nature Communications\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":15.7000,\"publicationDate\":\"2025-04-30\",\"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/s41467-025-58719-0\",\"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/s41467-025-58719-0","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}
引用次数: 0

摘要

粗粒度建模已成为补充实验测量的重要工具,允许访问超越全原子基础方法的时空尺度。GōMartini模型结合了基于结构和物理的粗粒度方法,平衡了计算效率和蛋白质动力学的准确表示与研究不同生物环境中的蛋白质的能力。本文介绍了一个增强的GōMartini模型,该模型结合了ghi模型的虚拟站点实现和Martini 3。自重新参数化版本的Martini发布以来,社区已经对该实现进行了广泛的测试。这项工作证明了该模型在各种案例研究中的能力,从蛋白质-膜结合到蛋白质-配体相互作用和AFM力谱计算。该模型也是通用的,因为它可以解决最近在马提尼蛋白质模型中报道的不准确性。最后,本文讨论了Martini 3蛋白模型及其与ggi模型的结合的优势、局限性和未来展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

GōMartini 3: From large conformational changes in proteins to environmental bias corrections

Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the reparametrized version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信