大分子自组装网络:计算与实验相结合的设计策略

IF 14.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Journal of the American Chemical Society Pub Date : 2024-10-25 DOI:10.1021/jacs.4c1189210.1021/jacs.4c11892
Jiangbo Wu, Zhaoyi Gu, Justin A. Modica, Sijia Chen, Milan Mrksich* and Gregory A. Voth*, 
{"title":"大分子自组装网络:计算与实验相结合的设计策略","authors":"Jiangbo Wu,&nbsp;Zhaoyi Gu,&nbsp;Justin A. Modica,&nbsp;Sijia Chen,&nbsp;Milan Mrksich* and Gregory A. Voth*,&nbsp;","doi":"10.1021/jacs.4c1189210.1021/jacs.4c11892","DOIUrl":null,"url":null,"abstract":"<p >This work describes the use of computational strategies to design megamolecule building blocks for the self-assembly of lattice networks. The megamolecules are prepared by attaching four Cutinase-SnapTag fusion proteins (CS fusions) to a four-armed linker, followed by functionalizing each fusion with a terpyridine linker. This functionality is designed to participate in a metal-mediated self-assembly process to give networks. This article describes a simulation-guided strategy for the design of megamolecules to optimize the peptide linker in the fusion protein to give conformations that are best suited for self-assembly and therefore streamlines the typically time-consuming and labor-intensive experimental process. We designed 11 candidate megamolecules and identified the most promising linker, (EAAAK)<sub>2</sub>, along with the optimal experimental conditions through a combination of all-atom molecular dynamics, enhanced sampling, and larger-scale coarse-grained molecular dynamics simulations. Our simulation findings were validated and found to be consistent with the experimental results. Significantly, this study offers valuable insight into the self-assembly of megamolecule networks and provides a novel and general strategy for large biomolecular material designs by using systematic bottom-up coarse-grained simulations.</p>","PeriodicalId":49,"journal":{"name":"Journal of the American Chemical Society","volume":"146 44","pages":"30553–30564 30553–30564"},"PeriodicalIF":14.4000,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy\",\"authors\":\"Jiangbo Wu,&nbsp;Zhaoyi Gu,&nbsp;Justin A. Modica,&nbsp;Sijia Chen,&nbsp;Milan Mrksich* and Gregory A. Voth*,&nbsp;\",\"doi\":\"10.1021/jacs.4c1189210.1021/jacs.4c11892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >This work describes the use of computational strategies to design megamolecule building blocks for the self-assembly of lattice networks. The megamolecules are prepared by attaching four Cutinase-SnapTag fusion proteins (CS fusions) to a four-armed linker, followed by functionalizing each fusion with a terpyridine linker. This functionality is designed to participate in a metal-mediated self-assembly process to give networks. This article describes a simulation-guided strategy for the design of megamolecules to optimize the peptide linker in the fusion protein to give conformations that are best suited for self-assembly and therefore streamlines the typically time-consuming and labor-intensive experimental process. We designed 11 candidate megamolecules and identified the most promising linker, (EAAAK)<sub>2</sub>, along with the optimal experimental conditions through a combination of all-atom molecular dynamics, enhanced sampling, and larger-scale coarse-grained molecular dynamics simulations. Our simulation findings were validated and found to be consistent with the experimental results. Significantly, this study offers valuable insight into the self-assembly of megamolecule networks and provides a novel and general strategy for large biomolecular material designs by using systematic bottom-up coarse-grained simulations.</p>\",\"PeriodicalId\":49,\"journal\":{\"name\":\"Journal of the American Chemical Society\",\"volume\":\"146 44\",\"pages\":\"30553–30564 30553–30564\"},\"PeriodicalIF\":14.4000,\"publicationDate\":\"2024-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Chemical Society\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/jacs.4c11892\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Chemical Society","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/jacs.4c11892","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

这项研究介绍了如何利用计算策略设计用于晶格网络自组装的大分子构建模块。制备大分子的方法是将四个 Cutinase-SnapTag 融合蛋白(CS 融合蛋白)连接到一个四臂连接体上,然后用一个特吡啶连接体对每个融合蛋白进行功能化。这种功能旨在参与金属介导的自组装过程,从而形成网络。本文介绍了一种模拟指导下的巨分子设计策略,通过优化融合蛋白中的肽连接体来获得最适合自组装的构象,从而简化了通常耗时耗力的实验过程。我们设计了 11 种候选巨分子,并通过全原子分子动力学、增强采样和更大规模粗粒度分子动力学模拟的组合,确定了最有前途的连接体 (EAAAK)2 以及最佳实验条件。我们的模拟结果经过验证,与实验结果一致。重要的是,这项研究为巨分子网络的自组装提供了有价值的见解,并通过使用系统的自下而上的粗粒度模拟,为大型生物分子材料的设计提供了一种新颖的通用策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy

This work describes the use of computational strategies to design megamolecule building blocks for the self-assembly of lattice networks. The megamolecules are prepared by attaching four Cutinase-SnapTag fusion proteins (CS fusions) to a four-armed linker, followed by functionalizing each fusion with a terpyridine linker. This functionality is designed to participate in a metal-mediated self-assembly process to give networks. This article describes a simulation-guided strategy for the design of megamolecules to optimize the peptide linker in the fusion protein to give conformations that are best suited for self-assembly and therefore streamlines the typically time-consuming and labor-intensive experimental process. We designed 11 candidate megamolecules and identified the most promising linker, (EAAAK)2, along with the optimal experimental conditions through a combination of all-atom molecular dynamics, enhanced sampling, and larger-scale coarse-grained molecular dynamics simulations. Our simulation findings were validated and found to be consistent with the experimental results. Significantly, this study offers valuable insight into the self-assembly of megamolecule networks and provides a novel and general strategy for large biomolecular material designs by using systematic bottom-up coarse-grained simulations.

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
CiteScore
24.40
自引率
6.00%
发文量
2398
审稿时长
1.6 months
期刊介绍: The flagship journal of the American Chemical Society, known as the Journal of the American Chemical Society (JACS), has been a prestigious publication since its establishment in 1879. It holds a preeminent position in the field of chemistry and related interdisciplinary sciences. JACS is committed to disseminating cutting-edge research papers, covering a wide range of topics, and encompasses approximately 19,000 pages of Articles, Communications, and Perspectives annually. With a weekly publication frequency, JACS plays a vital role in advancing the field of chemistry by providing essential research.
期刊最新文献
Analysis of the TiO2 Photoanode Process Using Intensity Modulated Photocurrent Spectroscopy and Distribution of Relaxation Times Red Light Mediated Photoconversion of Silicon Rhodamines to Oxygen Rhodamines for Single-Molecule Microscopy Light-Independent Fe3O4–Methanosarcina acetivorans Biohybrid Enhances Nitrogen Fixation and Methanogenesis Rapid Microwave-Assisted Chemical Recycling of Poly(p-Phenylene Terephthalamide) Verdazyl-Based Radicals for High-Field Dynamic Nuclear Polarization NMR
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1