Computational modeling to determine strategies to optimize self-limited assembly

计算建模以确定优化自限性装配的策略

• 批准号: 2309635
• 负责人: Michael Hagan
• 金额: $ 42万
• 依托单位: Brandeis University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309635&HistoricalAwards=false
• 关键词: Computational; modeling; determine; strategies; optimize

NON-TECHNICAL SUMMARY Self-assembly is a process by which basic subunits come together to form structures with increased size and complexity. Many self-assembly processes in biology are ‘self-limited’, meaning that assembly automatically stops at a particular size and structure. These self-limited assemblies perform important functions in biological cells, and thus understanding how they work would advance our understanding of life and diseases. Moreover, learning to design self-limited assembly processes in synthetic systems could enable important technological applications. However, the achievable sizes and yields of assembled structures are currently much smaller than those of natural systems. This limitation arises because the field lacks theoretical principles to guide designing the subunits and reaction conditions to ensure robust, efficient assembly. This project aims to develop such theoretical principles, by using computation and theory to understand mechanisms that biology uses make self-limited assembly efficient, and to learn how to apply them to synthetic assemblies. The project will undertake three thrusts, each of which investigates a different mechanism. The first thrust will study how using multiple species of subunits with different interactions can increase achievable assembly sizes and yield. The second thrust will investigate how varying reaction conditions in time can increase assembly rates and yields. The investigators will combine new computational methods with a theoretical framework called optimal control theory to develop efficient algorithms to determine time-sequences of reaction conditions that maximize yields. The third thrust will study self-assembly within phase-separated droplets. Liquid-liquid phase separation refers to the de-mixing of a solution into droplets with different chemical compositions, such as when oil and water separate. During some virus infections, the virus remodels its host cell to form phase-separated droplets within which new viral particles assemble. This project will study how assembly rates and yields depend on properties of the phase-separated droplets, such as their size and the tendency of subunits to locally concentrate inside of the droplets. Results from each thrust will be tested against experiments performed by collaborators, in which DNA origami or protein design is used to create subunits that assemble into symmetric shells, helical tubules, and other structures.The research will provide interdisciplinary science technology engineering and mathematical (STEM) training for undergraduate and graduate students, at the interface between physics and biology. The research program is designed to recruit diverse students, and train them in computational research as well as effective scientific communication to expert and non-expert audiences. The project will also include programs in which the researchers describe their results to the public. These efforts will include a program integrated in the physics curriculum of a local high school, in which students engage in a hands-on activity that explains the physics and geometry of self-assembly in viruses and technology, while conveying the wonder, excitement, and impact on society of scientific research.TECHNICAL SUMMARYThe self-limited assembly of protein subunits into finite-sized structures with well-defined architectures is a hallmark of life. Such structures abound in nature, where they perform essential functions of cells and the pathogens that infect them. Recently, advances in DNA origami and protein design have enabled engineering synthetic subunits that are programmed for self-limited assembly, with atomic-scale precision rivaling that of natural proteins. Yet, achievable sizes and yields of assembled structures fall far short of nature, due to a lack of theoretical principles to guide designing subunits and reaction conditions for robust, efficient assembly. This project aims to overcome this limitation, by using computation to understand mechanisms that biology uses to circumvent constraints on assembly timescales: tunable ‘subunit complexity’, by having multiple subunit species with specific interactions, and nonequilibrium spatiotemporally varying assembly driving forces. The project will undertake three complementary thrusts. Thrust 1 investigates how self-limited assembly depends on subunit complexity, to identify general strategies to increase yields. Thrust 2 combines Markov state models with optimal control theory to develop efficient algorithms for optimizing time-dependent assembly protocols. Thrust 3 will use simulations to understand how self-assembly is affected by a prominent form of spatial control in cells – liquid-liquid phase separation. The research will investigate how liquid-liquid phase separation can accelerate assembly and enhance robustness against parameter variations. Results from each thrust will be tested against experiments performed by collaborators, in which DNA origami or protein design is used to create subunits that assemble into icosahedral capsids, helical tubules, and other structures. Assembling large target structures is challenging because assembly rates are constrained by competing thermodynamic and kinetic effects. The scientific community lacks strategies to engineer assembly reactions that simultaneously satisfy these trade-offs, due to crucial gaps in self-assembly theory: (1) Previous models have focused on minimal subunit complexity (assembly from one subunit species) or maximal complexity (addressable assembly, in which each subunit is unique); (2) Optimizing time-dependent assembly protocols for three-dimensional systems has been computationally intractable for most systems; (3) Despite intensive research on liquid-liquid phase separation, its effect on self-assembly has received relatively little attention. This project aims to develop computational models and tools that overcome these limitations. Thrust 1 will provide the first systematic study across the full range of subunit complexity, to identify optimal levels of complexity and the effects of geometric frustration or redundant interactions that arise at low or high complexity. Thrust 2 will leverage the properties of Markov state models to develop a highly efficient optimization framework that is applicable to diverse self-assembly systems. The investigators will use this framework to determine optimal time-dependent protocols for three-dimensional self-limited assembly. Thrust 3 will provide the first models for self-limited assembly coupled to liquid-liquid phase separation. By establishing design principles for engineering subunits that can be preprogrammed to assemble into arbitrary three-dimensional structures, this research will pave the way to highly scalable manufacturing of nanostructured materials for biomedical and technological applications. The results also make a key step toward a theory of living matter, by elucidating self-assembly mechanisms that underlie essential functions in biological cells and pathogens. The computational algorithms developed for this research will be broadly applicable to self-assembly. The research will provide interdisciplinary STEM training for undergraduate and graduate students, at the interface between soft matter physics and cell biology. The research program will recruit diverse students, and train them in computational research as well as effective scientific communication to expert and non-expert audiences. Public outreach will include a program integrated in the physics curriculum of a local high school, in which students engage in a hands-on activity that explains the physics and geometry of self-assembly in viruses and technology, while conveying the wonder, excitement, and impact on society of scientific research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

项目成果

Hierarchical assembly is more robust than egalitarian assembly in synthetic capsids.

合成衣壳中的分层组装比平等组装更稳健。

• DOI: 10.1073/pnas.2312775121
• 发表时间: 2024
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1
• 作者: Wei,Wei-Shao;Trubiano,Anthony;Sigl,Christian;Paquay,Stefan;Dietz,Hendrik;Hagan,MichaelF;Fraden,Seth
• 通讯作者: Fraden,Seth