Delay-facilitated self-assembly in compartmentalized systems

Self-assembly processes in biological and synthetic biomolecular systems are often governed by the spatial separation of biochemical processes. While previous work has focused on optimizing self-assembly through fine-tuned reaction parameters or using phase-separated liquid compartments with fast particle exchange, the role of slow intercompartmental exchange remains poorly understood. Here, we demonstrate that slow particle exchange between reaction domains can enhance self-assembly efficiency through a cooperative mechanism: delay-facilitated assembly. Using a minimal model of irreversible self-assembly in two compartments with distinct reaction and exchange dynamics, we identify scenarios where slow particle exchange maximizes yield and minimizes assembly time for given suboptimal reaction dynamics, even under conditions where isolated compartments would fail to facilitate any self-assembly. The mechanism relies on a separation of timescales between intracompartmental reactions and intercompartmental exchange and is robust across a wide range of geometries, including spatially extended domains with diffusive transport. We demonstrate that this effect enables geometric control of self-assembly processes through compartment volumes and exchange rates, eliminating the need for fine-tuning local reaction rates. These results offer a conceptual framework for leveraging spatial separation in synthetic self-assembly design and suggest that biological systems may use slow particle exchange to improve assembly efficiency.

Authors

Institutions

Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-11-25
DOI
https://doi.org/10.1073/pnas.2515123122
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Delay-facilitated self-assembly in compartmentalized systems

Richard Swiderski, Severin Angerpointner, Erwin Frey
Proceedings of the National Academy of Sciences
Modular Robots and Swarm Intelligence
article

Delay-facilitated self-assembly in compartmentalized systems

Richard Swiderski, Severin Angerpointner, Erwin Frey
article en

Abstract

Self-assembly processes in biological and synthetic biomolecular systems are often governed by the spatial separation of biochemical processes. While previous work has focused on optimizing self-assembly through fine-tuned reaction parameters or using phase-separated liquid compartments with fast particle exchange, the role of slow intercompartmental exchange remains poorly understood. Here, we demonstrate that slow particle exchange between reaction domains can enhance self-assembly efficiency through a cooperative mechanism: delay-facilitated assembly. Using a minimal model of irreversible self-assembly in two compartments with distinct reaction and exchange dynamics, we identify scenarios where slow particle exchange maximizes yield and minimizes assembly time for given suboptimal reaction dynamics, even under conditions where isolated compartments would fail to facilitate any self-assembly. The mechanism relies on a separation of timescales between intracompartmental reactions and intercompartmental exchange and is robust across a wide range of geometries, including spatially extended domains with diffusive transport. We demonstrate that this effect enables geometric control of self-assembly processes through compartment volumes and exchange rates, eliminating the need for fine-tuning local reaction rates. These results offer a conceptual framework for leveraging spatial separation in synthetic self-assembly design and suggest that biological systems may use slow particle exchange to improve assembly efficiency.

Proceedings of the National Academy of SciencesVol. 122(48)
Center for NanoScience (DE), Center for Theoretical Physics (PL), Max Planck School Matter to Life, Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 62%
Modular Robots and Swarm Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.