ArticlePRX life2025
Sticky enzymes: increased metabolic efficiency via substrate-dependent enzyme clustering.
Article in PRX life, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Accelerated Ostwald Ripening by Chemical Activity.Journal of the American Chemical Society · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Coclustering of subsequent enzymes in a pathway can accelerate the processing of metabolic intermediates, with benefits including increased pathway fluxes, reduced toxicity, and sensitive branch-point regulation. While the optimal organization of such clusters has been explored theoretically, little is known about how to achieve such organization inside cells. Here we propose that phase-separating enzymes can self-organize into nearly-optimally sized and spaced clusters, provided that their "stickiness" is regulated by local substrate availability. In a nutshell, enzyme clusters only form when and where they are needed to process substrate. We study a mathematical model that implements this scheme for simple metabolic pathways, including all thermodynamic constraints. We find that pathway fluxes can be increased by 50 to 1000-fold and toxic metabolites can be decreased by 10 to 100-fold, at realistic enzyme densities. Finally, we discuss how enzyme "stickiness" could be allosterically regulated. This study presents a self-organization strategy that goes beyond current paradigms for natural and engineered enzyme clusters, and thus represents a motivating challenge to the fields of synthetic biology and metabolic engineering.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.