ArticleThe Journal of chemical physics2015
Percolation-like phase transitions in network models of protein dynamics.
Article in The Journal of chemical physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 9 citations in OpenAlex.
- The Epichaperome Matrix Theory: A systems-level model of active molecular organization.Cell stress & chaperones · 2026Article
- Conformational Stability of the N-Terminal Region of MDM2.Molecules (Basel, Switzerland) · 2023Article
- Self-organization, entropy and allostery.Biochemical Society transactions · 2018Review
- Rare Dissipative Transitions Punctuate the Initiation of Chemical Denaturation in Proteins.Biophysical journal · 2018Article
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2 authors at 1 institution in 1 country.
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Abstract
In broad terms, percolation theory describes the conditions under which clusters of nodes are fully connected in a random network. A percolation phase transition occurs when, as edges are added to a network, its largest connected cluster abruptly jumps from insignificance to complete dominance. In this article, we apply percolation theory to meticulously constructed networks of protein folding dynamics called Markov state models. As rare fluctuations are systematically repressed (or reintroduced), we observe percolation-like phase transitions in protein folding networks: whole sets of conformational states switch from nearly complete isolation to complete connectivity in a rapid fashion. We analyze the general and critical properties of these phase transitions in seven protein systems and discuss how closely dynamics on protein folding landscapes relate to percolation on random lattices.
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