Paper List
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The Effective Reproduction Number in the Kermack-McKendrick model with age of infection and reinfection
This paper addresses the challenge of accurately estimating the time-varying effective reproduction number ℛ(t) in epidemics by incorporating two crit...
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Covering Relations in the Poset of Combinatorial Neural Codes
This work addresses the core challenge of navigating the complex poset structure of neural codes to systematically test the conjecture linking convex ...
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Collective adsorption of pheromones at the water-air interface
This paper addresses the core challenge of understanding how amphiphilic pheromones, previously assumed to be transported in the gas phase, can be sta...
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pHapCompass: Probabilistic Assembly and Uncertainty Quantification of Polyploid Haplotype Phase
This paper addresses the core challenge of accurately assembling polyploid haplotypes from sequencing data, where read assignment ambiguity and an exp...
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Setting up for failure: automatic discovery of the neural mechanisms of cognitive errors
This paper addresses the core challenge of automating the discovery of biologically plausible recurrent neural network (RNN) dynamics that can replica...
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Influence of Object Affordance on Action Language Understanding: Evidence from Dynamic Causal Modeling Analysis
This study addresses the core challenge of moving beyond correlational evidence to establish the *causal direction* and *temporal dynamics* of how obj...
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Revealing stimulus-dependent dynamics through statistical complexity
This paper addresses the core challenge of detecting stimulus-specific patterns in neural population dynamics that remain hidden to traditional variab...
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Exactly Solvable Population Model with Square-Root Growth Noise and Cell-Size Regulation
This paper addresses the fundamental gap in understanding how microscopic growth fluctuations, specifically those with size-dependent (square-root) no...
Topological Enhancement of Protein Kinetic Stability
BioISI – Instituto de Biossistemas e Ciências Integrativas and Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, 1749-016, Lisboa, Portugal
30秒速读
IN SHORT: This work addresses the long-standing puzzle of why knotted proteins exist by demonstrating that deep knots provide a functional advantage through enhanced kinetic stability, not equilibrium thermodynamics.
核心创新
- Methodology Introduces a controlled computational framework (LTyP vs. non-LTyP Monte Carlo simulations) to isolate the pure topological effect of knots from sequence, structure, and energetic contributions.
- Biology Reveals a strong, asymmetric dependence on knot depth: deep knots (e.g., YibK) suppress unfolding transitions by >1 order of magnitude, dramatically enhancing kinetic stability, while shallow knots have minimal effect.
- Theory Integrates a reverse evolution model, showing that kinetic stabilization is sequence-dependent, emerging fully only with increased amino acid alphabet complexity, providing an evolutionary rationale for knotted protein conservation.
主要结论
- Deep protein knots (e.g., YibK) enhance kinetic stability (resistance to unfolding) by more than an order of magnitude compared to topology-breaking controls, while shallow knots show minimal effect.
- Kinetic stability increases sharply with knot depth, whereas foldability is only moderately affected, revealing an asymmetric topological constraint favoring native state persistence.
- Kinetic stabilization is sequence-dependent: early, low-complexity (10-letter alphabet) sequences exhibit weaker resistance to unfolding, with stabilization becoming pronounced only with modern (20-letter) alphabet complexity.
摘要: Knotted proteins embed a physical (i.e., open) knot within their native structures. For decades, significant effort has been devoted to elucidating the functional role of knots in proteins, yet no consensus has been reached. Here, using extensive Monte Carlo off-lattice simulations of a simple structure-based model, we isolate the effect of topology by comparing simulations that preserve the linear topology of the chain with simulations that allow chain crossings. This controlled framework enables us to isolate topological effects from sequence, structure and energetic contributions. We show that protein kinetic stability, defined as resistance to unfolding at a fixed temperature, is higher in knotted proteins. Additionally, kinetic stability increases significantly with knot depth, whereas foldability (or folding efficiency) is comparatively less affected. By considering a simple model of protein evolution in which amino-acid alphabet size is used as a proxy for evolutionary time, we find that increasing primary-sequence complexity through the addition of biotic amino acids predominantly enhances kinetic stability. Taken together, these results indicate that kinetic stability is a functional advantage conferred by protein knots and suggest that evolutionary pressure for kinetic stability could contribute to the persistence of knotted proteins.