Paper List
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Formation of Artificial Neural Assemblies by Biologically Plausible Inhibition Mechanisms
This work addresses the core limitation of the Assembly Calculus model—its fixed-size, biologically implausible k-WTA selection process—by introducing...
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How to make the most of your masked language model for protein engineering
This paper addresses the critical bottleneck of efficiently sampling high-quality, diverse protein sequences from Masked Language Models (MLMs) for pr...
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Module control in youth symptom networks across COVID-19
This paper addresses the core challenge of distinguishing whether a prolonged societal stressor (COVID-19) fundamentally reorganizes the architecture ...
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JEDI: Jointly Embedded Inference of Neural Dynamics
This paper addresses the core challenge of inferring context-dependent neural dynamics from noisy, high-dimensional recordings using a single unified ...
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ATP Level and Phosphorylation Free Energy Regulate Trigger-Wave Speed and Critical Nucleus Size in Cellular Biochemical Systems
This work addresses the core challenge of quantitatively predicting how the cellular energy state (ATP level and phosphorylation free energy) governs ...
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Packaging Jupyter notebooks as installable desktop apps using LabConstrictor
This paper addresses the core pain point of ensuring Jupyter notebook reproducibility and accessibility across different computing environments, parti...
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SNPgen: Phenotype-Supervised Genotype Representation and Synthetic Data Generation via Latent Diffusion
This paper addresses the core challenge of generating privacy-preserving synthetic genotype data that maintains both statistical fidelity and downstre...
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Continuous Diffusion Transformers for Designing Synthetic Regulatory Elements
This paper addresses the challenge of efficiently generating novel, cell-type-specific regulatory DNA sequences with high predicted activity while min...
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.