Paper List
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A Theoretical Framework for the Formation of Large Animal Groups: Topological Coordination, Subgroup Merging, and Velocity Inheritance
This paper addresses the core problem of how large, coordinated animal groups form in nature, challenging the classical view of gradual aggregation by...
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CONFIDE: Hallucination Assessment for Reliable Biomolecular Structure Prediction and Design
This paper addresses the critical limitation of current protein structure prediction models (like AlphaFold3) where high-confidence scores (pLDDT) can...
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Generative design and validation of therapeutic peptides for glioblastoma based on a potential target ATP5A
This paper addresses the critical bottleneck in therapeutic peptide design: how to efficiently optimize lead peptides with geometric constraints while...
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Pharmacophore-based design by learning on voxel grids
This paper addresses the computational bottleneck and limited novelty in conventional pharmacophore-based virtual screening by introducing a voxel cap...
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Human-Centred Evaluation of Text-to-Image Generation Models for Self-expression of Mental Distress: A Dataset Based on GPT-4o
This paper addresses the critical gap in evaluating how AI-generated images can effectively support cross-cultural mental distress communication, part...
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ANNE Apnea Paper
This paper addresses the core challenge of achieving accurate, event-level sleep apnea detection and characterization using a non-intrusive, multimoda...
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DeeDeeExperiment: Building an infrastructure for integrating and managing omics data analysis results in R/Bioconductor
This paper addresses the critical bottleneck of managing and organizing the growing volume of differential expression and functional enrichment analys...
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Cross-Species Antimicrobial Resistance Prediction from Genomic Foundation Models
This paper addresses the core challenge of predicting antimicrobial resistance across phylogenetically distinct bacterial species, where traditional m...
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.