Native entanglement misfolding contributes to age-associated structural changes across the Saccharomyces cerevisiae proteome

This study reveals that the accumulation of native entanglement misfolding in globular proteins is a key driver of age-associated structural changes across the *Saccharomyces cerevisiae* proteome, as these entangled regions are significantly more prone to forming long-lived, near-native misfolded states during aging.

The Gist

The Big Picture: The "Tangled Yarn" Problem of Aging

Imagine your body is a massive, bustling factory. Inside this factory, thousands of machines (proteins) are constantly being built to keep the lights on, the doors open, and the products moving. These machines need to be built in a very specific, precise shape to work correctly.

As the factory gets older, things start to go wrong. The machines don't just break; they get built in slightly "off" shapes. They look almost right, but they don't quite work. This is called protein misfolding, and it's a major reason why cells (and us) age.

This paper discovered a specific, sneaky reason why these machines get built wrong: They get physically tangled.

The Main Character: The "Lasso" Knot

The researchers focused on a specific shape called a Non-Covalent Lasso Entanglement (NCLE).

• The Analogy: Imagine a piece of string (the protein) that loops around to form a circle, and then another part of that same string pokes through the middle of the loop, like a lasso catching a horse.
• The Native State: In a healthy, young cell, this lasso is formed perfectly. It's stable and functional.
• The Problem: As the cell ages, the "construction crew" (the cell's folding machinery) sometimes makes a mistake. They build the loop, but they forget to thread the string through it, or they thread it through the wrong way.

The Discovery: Tangled Proteins Age Faster

The team looked at the yeast cell (a tiny, single-celled organism often used to study aging) and compared "young" yeast to "old" yeast. They found three big things:

1. The Tangled Ones Break First: Proteins that naturally have this "lasso" shape are twice as likely to show signs of structural damage as they age compared to proteins that don't have lassos.

   • Think of it like this: If you have a complex knot in your shoelace, it's much harder to untie or fix than a straight lace. If the factory gets old and sloppy, the complex knots are the first to get messed up.

2. The Damage is Localized: When these lasso proteins do get damaged, the damage happens right where the knot is.

   • Analogy: If you have a tangled headphone cord, the part that gets frayed or broken is usually right in the middle of the knot, not at the ends. The study found that the "lasso" parts of the proteins were 59% more likely to be the ones getting damaged.

3. The "Ghost" Machines: This is the most fascinating part. When these proteins misfold, they don't turn into a useless, crumpled ball of trash. Instead, they become "Near-Native" ghosts.

   • The Metaphor: Imagine a robot that is supposed to have a specific arm movement. A "broken" robot might fall apart completely. But a "near-native" misfolded robot looks 90% identical to the working one. It just has one arm twisted slightly wrong.
   • Why this is bad: Because the robot looks so much like the real thing, the factory's "quality control inspectors" (chaperone proteins) don't notice it's broken. They let it stay on the assembly line. But because the arm is twisted, the robot can't do its job. It just sits there, taking up space and clogging the works.

The Vicious Cycle of Aging

The paper suggests a vicious cycle:

1. As cells age, they get worse at cleaning up broken parts.
2. Proteins with "lasso" shapes are prone to making these "ghost" mistakes (where they look right but are twisted).
3. Because these ghosts look so much like the real thing, the cell's cleanup crew ignores them.
4. These useless, twisted machines pile up over time, clogging the factory and causing the cell to lose function.

The Bottom Line

The researchers used computer simulations to prove that proteins with these natural "lasso" knots are seven times more likely to get stuck in these twisted, broken states than proteins without knots.

In simple terms: Aging isn't just about things breaking randomly. It's partly about our body's complex "knots" getting untied or tied wrong. Once tied wrong, they look so similar to the real thing that our body's cleanup crew misses them, allowing them to accumulate and slowly shut down the cell.

This discovery is exciting because it gives scientists a new target: If we can figure out how to prevent these "lasso" knots from getting tangled in the first place, or help the cell recognize these "ghost" machines, we might be able to slow down the aging process.

Technical Summary

1. Problem Statement

Aging at the subcellular level is characterized by a decline in protein homeostasis (proteostasis), leading to the accumulation of misfolded proteins. While previous models attribute this to general proteostasis network failure or aggregation, a specific mechanism involving native non-covalent lasso entanglements (NCLEs) has been underexplored in the context of aging.

• The Gap: NCLEs are geometric motifs where a polypeptide loop is closed by non-covalent contacts and threaded by another backbone segment. Previous simulations suggest these motifs can act as kinetic traps, leading to long-lived, near-native misfolded states that evade chaperone refolding.
• The Question: Do proteins containing native NCLEs exhibit a higher propensity for age-associated structural changes in living cells, and can this explain a portion of proteome aging?

2. Methodology

The study employs a multi-modal approach integrating proteomics, structural bioinformatics, and molecular dynamics simulations.

• Data Integration:

  • Proteomics: Utilized a published Limited Proteolysis Mass Spectrometry (LiP-MS) dataset comparing young (S. cerevisiae, 0.6 divisions) and aged (4.2 divisions) cells. This data identifies proteins with altered proteolytic cleavage patterns, indicating conformational changes.
  • Structural Annotation: Mapped LiP-MS data to high-confidence AlphaFold2 structures (pLDDT ≥ 70). Proteins were annotated for the presence of native NCLEs using Gaussian Linking Integration methods. Proteins with knots or covalent lassos were excluded.
  • Filtering: The final dataset comprised 2,256 proteins (1,686 with native NCLEs, 570 without), of which 438 showed age-associated structural changes.

• Statistical Analysis:

  • Odds Ratios: Calculated crude and adjusted odds ratios (OR) to determine the association between NCLE presence and age-related structural changes.
  • Confounding Control: Used logistic regression to control for protein length, a known confounder (longer proteins are more prone to misfolding and contain more NCLEs).
  • Residue-Level Analysis: Analyzed whether structural changes were localized specifically to the entangled regions (defined as residues within ±3 positions of loop-closing contacts and crossing residues, plus contacting residues).

• Molecular Simulations:

  • Model Selection: Selected 24 proteins with native NCLEs and age-associated changes, paired with 24 non-entangled proteins without such changes (matched by length).
  • Simulation Protocol: Performed coarse-grained C$\alpha$ Go-model molecular dynamics. Proteins were thermally unfolded (600 K) and quenched to 300 K for 1.5 $\mu$s trajectories.
  • Metrics: Calculated the fraction of native contacts ($Q$) and the fraction of native contacts with entanglement changes ($G$) to identify "near-native misfolded states."
  • Validation: Compared simulation-derived solvent accessible surface area (SASA) changes against experimental LiP-MS proteolytic alterations.

3. Key Contributions

• Proteome-Wide Validation: Provided the first large-scale, proteome-wide evidence linking native topological entanglements to aging in a eukaryotic system (S. cerevisiae).
• Mechanistic Insight: Demonstrated that misfolding in entangled proteins is not random but localized to the entangled motifs, supporting the "failure-to-form" mechanism where the threading segment fails to pierce the loop.
• Accumulation Mechanism: Proposed that these misfolded states are "near-native" (high $Q$, low $G$), allowing them to bypass chaperone surveillance and accumulate as proteostasis declines.

4. Key Results

• Increased Susceptibility to Aging:

  • Proteins with native NCLEs are 121% more likely to exhibit age-associated structural changes compared to non-entangled proteins (Adjusted OR = 2.21, $p < 10^{-7}$).
  • This association holds even after controlling for protein length.

• Localization of Damage:

  • Within entangled proteins, the specific regions forming the NCLE are 59% more likely to undergo age-associated structural changes than non-entangled regions (Adjusted OR = 1.59, $p < 10^{-65}$).

• Simulation Evidence of Misfolding:

  • Simulations revealed that entangled proteins have a 7-fold higher probability of misfolding compared to non-entangled controls (Median misfolding probability: 27.9% vs. 4.1%).
  • The misfolding mechanism identified was the loss of the native entanglement (threading segment displaced outside the loop) while the rest of the structure remains folded.

• Nature of Misfolded States:

  • Analysis of the protein GDI1 (a key example) showed that misfolded states populated ~30% of the simulation time. These states were highly native-like ($Q \approx 0.9$) but lacked the specific entanglement topology.
  • These near-native states were consistent with experimental LiP-MS data (SASA deviations matched proteolytic alterations), suggesting they are stable enough to persist in cells.

• Protein Abundance:

  • Proteins exhibiting age-associated structural changes are 52% more likely to increase in abundance with age (Adjusted OR = 1.52). This suggests that misfolded, near-native states evade degradation mechanisms, leading to accumulation.

5. Significance

• New Mechanism of Aging: The study identifies entanglement misfolding as a distinct, widespread mechanism driving proteome aging, separate from general aggregation or chaperone overload.
• The "Stealth" Misfolding Hypothesis: It explains how misfolded proteins can accumulate without triggering immediate cellular stress responses: because they are structurally similar to the native state (near-native), they escape detection by quality control systems (chaperones and deaggregases).
• Therapeutic Implications: The findings suggest that targeting the formation or resolution of NCLEs could be a novel strategy to mitigate age-related proteostasis collapse.
• Broader Impact: By linking geometric topology (entanglement) directly to functional decline in aging, the paper bridges the gap between protein folding physics and cellular senescence.

In conclusion, the authors demonstrate that the geometric complexity of native protein structures (specifically NCLEs) creates intrinsic vulnerabilities that lead to the accumulation of long-lived, non-functional, near-native misfolded states, driving the structural decay of the proteome during aging.