Some Like It Cold: Stability, activity, and oligomerization of psychrophilic enzymes
Bibliographic record
Abstract
Extremophilic organisms inhabit all four corners of the world, and among them, we find psychrophiles. Psychrophiles, which translates to cold-loving, are organisms that excel at survival and reproduction in cold environments and have developed marvellous molecular adaptations to achieve this. A crucial adaptation is the evolution of the so-called cold-active enzymes, which are biocatalysts able to overcome the exponential dampening of the catalytic activity induced by a decrease in the temperature. In other words, cold-active enzymes are highly efficient in the cold; however, they often pay the price in terms of lower thermodynamic stability. The current energy crisis emphasizes the need for improved ways to reduce our energy consumption by, among other means, developing novel technologies requiring less heat input. Therefore, high catalytic rates at low temperatures make cold-active enzymes attractive biocatalysts for industrial applications, such as food preparation and conservation, textile processing, biofuel production, and pharmacological formulation. <br/>This dissertation uses computational, biophysical, and structural approaches to study the structure-function relationship of cold-active enzymes. We were interested in understanding what determines cold-activity on a molecular level and whether the aforementioned stability price can be overcome to develop potentially highly active and stable enzymes. To achieve this, the author has identified, expressed, and characterized several novel enzymes from genomes of psychrophilic bacteria uniquely capable of subzero growth yet also tolerant towards relatively high temperatures. These studies have led to exciting observations showing that low thermodynamic stability is common amongst cold-active enzymes and that electrostatic interactions may play a crucial role in stability improvement. Furthermore, the author also chose to study an industrially relevant lactose-degrading enzyme previously discovered by our collaborators. We found that this enzyme is highly active but has a severely low tolerance against heat and chemical denaturation. Moreover, we were able to show how the stability and cold-activity of this enzyme are connected to its biological assembly, which is a rarely reported aspect of cold-active enzymes. <br/>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".