Sampling the Conformational Energy Landscape of a Hyperthermophilic Protein by Engineering Key Substitutions
Bibliographic record
Abstract
Proteins exist as a dynamic ensemble of interconverting substates, which defines their conformational energy landscapes. Recent work has indicated that mutations that shift the balance between conformational substates (CSs) are one of the main mechanisms by which proteins evolve new functions. In the present study, we probe this assertion by examining phenotypic protein adaptation to extreme conditions, using the allosteric tetrameric lactate dehydrogenase (LDH) from the hyperthermophilic bacterium Thermus thermophilus (Tt) as a model enzyme. In the presence of fructose 1, 6 bis-phosphate (FBP), allosteric LDHs catalyze the conversion of pyruvate to lactate with concomitant oxidation of nicotinamide adenine dinucleotide, reduced form (NADH). The catalysis involves a structural transition between a low-affinity inactive "T-state" and a high-affinity active "R-state" with bound FBP. During this structural transition, two important residues undergo changes in their side chain conformations. These are R171 and H188, which are involved in substrate and FBP binding, respectively. We designed two mutants of Tt-LDH with one ("1-Mut") and five ("5-Mut") mutations distant from the active site and characterized their catalytic, dynamical, and structural properties. In 1-Mut Tt-LDH, without FBP, the K(m)(Pyr) is reduced compared with that of the wild type, which is consistent with a complete shifting of the CS equilibrium of H188 to that observed in the R-state. By contrast, the CS populations of R171, k(cat) and protein stability are little changed. In 5-Mut Tt-LDH, without FBP, K(m)(Pyr) approaches the values it has with FBP and becomes almost temperature independent, k(cat) increases substantially, and the CS populations of R171 shift toward those of the R-state. These changes are accompanied by a decrease in protein stability at higher temperature, which is consistent with an increased flexibility at lower temperature. Together, these results show that the thermal properties of an enzyme can be strongly modified by only a few or even a single mutation, which serve to alter the equilibrium and, hence, the relative populations of functionally important native-state CSs, without changing the nature of the CSs themselves. They also provide insights into the types of mutational pathways by which protein adaptation to temperature is achieved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".