Probing the formation of a hetero-dimeric membrane transport complex with dual in vitro and in silico mutagenesis
Bibliographic record
Abstract
The reversible association of transmembrane helices is a fundamental mechanism in how living cells convey information and respond to physiological events. The cardiac calcium transport regulator phospholamban (PLN) is an example of a single-span transmembrane protein that populates a variety of reversible and competing oligomeric states. PLN primarily forms monomers and pentamers in the membrane, where the PLN pentamer is a storage form and the PLN monomer forms a hetero-dimeric inhibitory complex with SERCA. The binding affinity and free-energy of formation of the SERCA-PLN complex in a membrane have not been determined. As is the case for most transmembrane protein interactions, measuring these quantities experimentally is extremely challenging. In this study, we estimated binding affinities by employing in silico alchemical free-energy calculations for all PLN transmembrane alanine substitutions in a membrane bilayer. The binding affinities were calculated separately for the SERCA-PLN complex, a PLN monomer, and a PLN pentamer and compared to in vitro functional measurements of SERCA regulation by the PLN alanine substitutions. Initially, the changes in SERCA inhibition by PLN alanine substitutions were compared to the changes in free energy for the SERCA-PLN complex formed from the PLN monomer. However, the functional data for the PLN alanine substitutions were better explained by the formation of the SERCA-PLN complex directly from the PLN pentamer. This finding points to an inhibitory mechanism favoring conformational selection of SERCA and the interaction of a PLN pentamer with SERCA for 'delivery' of a PLN monomer to the inhibitory site. The implications of these findings suggest that the energetics of helix exchange between homo- and hetero-oligomeric signaling complexes is favored over an intermediate involving a free monomeric helix in the membrane bilayer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".