Mutagenesis computer experiments in pentameric ligand-gated ion channels: the role of simulation tools with different resolution
Bibliographic record
Abstract
Pentameric ligand-gated ion channels (pLGICs) are an important class of widely expressed membrane neuroreceptors, which play a crucial role in fast synaptic communications and are involved in several neurological conditions. They are activated by the binding of neurotransmitters, which trigger the transmission of an electrical signal via facilitated ion flux. They can also be activated, inhibited or modulated by a number of drugs. Mutagenesis electrophysiology experiments, with natural or unnatural amino acids, have provided a large body of functional data that, together with emerging structural information from X-ray spectroscopy and cryo-electron microscopy, are helping unravel the complex working mechanisms of these neuroreceptors. Computer simulations are complementing these mutagenesis experiments, with insights at various levels of accuracy and resolution. Here, we review how a selection of computational tools, including first principles methods, classical molecular dynamics and enhanced sampling techniques, are contributing to construct a picture of how pLGICs function and can be pharmacologically targeted to treat the disorders they are responsible for.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".