Ion Transport and Inhibitor Binding by human NHE1: Insights from Molecular Dynamics Simulations and Free Energy Calculations
Bibliographic record
Abstract
The human Na+/H+ exchanger one (hNHE1) plays a crucial role in maintaining intracellular pH by regulating the electroneutral exchange of a single intracellular H+ for one extracellular Na+ across the plasma membrane. Understanding the molecular mechanisms governing ion transport and the binding of inhibitors is of importance in the development of anticancer therapeutics targeting hNHE1. In this context, we performed molecular dynamics (MD) simulations based on the recent cryo-electron microscopy (cryo-EM) structures of outward and inward-facing conformations of hNHE1. These simulations allowed us to explore the dynamics of the protein, examine the ion- translocation pore and confirm that Asp267 is the ion-binding residue. Our free energy calculations suggest that Na+ and K+ bind similarly at the ion-binding site. Consequently, Na+ over K+ selectivity cannot be solely explained by differences in ion binding. Our MD simulations involving hNHE1 inhibitors (cariporide and amiloride analogues), showed maintained stable interactions with Asp267 and Glu346. Our study highlights the importance of the salt bridge between the positively charged acylguanidine moiety and Asp267, which appears to play a role in the competitive inhibitory mechanism for this class of inhibitors. Our computational study provides a detailed mechanistic interpretation of experimental data and serves the basis of future structure-based inhibitor design.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".