Deciphering Genotype-Phenotype Correlations and the Mechanism of the Action of Neutrophil Elastase Inhibitors during <i>ELANE</i> Associated Neutropenia Utilizing Molecular Modeling Software
Bibliographic record
Abstract
Background: Mutations in ELANE cause cyclic and severe congenital neutropenia. ELANE encodes neutrophil elastase (NE), a serine protease expressed in neutrophils. Mutations in ELANE impair neutrophil production and lead to serious infections and the risk of myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The clinical phenotype, response to G-CSF and severity of disease are heterogeneous. A genotype-phenotype analysis demonstrated that some variants carry a particularly high risk of these events (PMID: 25427142). It is not known whether these high-risk mutations cause a more severe phenotype due to conformational changes to the tertiary structure of NE, or via yet to be identified secondary mechanisms and modulators. We and others have investigated NE specific inhibitors as an alternative therapy to G-CSF. (PMID: 26193632, PMID: 36052149, PMID: 28754797) Only a few showed encouraging results. Aims: To perform modeling studies of high- and low risk NE mutations to evaluate structural integrity and stability, and compare with the w-type NE using molecular modeling software. To perform docking analysis of NE inhibitors with w-type and mutant NE, characterize and compare the stability of these complexes and binding sites of different inhibitors to NE using molecular modeling software. Methods: High (G214R, C151Y, A57T, G203R) and low (P139L, R220Q, S126L, S126W, A61V) risk ELANE single point mutations were selected based on the clinical data of patients with ELANE neutropenia based on median GCSF treatment dose and risk of MDS/AML transformation, data available through Severe Chronic Neutropenia International Registry (SCNIR). The Molecular Operating Environment (MOE) molecular modeling software platform was used for NE modeling and characterization and inhibitor docking simulations. (Chemical Computing Group Inc, Montreal, Canada) Results: Protein stability values were calculated for each mutation. There was a notable difference in protein stability scores within the high and low risk mutations. For the high-risk mutations, the average stability score was 3.08 and for low-risk mutations 0.37. W-type NE protein stability score is 0.00. The higher the value, the more unstable the protein. We have also compared the predicted protein structures for two distinct mutations: P139L (low-risk) and G214R (high-risk) with w-type NE. The P139L substitution resulted in minimal conformational changes compared to w-type protein; however, the G214R mutation caused significant changes to the protein structure at amino acids Val31-Arg35 and Asn76-Ala79. Molecular docking analysis of 4 small molecule, cell permeable NE inhibitors (MK0339, sivelestat, GW311616, BAY-678) and inactive control, BAY-677, revealed an alternative binding site for MK0339 inhibitor compared to all others. MOE software analysis showed that sivelestat, GW311616 and BAY-678 have similar binding sites with the NE molecule. MK0339 binds at the completely opposite site of the molecule, suggesting a different mechanism of inhibition. The calculated stability score of MK0339 inhibitor with the protein complex was -7.76, -7.20 and -8.21 for G214R, P139L and w-type NE respectively. Interestingly, sivelestat, GW311616 and BAY-678 had higher values that were very similar to BAY-677, the inactive control (stability values were -6.76, -6.57, and -6.75 for G214R, P139L and w-type NE respectively.) Higher values indicate a less stable inhibitor-protein complex. Conclusions: Molecular modeling software analysis of the effect of high- and low-risk mutations on NE protein structure may be key for understanding genotype-phenotype correlations for ELANE associated neutropenia. The current results of molecular docking and inhibitor-protein complex analysis via molecular modeling software correlates with our previous studies and suggests that MK0339 forms a much more stable complex with w-type and mutant NE protein compared to the other inhibitors tested, a valuable insight for developing a therapeutic agent for ELANE associated neutropenia.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".