Probing the Effect of Protein and Inhibitor Conformational Flexibility on the Reaction of Rocelitinib-Like Covalent Inhibitors of Epidermal Growth Factor Receptor. A Quantum Mechanics/Molecular Mechanics Study
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Epidermal growth factor receptor (EGFR) is a tyrosine kinase and a validated target for non-small cell lung cancer (NSCLC). Drug discovery efforts on this target initially focused on traditional competitive, reversible ATP-binding site inhibitors; however, irreversible covalent binding EGFR inhibitors have become increasingly more popular. Covalent EGFR inhibitors have been developed using a range of different scaffolds, and unsurprisingly, the incorporation of an electrophilic acrylamide group can result in sizable orientation differences relative to the Cys797 nucleophile and the Asp800 general base. In this work, we report a QM/MM study aiming to better understand the aspects of covalent adduct formation, including the role of protein flexibility on chemical reactivity, the impact of electrophile location within the ATP binding site, and the impact of the acrylamide conformation ( s - cis vs s - trans ). We focus here on the diaminopyrimidine scaffold, as exemplified by Rocelitinib, where the electrophile is attached to its back pocket binding group. Our goal is to elucidate how electrophilic groups can be incorporated onto different inhibitor scaffolds targeting reactive active site residues. We find that irrespective of the EGFR MD conformation chosen, acrylamide, in both the s - cis or s - trans, can undergo reaction with rate-determining barriers of ∼20 kcal/mol. Interestingly, the nature of the rate-determining step for Rocelitinib-like inhibitors was found to be either direct nucleophilic attack or keto–enol tautomerization, depending on the precise protein and inhibitor conformation.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".