Deciphering the Mechanism of Binding Selectivity of Chlorofluoroacetamide-Based Covalent Inhibitors toward L858R/T790M Resistance Mutation
Bibliographic record
Abstract
Covalent modification of the oncogenic mutant epidermal growth factor receptor (EGFR) by small molecules is an efficient strategy for achieving an enhanced and sustained pharmacological effect in the treatment of non-small-cell lung cancer. NSP-037 ( 18 ), an irreversible inhibitor of the L858R/T790M double-mutant EGFR (EGFR DM ) using α-chlorofluoroacetamide (CFA) as a novel warhead, has seven times the inhibition selectivity for EGFR DM over the wild type (EGFR WT ), as compared to clinically approved osimertinib ( 7 ). Here, we employ multiple computational approaches to elucidate the mechanism underlining this improved selectivity, as well as the effect of CFA on the selectivity enhancement of inhibitor 18 over 7 . We find that EGFR DM undergoes significantly larger conformational changes than EGFR WT upon binding to 18 . The conformational stability of the diamine side chain and the CFA motif of 18 in the orthosteric site of EGFR DM is identified as key for the disparate binding mechanism and inhibitory prowess of 18 with respect to EGFR WT and EGFR DM and 18 ’s higher selectivity than 7 . The binding free energy of the 18 -bound complexes is −6.38 kcal/mol greater than that of the 7 -bound complexes, explaining the difference in selectivity of these inhibitors. Further, free energy decomposition analysis indicates that the electrostatic contribution of key residues plays an important role in the 18 -bound complexes. QM/MM calculations show that the most favored mechanism for the Cys797 alkylation reaction is the direct displacement mechanism through a CFA-based inhibitor, producing a reaction with the lowest energy barrier and most stable product.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".