Abstract A142: Molecular modeling approach to the rational design of promiscuous quinazoline-based EGFR inhibitors
Bibliographic record
Abstract
Abstract Solid tumors at the advanced stages are often characterized by the overexpression of tyrosine kinase receptors that stimulate growth through the MAP kinase pathway and activate antiapoptotic signaling through the PI3K kinase pathway. One such receptor is the epidermal growth factor receptor (EGFR) that is overexpressed in many tumors including brain, lung, breast, ovarian and prostate carcinomas. EGFR can synergize with other tyrosine kinases such as Src to promote invasion and metastasis. However, despite the implication of EGFR in multiple processes, inhibitors of its tyrosine kinase activity such as ZD1839 or erlotinib showed moderate antiproliferative activity against certain tumor types in the clinic. It has been reported that EGFR expressing cells that harbor dysfunctional PTEN, are moderately sensitive to EGFR inhibitors. Given the complexity of cell response the latter class of inhibitors, we thought it of interest to investigate agents that are not only directed at EGFR but also to divergent targets such as Src or DNA, with the purpose of producing single compounds with greater potency than their single inhibitor counterpart. These molecules termed “combi-molecules” were designed to remain small enough for their quinazoline moiety to be able to bind to the ATP site of EGFR and to block a divergent target such as Src or DNA. Using molecular modeling, a structure-based drug design program was used to identify a linker that could be placed between the quinazoline moiety required for binding in the ATP site and the appendage directed at the divergent target. A solvent exposed ASP residue near the opening of the EGFR ATP binding pocket was used to optimize interaction with ionizable linkers. This interaction was found to be tolerant of bulky substituents and was exploited to append other pharmacophores to the combi-molecules. The results showed that in the category of mixed EGFR-DNA targeting molecules, the EGFR inhibitory potency of EGFR was in the low micromolar to nM range and the compounds also retained significant DNA damaging potential. In the category of EGFR-Src targeting molecules, we identified SB163 that contained a quinazoline moiety, the ionizable spacer and an analogue of PP2. SB163 showed significant antiproliferative and antimetastatic property in a Boyden Chamber assay and its activity was superior to that of a combination of known Src inhibitor PP2 + ZD1839, a clinical inhibitor of EGFR. Furthermore, sub-cellular distribution studies, using a fluorescent probe containing the optimized ionizable spacer showed that their biodistribution is unique with preferential localization in the perinuclear region. The results in toto suggests that in the design of promiscuous molecules, an ionizable basic arm linked to the aminoquinazoline moiety preserves EGFR inhibitory potency and allow freedom to append other moiety directed at the cross- target. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A142.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".