Making NSCLC Crystal Clear: How Kinase Structures Revolutionized Lung Cancer Treatment

Vilacha, Juliana F; Mitchel, Sarah C.; Akele, Muluembet; Evans, Stephen; Groves, Matthew R.

doi:10.3390/cryst10090725

Cited by 6 publications

(12 citation statements)

References 333 publications

(481 reference statements)

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“…The C797S mutation occurs in cis - (on the same allele) or trans -forms (on different alleles), according to in vitro studies (on separate alleles), and no EGFR TKIs alone or in combination is able to suppress activity when the mutation is in the cis -form. − Thus, C797S is a prone candidate for a mutation-mediated resistance. − …”

Section: Mechanisms Of Osimertinib Resistancementioning

confidence: 99%

“…Similarly, phenylpiperazine was inserted at the C-6 isoindolinone moiety of EAI045 to yield 56, which demonstrated a significant potency against EGFR L858R/ T790M (IC 50 = 0.26 nM) (Figure 44). In a panel of Ba/F3 cell lines, To et al evaluated the ability of JBJ-04-125-02 (56) to inhibit cell proliferation. Remarkably, JBJ-04-125-02 (56) was most potent when compared to to EAI045 and JBJ-02-112-05 (57) in combination with Cetuximab.…”

Section: Allosteric Inhibitorsmentioning

confidence: 99%

“…In a panel of Ba/F3 cell lines, To et al evaluated the ability of JBJ-04-125-02 (56) to inhibit cell proliferation. Remarkably, JBJ-04-125-02 (56) was most potent when compared to to EAI045 and JBJ-02-112-05 (57) in combination with Cetuximab.…”

Section: Allosteric Inhibitorsmentioning

confidence: 99%

“…The JBJ-04-125-02 (56)−EGFR T790M crystal structure elucidates that JBJ-04-125-02 (56) binds to the allosteric pocket of the EGFR, which is formed by the outer displacement of the C-helix in the inactive kinase conformation. The binding interactions of the phenyl ring, the thiazoleamide, and the isoindolinone of JBJ-04-125-02 (56) are similar to those observed previously for EAI001, and one more hydrogen bond was observed in the DFG motif between the hydroxyl group of phenyl ring and the carbonyl functional group of the residue Phe856. The 4-piperazinophenyl group extends toward the solvent-exposed area (the αC-helix), and the phenyl ring forms a π−π stacking interaction with the Phe723 residue of the P-loop.…”

Section: Allosteric Inhibitorsmentioning

confidence: 99%

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Emerging Approaches to Overcome Acquired Drug Resistance Obstacles to Osimertinib in Non-Small-Cell Lung Cancer

et al. 2021

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The pyrimidine core-containing compound Osimertinib is the only epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) from the third generation that has been approved by the U.S. Food and Drug Administration to target threonine 790 methionine (T790M) resistance while sparing the wild-type epidermal growth factor receptor (WT EGFR). It is nearly 200-fold more selective toward the mutant EGFR as compared to the WT EGFR. A tertiary cystein 797 to serine 797 (C797S) mutation in the EGFR kinase domain has hampered Osimertinib treatment in patients with advanced EGFR-mutated non-small-cell lung cancer (NSCLC). This C797S mutation is presumed to induce a tertiary-acquired resistance to all current reversible and irreversible EGFR TKIs. This review summarizes the molecular mechanisms of resistance to Osimertinib as well as different strategies for overcoming the EGFR-dependent and EGFR-independent mechanisms of resistance, new challenges, and a future direction.

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Section: Mechanisms Of Osimertinib Resistancementioning

confidence: 99%

Section: Allosteric Inhibitorsmentioning

confidence: 99%

Section: Allosteric Inhibitorsmentioning

confidence: 99%

Section: Allosteric Inhibitorsmentioning

confidence: 99%

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Emerging Approaches to Overcome Acquired Drug Resistance Obstacles to Osimertinib in Non-Small-Cell Lung Cancer

et al. 2021

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“…4 a), but only seven of them locate in the kinase subpockets. A secondary amine (f-51 and f-54) near the common moiety, an ether group (f-37) for hydrophobic interactions [ 17 ], two halogens on the aromatic ring (f-67 and f-69), and an amide group (f-82 and f-87) near the alkenyl group. After literature survey, we inferred that most of these moieties are designed to help anchor the common moieties at ATP-binding site, and do not directly participate in the substrate binding.…”

Section: Resultsmentioning

confidence: 99%

Exploring kinase family inhibitors and their moiety preferences using deep SHapley additive exPlanations

et al. 2022

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Background While it has been known that human protein kinases mediate most signal transductions in cells and their dysfunction can result in inflammatory diseases and cancers, it remains a challenge to find effective kinase inhibitor as drugs for these diseases. One major challenge is the compensatory upregulation of related kinases following some critical kinase inhibition. To circumvent the compensatory effect, it is desirable to have inhibitors that inhibit all the kinases belonging to the same family, instead of targeting only a few kinases. However, finding inhibitors that target a whole kinase family is laborious and time consuming in wet lab. Results In this paper, we present a computational approach taking advantage of interpretable deep learning models to address this challenge. Specifically, we firstly collected 9,037 inhibitor bioassay results (with 3991 active and 5046 inactive pairs) for eight kinase families (including EGFR, Jak, GSK, CLK, PIM, PKD, Akt and PKG) from the ChEMBL25 Database and the Metz Kinase Profiling Data. We generated 238 binary moiety features for each inhibitor, and used the features as input to train eight deep neural networks (DNN) models to predict whether an inhibitor is active for each kinase family. We then employed the SHapley Additive exPlanations (SHAP) to analyze the importance of each moiety feature in each classification model, identifying moieties that are in the common kinase hinge sites across the eight kinase families, as well as moieties that are specific to some kinase families. We finally validated these identified moieties using experimental crystal structures to reveal their functional importance in kinase inhibition. Conclusion With the SHAP methodology, we identified two common moieties for eight kinase families, 9 EGFR-specific moieties, and 6 Akt-specific moieties, that bear functional importance in kinase inhibition. Our result suggests that SHAP has the potential to help finding effective pan-kinase family inhibitors.

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Integrated PBPK-EO modeling of osimertinib to predict plasma concentrations and intracranial EGFR engagement in patients with brain metastases

Liang,

Zhang,

Xue

et al. 2024

Sci Rep

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The purpose of this study was to develop and validate a physiologically based pharmacokinetic (PBPK) model combined with an EGFR occupancy (EO) model for osimertinib (OSI) to predict plasma trough concentration (Ctrough) and the intracranial time-course of EGFR (T790M and L858R mutants) engagement in patient populations. The PBPK model was also used to investigate the key factors affecting OSI pharmacokinetics (PK) and intracranial EGFR engagement, analyze resistance to the target mutation C797S, and determine optimal dosing regimens when used alone and in drug-drug interactions (DDIs). A population PBPK-EO model of OSI was developed using physicochemical, biochemical, binding kinetic, and physiological properties, and then validated using nine clinical PK studies, observed EO study, and two clinical DDI studies. The PBPK-EO model demonstrated good consistency with observed data, with most prediction-to-observation ratios falling within the range of 0.7 to 1.3 for plasma AUC, Cmax, Ctrough and intracranial free concentration. The simulated time-course of C797S occupancy by the PBPK model was much lower than T790M and L858R occupancy, providing an explanation for OSI on-target resistance to the C797S mutation. The PBPK model identified ABCB1 CLint,u, albumin level, and EGFR expression as key factors affecting plasma Ctrough and intracranial EO for OSI. Additionally, PBPK-EO simulations indicated that the optimal dosing regimen for OSI in patients with brain metastases is either 80 mg once daily (OD) or 160 mg OD, or 40 mg or 80 mg twice daily (BID). When used concomitantly with CYP enzyme perpetrators, the PBPK-EO model suggested appropriate dosing regimens of 80 mg OD with fluvoxamine (FLUV) itraconazole (ITR) or fluvoxamine (FLUC) for co-administration and an increase to 160 mg OD with rifampicin (RIF) or efavirenz (EFA). In conclusion, the PBPK-EO model has been shown to be capable of simulating the pharmacokinetic concentration–time profiles and the time-course of EGFR engagement for OSI, as well as determining the optimum dosing in various clinical situations.

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Making NSCLC Crystal Clear: How Kinase Structures Revolutionized Lung Cancer Treatment

Cited by 6 publications

References 333 publications

Emerging Approaches to Overcome Acquired Drug Resistance Obstacles to Osimertinib in Non-Small-Cell Lung Cancer

Emerging Approaches to Overcome Acquired Drug Resistance Obstacles to Osimertinib in Non-Small-Cell Lung Cancer

Exploring kinase family inhibitors and their moiety preferences using deep SHapley additive exPlanations

Integrated PBPK-EO modeling of osimertinib to predict plasma concentrations and intracranial EGFR engagement in patients with brain metastases

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