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Distinct in vivo target occupancy by bivalent- and induced-fit-like binding drugs.

ABSTRACT: BACKGROUND AND PURPOSE:Optimal drug therapy often requires long-lasting target occupancy While this attribute was usually linked to the drug's pharmacokinetic properties, the dissociation rate is now increasingly recognized to contribute as well. Nearly all the earlier pharmacokinetic-pharmacodynamic (PK-PD) simulations encompassed single-step binding drugs and focused on koff . However, 'micro'-PK mechanisms and more complex binding mechanisms like bivalent- and induced-fit binding may contribute as well. Corresponding binding models are presently explored. EXPERIMENTAL APPROACH:We compared the 24 h in vivo occupancy over time profiles of prototype bivalent- and induced-fit-like binding drugs (A and B) after one or repeated daily dosings, both without and with rebinding. Special attention was focused on the effect of each of the microscopic rate constants on the occupancy profiles and on the metrics to represent those profiles. KEY RESULTS:Although both models can be represented by the same mathematical formulation, drugs A and B display quite different occupancy profiles, even though they have the same potency. These differences can be attributed to the different effects of their microscopic rate constants on their composite koff and also on their susceptibility to experience rebinding. This also affects how the occupancy profiles of bivalent- and induced-fit-like binders progress when repeating the dosings and by changing the dosage. CONCLUSIONS AND IMPLICATIONS:Closer attention should be paid to more complex binding models in PK-PD simulations. This may help pharmacologists and medicinal chemists to improve the translation of in vitro kinetic measurements from preclinical screening programmes into clinical efficiency.

SUBMITTER: Vauquelin G

PROVIDER: S-EPMC5715606 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Distinct in vivo target occupancy by bivalent- and induced-fit-like binding drugs.

Vauquelin Georges G

British journal of pharmacology 20171018 23

<h4>Background and purpose</h4>Optimal drug therapy often requires long-lasting target occupancy While this attribute was usually linked to the drug's pharmacokinetic properties, the dissociation rate is now increasingly recognized to contribute as well. Nearly all the earlier pharmacokinetic-pharmacodynamic (PK-PD) simulations encompassed single-step binding drugs and focused on k<sub>off</sub> . However, 'micro'-PK mechanisms and more complex binding mechanisms like bivalent- and induced-fit b ...[more]

PMID: 28838028

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Project description:Tumour cell heterogeneity is a major barrier for efficient design of targeted anti-cancer therapies. A diverse distribution of phenotypically distinct tumour-cell subpopulations prior to drug treatment predisposes to non-uniform responses, leading to the elimination of sensitive cancer cells whilst leaving resistant subpopulations unharmed. Few strategies have been proposed for quantifying the variability associated to individual cancer-cell heterogeneity and minimizing its undesirable impact on clinical outcomes. Here, we report a computational approach that allows the rational design of combinatorial therapies involving epigenetic drugs against chromatin modifiers. We have formulated a stochastic model of a bivalent transcription factor that allows us to characterise three different qualitative behaviours, namely: bistable, high- and low-gene expression. Comparison between analytical results and experimental data determined that the so-called bistable and high-gene expression behaviours can be identified with undifferentiated and differentiated cell types, respectively. Since undifferentiated cells with an aberrant self-renewing potential might exhibit a cancer/metastasis-initiating phenotype, we analysed the efficiency of combining epigenetic drugs against the background of heterogeneity within the bistable sub-ensemble. Whereas single-targeted approaches mostly failed to circumvent the therapeutic problems represented by tumour heterogeneity, combinatorial strategies fared much better. Specifically, the more successful combinations were predicted to involve modulators of the histone H3K4 and H3K27 demethylases KDM5 and KDM6A/UTX. Those strategies involving the H3K4 and H3K27 methyltransferases MLL2 and EZH2, however, were predicted to be less effective. Our theoretical framework provides a coherent basis for the development of an in silico platform capable of identifying the epigenetic drugs combinations best-suited to therapeutically manage non-uniform responses of heterogenous cancer cell populations.

Dataset Information

Distinct in vivo target occupancy by bivalent- and induced-fit-like binding drugs.

Publications

Distinct in vivo target occupancy by bivalent- and induced-fit-like binding drugs.

Similar Datasets

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