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Drug Distribution. Part 1. Models to Predict Membrane Partitioning

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Abstract

Purpose

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution.

Methods

Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs.

Results

The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs).

Conclusions

Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

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Abbreviations

acc:

Number of acceptors

don:

Number of donors

fum :

Fraction unbound in microsomal incubation

fup :

Unbound fraction in plasma

KL :

Association constant for drug binding to the lipid

Kp :

Tissue partition constant

L:

Amount of lipid in the tissue

NO2:

Number of NO2 groups

PBPK:

Physiologically based pharmacokinetic models

pKa,a and pKa,b:

pKa values for acids and bases are respectively

PLS:

Partial least squares

SO:

Number of S=O groups

Vss :

Steady-state volume of distribution of a drug

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ACKNOWLEDGMENTS AND DISCLOSURES

This work was partially funded by NIH/NIGMS grants 1R01GM104178 and 1R01GM114369 to KK and SN.

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N Broad Street, Philadelphia, Pennsylvania, 19140, USA

    Swati Nagar & Ken Korzekwa

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  1. Swati Nagar
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  2. Ken Korzekwa
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Correspondence to Ken Korzekwa.

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Nagar, S., Korzekwa, K. Drug Distribution. Part 1. Models to Predict Membrane Partitioning. Pharm Res 34, 535–543 (2017). https://doi.org/10.1007/s11095-016-2085-z

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  • DOI: https://doi.org/10.1007/s11095-016-2085-z

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