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Structural and conformational determinants of macrocycle cell permeability

An Erratum to this article was published on 18 July 2017

This article has been updated


Macrocycles are of increasing interest as chemical probes and drugs for intractable targets like protein–protein interactions, but the determinants of their cell permeability and oral absorption are poorly understood. To enable rational design of cell-permeable macrocycles, we generated an extensive data set under consistent experimental conditions for more than 200 non-peptidic, de novo–designed macrocycles from the Broad Institute's diversity-oriented screening collection. This revealed how specific functional groups, substituents and molecular properties impact cell permeability. Analysis of energy-minimized structures for stereo- and regioisomeric sets provided fundamental insight into how dynamic, intramolecular interactions in the 3D conformations of macrocycles may be linked to physicochemical properties and permeability. Combined use of quantitative structure–permeability modeling and the procedure for conformational analysis now, for the first time, provides chemists with a rational approach to design cell-permeable non-peptidic macrocycles with potential for oral absorption.

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Figure 1: Overview of properties of the representative macrocycle selection.
Figure 2: Molecular properties influencing cell permeability of macrocycles.
Figure 3: Influence of lipophilicity and polar features on cell permeability.
Figure 4: Influence of substructural features on cell permeability.
Figure 5: Explanation of stereospecific differences in Caco-2 cell permeability and efflux for stereo- and regioisomeric macrocycles.
Figure 6: Permeability predictions for de novo–designed macrocycles.

Change history

  • 15 May 2017

    In the version of this article initially published, two chemical compounds in Figure 5c were incorrectly drawn as protonated secondary amines instead of tertiary amines. The error has been corrected in the HTML and PDF versions of the article.


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This work was funded by a postdoctoral fellowship at AstraZeneca R&D Gothenburg (B.O.), the Carl Trygger Foundation (P. Matsson), the Swedish Research Council (grant no. 2822; P.A.) and the NIGMS-sponsored Center of Excellence in Chemical Methodology and Library Development (Broad Institute CMLD; P50 GM069721). ChemAxon and Simulations Plus are graciously acknowledged for providing access to the Instant JChem and ADMET Predictor software, respectively. We thank J. Wernevik, O. Hedge and R. Svensson for determining logD and pKa data, respectively, and J. Holmgren, L. Fredlund and C. Vedin for assistance with Caco-2 cell measurements. We also thank C. Mulrooney and J. Ulander for helpful discussions pertaining to computational experiments.

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Authors and Affiliations



B.O. and P. Matsson made major contributions to this work. J.K., C.H., M.A.F. and P.A. initiated the project. J.K., J.R.D., C.H., M.W.D.P., P.A., P. Matsson and B.O. designed experiments. J.K., J.R.D., C.H., M.W.D.P. and P.A. supervised the work. J.R.D., M.A.F., M.D.L. and G.M. were part of a team at the Broad Institute which designed and synthesized the macrocycles. B.O. performed biochemical experiments and cell assays. S.E.J. measured solubility. B.O. and R.J.L. performed NMR studies. B.C.D. assembled the beyond rule of 5 data set. C.T., P. McCarren, P. Matsson and B.O. performed conformational analysis. P. Matsson built the chemical networks for compound selection and PLS and RF multivariate regression models. U.N. built SVM and RF regression models. C.T. predicted cell permeability. P. Matsson, B.O. and B.C.D. analyzed the data. J.K., B.O., P. Matsson and J.R.D. prepared the manuscript, with feedback and contributions from the other authors.

Corresponding authors

Correspondence to Jeremy R Duvall or Jan Kihlberg.

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Competing interests

B.O., C.T., C.H., M.W.D.P. and R.J.L. are employees at AstraZeneca. M.D.L., G.M. and J.R.D. are employees at Ensemble Therapeutics.

Supplementary information

Supplementary Text and Figures

Supplementary Results, Supplementary Tables 1–53 and Supplementary Figures 1–38. (PDF 7626 kb)

Supplementary Dataset 1

All experimental data and structures. (TXT 513 kb)

Supplementary Dataset 2

All experimental data and structures. (XLSX 98 kb)

Supplementary Dataset 3

QSPR Models – Descriptors and model coefficients. (XLSX 12211 kb)

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Over, B., Matsson, P., Tyrchan, C. et al. Structural and conformational determinants of macrocycle cell permeability. Nat Chem Biol 12, 1065–1074 (2016).

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