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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.


  1. Lipinski, C.A., Lombardo, F., Dominy, B.W. & Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 46, 3–26 (2001).

    Article  CAS  PubMed  Google Scholar 

  2. Doak, B.C., Zheng, J., Dobritzsch, D. & Kihlberg, J. How beyond rule of 5 drugs and clinical candidates bind to their targets. J. Med. Chem. 59, 2312–2327 (2016).

    Article  CAS  PubMed  Google Scholar 

  3. Doak, B.C., Over, B., Giordanetto, F. & Kihlberg, J. Oral druggable space beyond the rule of 5: insights from drugs and clinical candidates. Chem. Biol. 21, 1115–1142 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. Driggers, E.M., Hale, S.P., Lee, J. & Terrett, N.K. The exploration of macrocycles for drug discovery--an underexploited structural class. Nat. Rev. Drug Discov. 7, 608–624 (2008).

    Article  CAS  PubMed  Google Scholar 

  5. Surade, S. & Blundell, T.L. Structural biology and drug discovery of difficult targets: the limits of ligandability. Chem. Biol. 19, 42–50 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Mallinson, J. & Collins, I. Macrocycles in new drug discovery. Future Med. Chem. 4, 1409–1438 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Giordanetto, F. & Kihlberg, J. Macrocyclic drugs and clinical candidates: what can medicinal chemists learn from their properties? J. Med. Chem. 57, 278–295 (2014).

    Article  CAS  PubMed  Google Scholar 

  8. Villar, E.A. et al. How proteins bind macrocycles. Nat. Chem. Biol. 10, 723–731 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Bockus, A.T. et al. Probing the physicochemical boundaries of cell permeability and oral bioavailability in lipophilic macrocycles inspired by natural products. J. Med. Chem. 58, 4581–4589 (2015).

    Article  CAS  PubMed  Google Scholar 

  10. Hewitt, W.M. et al. Cell-permeable cyclic peptides from synthetic libraries inspired by natural products. J. Am. Chem. Soc. 137, 715–721 (2015).

    Article  CAS  PubMed  Google Scholar 

  11. Nielsen, D.S. et al. Improving on nature: making a cyclic heptapeptide orally bioavailable. Angew. Chem. Int. Ed. Engl. 53, 12059–12063 (2014).

    Article  CAS  PubMed  Google Scholar 

  12. Wang, C.K. et al. Rational design and synthesis of an orally bioavailable peptide guided by NMR amide temperature coefficients. Proc. Natl. Acad. Sci. USA 111, 17504–17509 (2014).

    Article  CAS  PubMed  Google Scholar 

  13. Rosenquist, Å. et al. Discovery and development of simeprevir (TMC435), a HCV NS3/4A protease inhibitor. J. Med. Chem. 57, 1673–1693 (2014).

    Article  CAS  PubMed  Google Scholar 

  14. Rezai, T. et al. Conformational flexibility, internal hydrogen bonding, and passive membrane permeability: successful in silico prediction of the relative permeabilities of cyclic peptides. J. Am. Chem. Soc. 128, 14073–14080 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Thansandote, P. et al. Improving the passive permeability of macrocyclic peptides: balancing permeability with other physicochemical properties. Bioorg. Med. Chem. 23, 322–327 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Wang, C.K. et al. Exploring experimental and computational markers of cyclic peptides: charting islands of permeability. Eur. J. Med. Chem. 97, 202–213 (2015).

    Article  CAS  PubMed  Google Scholar 

  17. Schreiber, S.L. Organic chemistry: molecular diversity by design. Nature 457, 153–154 (2009).

    Article  CAS  PubMed  Google Scholar 

  18. Lovering, F. Escape from flatland 2: complexity and promiscuity. Med. Chem. Commun. 4, 515–519 (2013).

    Article  CAS  Google Scholar 

  19. Fitzgerald, M.E. et al. Build/couple/pair strategy for the synthesis of stereochemically diverse macrolactams via head-to-tail cyclization. ACS Comb. Sci. 14, 89–96 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Marcaurelle, L.A. et al. An aldol-based build/couple/pair strategy for the synthesis of medium- and large-sized rings: discovery of macrocyclic histone deacetylase inhibitors. J. Am. Chem. Soc. 132, 16962–16976 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Comer, E. et al. Fragment-based domain shuffling approach for the synthesis of pyran-based macrocycles. Proc. Natl. Acad. Sci. USA 108, 6751–6756 (2011).

    Article  CAS  PubMed  Google Scholar 

  22. Waring, M.J. Lipophilicity in drug discovery. Expert Opin. Drug Discov. 5, 235–248 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Artursson, P. & Karlsson, J. Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells. Biochem. Biophys. Res. Commun. 175, 880–885 (1991).

    Article  CAS  Google Scholar 

  24. Artursson, P., Palm, K. & Luthman, K. Caco-2 monolayers in experimental and theoretical predictions of drug transport. Adv. Drug Deliv. Rev. 22, 67–84 (1996).

    Article  CAS  Google Scholar 

  25. Hubatsch, I., Ragnarsson, E.G. & Artursson, P. Determination of drug permeability and prediction of drug absorption in Caco-2 monolayers. Nat. Protoc. 2, 2111–2119 (2007).

    Article  CAS  PubMed  Google Scholar 

  26. Giacomini, K.M. et al. Membrane transporters in drug development. Nat. Rev. Drug Discov. 9, 215–236 (2010).

    Article  CAS  PubMed  Google Scholar 

  27. Matsson, P., Pedersen, J.M., Norinder, U., Bergström, C.A. & Artursson, P. Identification of novel specific and general inhibitors of the three major human ATP-binding cassette transporters P-gp, BCRP and MRP2 among registered drugs. Pharm. Res. 26, 1816–1831 (2009).

    Article  CAS  PubMed  Google Scholar 

  28. Heinis, C. Drug discovery: tools and rules for macrocycles. Nat. Chem. Biol. 10, 696–698 (2014).

    Article  CAS  PubMed  Google Scholar 

  29. Matsson, P. et al. Exploring the role of different drug transport routes in permeability screening. J. Med. Chem. 48, 604–613 (2005).

    Article  CAS  PubMed  Google Scholar 

  30. Raub, T.J. P-glycoprotein recognition of substrates and circumvention through rational drug design. Mol. Pharm. 3, 3–25 (2006).

    Article  CAS  PubMed  Google Scholar 

  31. Zamek-Gliszczynski, M.J. et al. The important role of Bcrp (Abcg2) in the biliary excretion of sulfate and glucuronide metabolites of acetaminophen, 4-methylumbelliferone, and harmol in mice. Mol. Pharmacol. 70, 2127–2133 (2006).

    Article  CAS  PubMed  Google Scholar 

  32. Ferreira, R.J., Ferreira, M.J.U. & dos Santos, D.J.V.A. Molecular docking characterizes substrate-binding sites and efflux modulation mechanisms within P-glycoprotein. J. Chem. Inf. Model. 53, 1747–1760 (2013).

    Article  CAS  PubMed  Google Scholar 

  33. Desai, P.V., Raub, T.J. & Blanco, M.J. How hydrogen bonds impact P-glycoprotein transport and permeability. Bioorg. Med. Chem. Lett. 22, 6540–6548 (2012).

    Article  CAS  PubMed  Google Scholar 

  34. Hitchcock, S.A. Structural modifications that alter the P-glycoprotein efflux properties of compounds. J. Med. Chem. 55, 4877–4895 (2012).

    Article  CAS  PubMed  Google Scholar 

  35. Kuhn, B., Mohr, P. & Stahl, M. Intramolecular hydrogen bonding in medicinal chemistry. J. Med. Chem. 53, 2601–2611 (2010).

    Article  CAS  PubMed  Google Scholar 

  36. Guimarães, C.R.W., Mathiowetz, A.M., Shalaeva, M., Goetz, G. & Liras, S. Use of 3D properties to characterize beyond rule-of-5 property space for passive permeation. J. Chem. Inf. Model. 52, 882–890 (2012).

    Article  PubMed  CAS  Google Scholar 

  37. Alex, A., Millan, D.S., Perez, M., Wakenhut, F. & Whitlock, G.A. Intramolecular hydrogen bonding to improve membrane permeability and absorption in beyond rule of five chemical space. Med. Chem. Commun. 2, 669–674 (2011).

    Article  CAS  Google Scholar 

  38. Bockus, A.T. et al. Going out on a limb: delineating the effects of β-branching, N-methylation, and side chain size on the passive permeability, solubility, and flexibility of Sanguinamide A analogues. J. Med. Chem. 58, 7409–7418 (2015).

    Article  CAS  PubMed  Google Scholar 

  39. Varma, M.V.S. et al. Physicochemical space for optimum oral bioavailability: contribution of human intestinal absorption and first-pass elimination. J. Med. Chem. 53, 1098–1108 (2010).

    Article  CAS  PubMed  Google Scholar 

  40. Mathiowetz, A.M., Leung, S.S. & Jacobson, M.P. in Macrocycles in Drug Discovery Vol. 40 (ed. Levin, J.) 367–397 (Royal Soc. Chem. Press, Cambridge, 2014).

  41. Bickerton, G.R., Paolini, G.V., Besnard, J., Muresan, S. & Hopkins, A.L. Quantifying the chemical beauty of drugs. Nat. Chem. 4, 90–98 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Sauer, W.H.B. & Schwarz, M.K. Molecular shape diversity of combinatorial libraries: a prerequisite for broad bioactivity. J. Chem. Inf. Comput. Sci. 43, 987–1003 (2003).

    Article  CAS  PubMed  Google Scholar 

  43. Alelyunas, Y.W., Liu, R., Pelosi-Kilby, L. & Shen, C. Application of a Dried-DMSO rapid throughput 24-h equilibrium solubility in advancing discovery candidates. Eur. J. Pharm. Sci. 37, 172–182 (2009).

    Article  CAS  PubMed  Google Scholar 

  44. Kalvass, J.C. & Pollack, G.M. Kinetic considerations for the quantitative assessment of efflux activity and inhibition: implications for understanding and predicting the effects of efflux inhibition. Pharm. Res. 24, 265–276 (2007).

    Article  CAS  PubMed  Google Scholar 

  45. von Kienlin, M., Moonen, C.T.W., van der Toorn, A. & van Zijl, P.C.M. Rapid recording of solvent-suppressed 2D COSY spectra with inherent quadrature detection using pulsed field gradients. J. Magn. Reson. 93, 423–429 (1991).

    CAS  Google Scholar 

  46. Willker, W., Leibfritz, D., Kerssebaum, R. & Bermel, W. Gradient selection in inverse heteronuclear correlation spectroscopy. Magn. Reson. Chem. 31, 287–292 (1993).

    Article  CAS  Google Scholar 

  47. Marion, D. Rotating frame nuclear overhauser effect: a practical tool for the 1H NMR study of peptides in solution. FEBS Lett. 192, 99–103 (1985).

    Article  CAS  Google Scholar 

  48. Abraham, M.H. et al. An NMR method for the quantitative assessment of intramolecular hydrogen bonding; application to physicochemical, environmental, and biochemical properties. J. Org. Chem. 79, 11075–11083 (2014).

    Article  CAS  PubMed  Google Scholar 

  49. Freyhult, E. et al. Unbiased descriptor and parameter selection confirms the potential of proteochemometric modelling. BMC Bioinformatics 6, 50 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Mateus, A., Matsson, P. & Artursson, P. Rapid measurement of intracellular unbound drug concentrations. Mol. Pharm. 10, 2467–2478 (2013).

    Article  CAS  PubMed  Google Scholar 

  51. Chang, C.C. & Lin, C.J. LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 27:1–27:27 (2011).

    Article  Google Scholar 

  52. Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).

    Article  Google Scholar 

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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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