Prediction of drug penetration in tuberculosis lesions

Jansy P. Sarathy (Lead / Corresponding author), Fabio Zuccotto, Ho Hsinpin, Lars Sandberg, Laura E. Via, Gwendolyn A. Marriner, Thierry Masquelin, Paul Wyatt, Peter Ray, Véronique Dartois

Research output: Contribution to journalArticle

45 Citations (Scopus)
104 Downloads (Pure)

Abstract

The penetration of antibiotics in necrotic tuberculosis lesions is heterogeneous and drug-specific, but the factors underlying such differential partitioning are unknown. We hypothesized that drug binding to macromolecules in necrotic foci (or caseum) prevents passive drug diffusion through avascular caseum, a critical site of infection. Using a caseum binding assay and MALDI mass spectrometry imaging of tuberculosis drugs, we showed that binding to caseum inversely correlates with passive diffusion into the necrotic core. We developed a high-throughput assay relying on rapid equilibrium dialysis and a caseum surrogate designed to mimic the composition of native caseum. A set of 279 compounds was profiled in this assay to generate a large data set and explore the physicochemical drivers of free diffusion into caseum. Principle component analysis and modeling of the data set delivered an in silico signature predictive of caseum binding, combining 69 molecular descriptors. Among the major positive drivers of binding were high lipophilicity and poor solubility. Determinants of molecular shape such as the number of rings, particularly aromatic rings, number of sp(2) carbon counts, and volume-to-surface ratio negatively correlated with the free fraction, indicating that low-molecular-weight nonflat compounds are more likely to exhibit low caseum binding properties and diffuse effectively through caseum. To provide simple guidance in the property-based design of new compounds, a rule of thumb was derived whereby the sum of the hydrophobicity (clogP) and aromatic ring count is proportional to caseum binding. These tools can be used to ensure desirable lesion partitioning and guide the selection of optimal regimens against tuberculosis.

Original languageEnglish
Pages (from-to)552-563
Number of pages12
JournalACS Infectious Diseases
Volume2
Issue number8
Early online date22 Jun 2016
DOIs
Publication statusPublished - 12 Aug 2016

Keywords

  • Caseum
  • Drug penetration
  • Granuloma
  • In vitro assay
  • Mycobacterium tuberculosis
  • Principle component analysis

Fingerprint Dive into the research topics of 'Prediction of drug penetration in tuberculosis lesions'. Together they form a unique fingerprint.

  • Cite this

    Sarathy, J. P., Zuccotto, F., Hsinpin, H., Sandberg, L., Via, L. E., Marriner, G. A., Masquelin, T., Wyatt, P., Ray, P., & Dartois, V. (2016). Prediction of drug penetration in tuberculosis lesions. ACS Infectious Diseases, 2(8), 552-563. https://doi.org/10.1021/acsinfecdis.6b00051