DEC 09, 2020 1:00 PM EST

Using Physical Chemistry and a High-Throughput Drug Screen to Find a Drug to Treat Sickle Cell Disease

Speaker
  • Emily Dunkelberger, PhD

    Staff Scientist, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health
    BIOGRAPHY

Abstract

Sickle cell disease is considered an orphan disease in the United States, but affects millions of people world‐wide, primarily in sub-Saharan Africa and India. The molecular basis for the disease is a point mutation on the gene that codes for the beta‐strands of hemoglobin. In the 1990s, the first and only anti‐sickling drug, hydroxyurea, was approved by the FDA.
Hydroxyurea induces the production of fetal hemoglobin, which dilutes sickle hemogoblin and slows or prevents hemoglobin aggregation upon deoxygenation. However, hydroxyurea only works for a portion of those affected by sickle cell disease and can come with many severe side effects. At NIH, colleagues have found that –about 10% of sickle cell patients can be cured by stem cell transplantation, but an inexpensive drug that can be given orally and distributed worldwide is needed.

Over the past couple of years, research initiatives at the Eaton group have led to development of a high‐throughput drug screen that is currently being used to test a library of 12,000+ compounds that have previously been tested in humans. Drug repurposing is the highest priority, as it provides the quickest route from the lab to sickle cell disease patients. The assay depends on having an understanding of the underlying cause of the disease‐damaged, deoxygenated red blood cells that block the microcirculation and cause organ damage. Increasing the delay time between deoxygenation and sickling makes the disease survivable. In the drug screen workflow, a brightfield microscope is used to collect images of sickle red blood cells as a function of time after deoxygenation in the absence and presence of compounds in the test library. A machine learning algorithm identifies sickled cells based on differences in cellular properties such as morphology and optical density between unsickled and sickled cells. Any compound that increases the delay time prior to sickling or inhibits overall sickling compared to the control is considered a hit, and if the compound is known to be non‐toxic to humans, it may be immediately moved into research clinical trials at NIH.


 For Research Use Only. Not for use in diagnostic procedures.


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