COMPUTATIONAL SCREENING FOR NOVEL INHIBITORS OF PROTEINS IN THE MAST CELL DEGRANULATION PATHWAY
COMPUTATIONAL SCREENING FOR NOVEL INHIBITORS OF PROTEINS IN THE MAST CELL DEGRANULATION PATHWAY
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Date
2021
Authors
Fadul, Naja
Kasica, Zachary
Laurence, Kyeisha
Moy, Stephanie
Murugan, Sindhu
Pamala, Chinmayi
Robinson, Morgan
Shah, Rohan
Shrestha, Mansu
Smith, Marcus
Advisor
Frauwirth, Kenneth
Citation
DRUM DOI
Abstract
Allergies are a pervasive issue and require novel ways of alleviating symptoms.
Existing treatments focus on symptom management and immunotherapy in response to
an allergic reaction. However, there is also the potential for prophylactic treatment that
inhibits molecules involved in the mast cell degranulation pathway, which causes allergic
symptoms. We identified potential target proteins downstream of this pathway including
PKC, PLCγ, and PI3K isoforms, the activation of which results in the degranulation of
mast cells. We computationally modeled protein-inhibitor binding interactions and
identified inhibitors with the predicted highest binding affinity to the target pathway
proteins. For the most efficient inhibitors, we extended our analysis by construction of
analogs to determine which chemical properties of the inhibitors contributed to the
highest binding affinity. The identified possible inhibitors have the potential to hinder
mast cell degranulation, limit histamine and cytokine release, and therefore prevent
allergic symptoms, making them ideal targets for future pharmacology research.
Notes
Gemstone Team CASCADE