Identification of Hit Compounds Using Artificial Intelligence for the Management of Allergic Diseases

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Abstract
This study aimed to identify and evaluate drug candidates targeting the kinase inhibitory region of suppressor of cytokine signaling (SOCS) 3 for the treatment of allergic rhinitis (AR). Utilizing an artificial intelligence (AI)-based new drug development platform, virtual screening was conducted to identify compounds inhibiting the SH2 domain binding of SOCS3. Luminescence assays assessed the ability of these compounds to restore JAK-2 activity diminished by SOCS3. Jurkat T and BEAS-2B cells were utilized to investigate changes in SOCS3 and STAT3 expression, along with STAT3 phosphorylation in response to the identified compounds. In an OVA-induced allergic rhinitis mouse model, we measured serum levels of total IgE and OVA-specific IgE, performed real-time PCR on nasal mucosa samples to quantify Th2 cytokines and IFN-γ expression, and conducted immunohistochemistry to analyze eosinophil levels. Screening identified 20 hit compounds with robust binding affinities. As the concentration of SOCS3 increased, a corresponding decrease in JAK2 activity was observed. Compounds 5 and 8 exhibited significant efficacy in restoring JAK2 activity without toxicity. Treatment with these compounds resulted in reduced SOCS3 expression and the reinstatement of STAT3 phosphorylation in Jurkat T and BEAS-2B cells. In the OVA-induced allergic rhinitis mouse model, compounds 5 and 8 effectively alleviated nasal symptoms and demonstrated lower levels of immune markers compared to the allergy group. This study underscores the promising nonclinical efficacy of compounds identified through the AI-based drug development platform. These findings introduce innovative strategies for the treatment of AR and highlight the potential therapeutic value of targeting SOCS3 in managing AR.
Funding Information
  • National Research Foundation of Korea (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Ministry of Science and ICT, South Korea (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Institute for Information & communications Technology Planning & Evaluation (IITP) (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Korea Health Industry Development Institute (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Korea Health Industry Development Institute (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Ministry of Health and Welfare (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Korea University (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)
  • Korea University Medical Center and Anam Hospital (2017R1A2B2003575, NRF-2020R1A2C1006398, 2020R1C1C1012288, IITP-2023-2020-0-01819, HR22C1302, HI17C0387)

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