Identification of Potential Tryptase Inhibitors from FDA-Approved Drugs Using Machine Learning, Molecular Docking, and Experimental Validation-Reference-Cited by-同舟云学术

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Identification of Potential Tryptase Inhibitors from FDA-Approved Drugs Using Machine Learning, Molecular Docking, and Experimental Validation

Published:2024-09-04 Issue: Volume: Page:
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Yasir Muhammad¹,Park Jinyoung¹,Han Eun-Taek²,Park Won Sun³,Han Jin-Hee²,Chun Wanjoo¹^ORCID

Affiliation:

1. Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon, 24341, Republic of Korea

2. Department of Medical Environmental Biology and Tropical Medicine, Kangwon National University School of Medicine, Chuncheon, 24341, Republic of Korea

3. Department of Physiology, Kangwon National University School of Medicine, Chuncheon, 24341, Republic of Korea

Funder

Kangwon National University

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.4c04886

Reference51 articles.

1. Mast Cell Modulation of B Cell Responses: An Under-Appreciated Partnership in Host Defence

2. Mast cell-mediated immune regulation in health and disease

3. The role of human mast cells in allergy and asthma

4. Novel Strategies to Target Mast Cells in Disease

5. Mast Cell Biology at Molecular Level: a Comprehensive Review

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