Leveraging deep learning and structure-based drug repurposing for the discovery of potent Trk-A inhibitors targeting CIPA.

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Bibliographic Details
Title: Leveraging deep learning and structure-based drug repurposing for the discovery of potent Trk-A inhibitors targeting CIPA.
Authors: Iqbal MW; State Key Laboratory of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing 100029, PR China., Haider SZ; International Joint Laboratory on Synthetic Biology and Biomass Biorefinery, Biofuels Institute, School of Emergency Management, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China., Sun X; State Key Laboratory of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing 100029, PR China., Al-Ghanim KA; Department of Zoology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia., Nawaz MZ; International Joint Laboratory on Synthetic Biology and Biomass Biorefinery, Biofuels Institute, School of Emergency Management, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China. Electronic address: chzohaib@gmail.com., Yuan Q; State Key Laboratory of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing 100029, PR China. Electronic address: yuanqp@mail.buct.edu.cn.
Source: Bioorganic chemistry [Bioorg Chem] 2025 Aug; Vol. 163, pp. 108680. Date of Electronic Publication: 2025 Jun 11.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 1303703 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1090-2120 (Electronic) Linking ISSN: 00452068 NLM ISO Abbreviation: Bioorg Chem Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1090-2120
DOI:10.1016/j.bioorg.2025.108680