HDACiAP: A Curated Database and Analytical Platform for Histone Deacetylase Inhibitors

作者:Xiao, Y.; Ou, J.; Chen, J.; Zhou, X.; Fu, X.; Hu, J.; Ye, Z*.; Chen, G*.; Kang, W*

发表期刊:Journal of Chemical Information and Modeling(2026),Vol. None,pp. None

DOI:10.1021/acs.jcim.6c00572

article 2026

摘要

Histone deacetylases (HDACs) are pivotal epigenetic regulators that are aberrantly expressed in various cancers, making them prominent targets for anticancer drug development. Herein, we present HDACiAP (https://hdac.kangsgo.cn), a meticulously curated, comprehensive database and analytical platform dedicated to HDAC inhibitors. HDACiAP currently encompasses 32,721 compounds with 123,154 bioactivity records, integrating multidimensional data such as physicochemical properties, biological activities, toxicity predictions, compound selectivity annotations, computationally generated docking poses, and protein–ligand interaction profiles. The platform incorporates built-in molecular docking and integrated machine learning and deep learning-based prediction modules, enabling users to evaluate the potency of novel compounds. Additionally, HDACiAP offers an intuitive visualization interface, multimodal search capabilities, and programmatic access via RESTful APIs. In summary, by providing a curated bioactivity resource together with computational docking annotations and predictive models, HDACiAP offers a practical platform for exploring HDAC inhibitor chemical space, supporting preliminary virtual screening, and facilitating AI-assisted discovery of HDAC-targeted compounds.

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