{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T11:23:25Z","timestamp":1773833005037,"version":"3.50.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T00:00:00Z","timestamp":1772409600000},"content-version":"vor","delay-in-days":2,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["NSTC 112-2221-E-A49-061-MY3"],"award-info":[{"award-number":["NSTC 112-2221-E-A49-061-MY3"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","award":["NSTC 114-2221-E-A49-144-MY3"],"award-info":[{"award-number":["NSTC 114-2221-E-A49-144-MY3"]}],"id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,2,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Identifying drugs that target intercellular communication networks represents a promising therapeutic strategy, yet linking single-cell RNA sequencing (scRNA-seq) analysis to structure-based drug screening remains technically challenging and requires substantial bioinformatics expertise. We present scDock, an integrated and user-friendly pipeline that seamlessly connects scRNA-seq data processing, cell\u2013cell communication inference, and molecular docking-based drug discovery. Through a single configuration file, users can execute the complete workflow, from raw scRNA-seq data to ranked drug candidates, without programming skills. scDock automates the identification of disease-relevant ligand\u2013receptor interactions from scRNA-seq data and performs structure-based virtual screening against these communication targets using Protein Data Bank (PDB) or AlphaFold-predicted protein structures. The pipeline generates comprehensive outputs at each stage, enabling users to explore intercellular signaling alterations and discover therapeutic compounds targeting specific cell\u2013cell communications. scDock addresses a critical gap by providing an accessible end-to-end solution for communication-targeted drug discovery from single-cell data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>scDock is freely available at https:\/\/doi.org\/10.6084\/m9.figshare.31370368 and https:\/\/github.com\/Andrewneteye4343\/scDock. It is implemented in R, Python, shell scripts, and supports Linux systems, including Ubuntu and Debian.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag103","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T12:44:02Z","timestamp":1772196242000},"source":"Crossref","is-referenced-by-count":0,"title":["scDock: streamlining drug discovery targeting cell\u2013cell communication via scRNA-seq analysis and molecular docking"],"prefix":"10.1093","volume":"42","author":[{"given":"Chen-Hao","family":"Huang","sequence":"first","affiliation":[{"name":"Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University , Taipei 106,","place":["Taiwan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yen-Jen","family":"Oyang","sequence":"additional","affiliation":[{"name":"Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University , Taipei 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