To successfully fight against future coronavirus infections, intensive studies have been undertaken to identify effective and safe drugs. Many drugs have been identified to be effective against the infection of human coronavirus (including SARS-CoV, SAR-CoV-2, and MERS-CoV) in vitro or in vivo in an experimental or clinical setting. A systematic collection, annotation, representation, and analysis of these drugs, including chemical drugs and biological antibodies, would help us better understand the mechanisms under these drugs and facilitate future rational design. With this rationale in mind, we have conducted semi-manual and manual literature collection and annotation of these drugs and perform systematic study on them. The Coronavirus Infectious Disease Ontology (CIDO) has been used as an ontological platform to represent the anti-coronaviral drugs, active chemical compounds of these drugs, drug targets, biological processes, viruses, and the relations among these entities. For drug study, CIDO reuses many terms from existing ontologies including ChEBI, DrON, NDF-RT, and GO, and also developed new relations and axioms to semantically link and represent different entities together for integrative representation and analysis. We have also conducted many CIDO-based systematic analysis on our manually annotated anti-coronavirus drugs. This study has been published: Liu Y, Hur J, Chan WKB, Wang Z, Xie J, Sun D, Handelman S, Sexton J, Yu H, He Y. Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection. Sci Data 8, 16 (2021). doi: 10.1038/s41597-021-00799-w. PMID: 33441564. PMCID: PMC7806933. Links: https://www.nature.com/articles/s41597-021-00799-w , https://pubmed.ncbi.nlm.nih.gov/33441564/ , https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7806933/.