An automatic text-mining pipeline was developed and plugged into the VirHostNet system in order to prioritize scientific papers for protein-protein interaction curation. As a first step, all abstracts containing keywords related to both viruses and experimental procedures used for interactions identification (mainly yeast-two hybrid, co-imunoprecipitation, pull-down and tandem affinity purification) were extracted for an in-depth expertise. During curation, protein-protein interactions were carefully annotated according to: (i) the protein accession numbers of each of the protein interactor, the human and/or viral proteins being respectively referenced to ENSEMBL and NCBI accession numbers; (ii) the molecular interaction methods based on the PSI-MI 2.5 ontology vocabulary; and (iii) the PMIDs. Based on 1174 selected PMIDs, literature curation led to the annotation of 2186 redundant interactions in 723 papers (Supplementary Table 2 ). This effort significantly complemented data from public databases with 1297 new non-redundant protein-protein interactions. In order to provide a higher level of data accuracy, virus-virus and virus-host protein-protein interactions from public databases were also carefully inspected.