An Active Gene Annotation Corpus and Its Application on Anti-epilepsy Drug Discovery

After mutation, a gene either gains or loses a function, which is considered to be a critical piece of information for understanding a related pathology and thus for drug discovery. By classifying association of genes and phenotypes using the information of gain-of-function or loss-of-function, the exploration for drug repurposing can be guided in a much more efficient way. We present the active gene annotation corpus (AGAC), which contains 500 manually annotated abstracts collected from PubMed. Five bio-concept labels and three regulatory concept labels were designed for concept level annotation. Furthermore, two relation types, “Theme” and “Cause”, were designed to interlink regulatory concepts with their thematic and causal elements. We evaluated AGAC from three aspects, the results of which indicate the high quality of the annotation. Eventually, a PubMed-wide case study was performed to show that by using AGAC the process of anti-epilepsy drug discovery can be enhanced. After text retrieval, filtering, text classification and matching with DrugBank entries, 281 gene-drug pairs and 112 drugs were obtained and 30 out of 112 were recorded in databases. Among 10 newly predicted multi-target drugs which were not recorded in databases, 6 of them were found to be related to epilepsy with literature support, i.e., Oxazepam, Temazepam, Halazepam, Prazepam, Zolpidem and Thiamylal. The result of the case study support the potential of AGAC for enhancing knowledge discovery for drug repurposing.