Researchers are under constant pressure to provide solutions to meet the challenges of a growing world population and advance One Health. Translational biology can play an important role in achieving these goals by transforming basic research discoveries into practice quickly and efficiently. In plants, basic science can indeed be translated into methods to develop and improve crop varieties and thus achieve food security in a sustainable and safe way. Grain legumes are an important source of protein for animal and human nutrition. They are part of a large plant family with several, closely-related, agronomically-important crops. As the demand for plant-based protein continues to grow, more land is being devoted to these crops, but many environmental influences still constrain their productivity. Improving the response of grain legumes to limiting factors is key to ensuring the stability of yield and grain quality. Here, we report the development of OrthoLegKB, a knowledge graph database for grain legumes. The framework relies heavily on orthology and synteny relationships to build bridges between species, and transfer and/or compare information between them. Users can integrate published and unpublished data related to their species of interest including genetic, genomic and transcriptomic information. Heterogeneous datasets from multiple species can be accessed and explored with quasi-instantaneous query times, allowing relevant biological questions to be addressed, hypotheses to be generated, and information from a single or group of species to be transferred to others. OrthoLegKB is a significant step towards translational approaches in grain legumes and a great tool for research and breeding. The number of legume species will be constantly increased. Future developments to accommodate pangenomic datasets as well as proteomic and metabolomic information will further enrich the query capabilities.