Integrating bioinformatics resources can make use of specialised information from different sources to enhance their utility. The subcellular location database for Arabidopsis proteins (SUBA) includes locations based on both predictions or experimental evidence for over 35,888 proteins (May 2014). SUBA allows for structured localisation queries on including combinations of protein location, evidence type and literature reference. The BioCyc framework of metabolic databases creates pathway/genome databases (PGDB) that allow for queries based on pathways of an organism. AraCyc is a heavily curated PGDB for Arabidopsis thaliana. AraCyc 11.5 has 321 localisation (May 2014).We present work in progress on the integration of SUBA localisation data into the Arabidopsis metabolic database (AraCyc) in a way consistent with the evidence ontology of the BioCyc framework. This integration will allow for metabolic pathway focused queries to benefit from the SUBA localisation database to enhance the utility of both SUBA and AraCyc. This approach can be extended to other organisms with BioCyc databases and to other sources of localisation data.