Breast cancer is one of the most common malignancies in women around the world. Among the various hormonal types of breast cancer, those that are estrogen receptor (ER) positive account for the majority. Among the estrogen related receptors, estrogen related receptor ${alpha}$ is known to have a potential role in breast cancer and is one of the therapeutic target. Hence, prediction of novel ligands interact with estrogen related receptor alpha is therapeutically important. The present study, aims at prediction and analysis of ligands from the KEGG COMPOUND database (containing 10,739 entries) able to interact against estrogen receptor alpha using a similarity search and molecular docking approach.