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