Phosphatases are well known drug targets for diseases such as diabetes, obesity and other autoimmune diseases. Their role in cancer is due to unusual expression patterns in different types of cancer. However, there is strong evidence for selective targeting of phosphatases in cancer therapy. Several experimental and in silico techniques have been attempted for design of phosphatase inhibitors, with focus on diseases such as diabetes, inflammation and obesity. Their utility for cancer therapy is limited and needs to be explored vastly. Quantitative Structure Activity relationship (QSAR) is well established in silico ligand based drug design technique, used by medicinal chemists for prediction of ligand binding affinity and lead design. These techniques have shown promise for subsequent optimization of already existing lead compounds, with an aim of increased potency and pharmacological properties for a particular drug target. Furthermore, their utility in virtual screening and scaffold hopping is highlighted in recent years. This review focuses on the recent molecular field analysis (MFA) and QSAR techniques, directed for design and development of phosphatase inhibitors and their potential use in cancer therapy. In addition, this review also addresses issues concerning the binding orientation and binding conformation of ligands for alignment sensitive QSAR approaches.