Target identification and validation is crucial for drug discovery. Besides the disease relevance, successful drug targets generally have some common features different from other non-target proteins. Target prediction (i.e. predicting whether a protein is proper to be a target) based on characteristics of successful drug targets will help improve the efficiency and success rate of target selection.
Protein and peptide drugs, after decades of development have grown into a major drug class of the marketplace, and their research and development (R ＆ D) and approval are constantly keeping hot and market share increasing steadily. Research indicates that target properties of protein and peptide drugs are significantly different from those of traditional, dominant small-molecule drugs.
POPPIT (Predictor Of Protein, PeptIde, small-molecule drugs’ therapeutic Targets) is the first web server for human genome-wide target prediction specially for different drug types (including protein, peptide and small-molecule drugs) based on their respective features, and meanwhile provides various annotations (including >60 data fields) for the potential targets and their relevance to various diseases, aiming to improve efficiency and success rate of target selection.
POPPIT supports two simple workflows. In the first one, users start from this homepage to firstly do the target prediction and then can also further check predicted candidate targets' associated disease. In the second one, users start with an interested disease from "Disease2Target" page and then do target estimation for proteins with relevance to the disease.
Please see Documents for more information.