A model to predict the function of hypothetical proteins through a nine-point classification scoring schema.

Background: Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the challenge in understanding their diverse functions. Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted.

Annotation and curation of uncharacterized proteins- challenges.

Hypothetical proteins (HPs) are the proteins predicted to be expressed from an open reading frame, making a substantial fraction of proteomes in both prokaryotes and eukaryotes. Genome projects have led to the identification of many therapeutic targets, the putative function of the protein, and their interactions. In this review we enlist various methods linking annotation to structural and functional prediction of HPs that assist in the discovery of new structures and functions serving as markers and pharmacological targets for drug designing, discovery, and screening.