GDP : GroEL Dependency Predictor

In cellular environment proteins perform various essential jobs. And to do so they are required to be in their native structural state, where some of them do not achieve the reuire state by themselves and are trapped in misfolded state. Chaperone network helps some of this misfolded proteins to get their native states and GroEL plays an irreplaceable role in this network. How GroEl identify misfolded proteins is still unknown.

The GroEL interacting proteins are further classified in three classes such as;
C1 (37): Only interacts with GroEL but not dependent, download
C2 (125): Partially dependent on GroEL, download
C3 (83): Obligate to GroEL in normal cell condition download and
NS (326): Not interacts or depends on GroEL download.

The above dataset are used to build a SVM-based predictor model which can identify the amount of GroEL dependency of proteins from thier primary sequence (i.e. from amino acid sequence).
The platform independent tool is available here.