PSEApred2
Prediction of Plasmodium Secretory and
Infected Erythrocyte Associated Proteins.
Why PSEApred2 ?
PSEApred is a general method for predicting secretory proteins of malaria parasite, which is based on SVM module,uses dipeptide composition with PSSM profiles obtained from PSI-BLAST. But it has following short comings:
Due to the above reasons we have come up with more efficient and accurate method and named it PSEApred2 as an extension of PSEApred.
PSEApred2
Malaria the most dreadful disease of the developing countries needs a much more attention. Out of the known species of malaria, Plasmodium falciparum is the most studied one. This parasite secretes many proteins in infected erythrocyte which helps the parasite to use the host cell’s machinery for its growth and survival. This calls for the need of identifying these proteins which could be potential candidates for designing vaccine/drug targets against malaria
PSEApred2 is the succession of previously developed method PSEApred for prediction of secretory proteins of Plasmodium falciparum with new features. PSEApred2 identifies secretory proteins using three types of models. Firstly we develop motif based strategy for predicting secretory proteins having PEXEL/VTS motif using MEME/MAST. This cover families life rifin and stevor. Secondly we developed a domain based approach for predicting proteins which have Duffy binding domain using HMMER. Thirdly we developed a SVM based model using composition of proteins for predicting experimentally proved secretory proteins which do not have motif or domain. In case of SVM model we achieve a maximal MCC 0.58, 0.57, 0.68 and accuracy 78.95%, 78.29%, 84.21% using amino acid composition, dipeptide composition and Position Specific Scoring Matrix (PSSM) respectively. These models are able to cover a wide range of experimentally known secretory proteins which lack the PEXEL motif.
Click HERE to access the Supplementary Section which have dataset of pseapred2.