Identification of Proteins Secreted by Malaria Parasite into Erythrocyte using SVM and PSSM profiles

Background: Malaria parasite secretes various proteins in infected RBC for its growth and survival. Thus identification of these secretory proteins is important for developing vaccine/drug against malaria. The existing motif-based methods have got limited success due to lack of universal motif in all secretory proteins of malaria parasite. Results: In this study a systematic attempt has been made to develop a general method for predicting secretory proteins of malaria parasite. All models were trained and tested on a nonredundant dataset of 252 secretory and 252 non-secretory proteins. We developed SVM models and achieved maximum MCC 0.72 with 85.65% accuracy and MCC 0.74 with 86.45% accuracy using amino acid and dipeptide composition respectively. SVM models were developed using split-amino acid and split-dipeptide composition and achieved maximum MCC 0.74 with 86.40% accuracy and MCC 0.77 with accuracy 88.22% respectively. In this study, for the first time PSSM profiles obtained fro...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Ruchi Verma, Ajit Tiwari, Sukhwinder Kaur, Grish C. Varshney, Gajendra P. S. Raghava
• Keywords: BMCBI 2008, Malaria Parasites, Secretory Proteins, SVM Model