PSEApred: Identification of Proteins Secreted by Malaria Parasite into Erythrocyte Using SVM and PSSM Profiles

PSEApred: Identification of Proteins Secreted by Malaria Parasite into Erythrocyte Using SVM and PSSM Profiles PSEApred is a computational web server developed for predicting proteins secreted by the malaria parasite Plasmodium falciparum into infected erythrocytes. The tool helps identify parasite-secreted proteins that may be involved in host-cell remodeling, parasite survival, immune evasion, malaria pathogenesis, and potential drug or vaccine target discovery. PSEApred uses support vector machine-based models trained on amino acid composition, dipeptide composition, split-composition features, pseudo amino acid composition, and evolutionary information from PSSM profiles. Web Server: http://www.imtech.res.in/raghava/pseapred/ Citation Verma, R., Tiwari, A., Kaur, S., Varshney, G. C., and Raghava, G. P. S. Identification of proteins secreted by malaria parasite into erythrocyte using SVM and PSSM profiles. BMC Bioinformatics, 9, 201, 2008. https://doi.org/10.1186/1471-2105-9-201 About the Research Plasmodium falciparum secretes several proteins into infected red blood cells during malaria infection. These secreted proteins help the parasite survive inside the host cell, remodel the erythrocyte, alter membrane rigidity and permeability, support cytoadherence, and evade host immunity. Identifying secretory proteins of malaria parasites is important because these proteins can serve as potential drug targets, vaccine candidates, and markers for understanding malaria pathogenesis. Earlier methods mainly depended on known export motifs such as PEXEL or VTS. However, many experimentally known secreted proteins do not contain these motifs, suggesting that multiple secretion pathways may exist. PSEApred was developed as a general sequence-based method that does not depend only on a single conserved motif. Data Compilation: The study used a non-redundant dataset of 252 secretory and 252 non-secretory Plasmodium falciparum proteins. Secretory proteins were collected from literature and included Rifins, Stevors, PfEMP1 proteins, experimentally validated secretory proteins, REX proteins, PIESPs, clag9, Sbp1, and Maurer’s cleft-associated proteins. Non-secretory proteins were collected from Swiss-Prot and PlasmoDB. Methodology: PSEApred uses support vector machine models trained on sequence-derived features and evolutionary information. The study tested amino acid composition, dipeptide composition, split amino acid composition, split dipeptide composition, pseudo amino acid composition, and PSSM profiles generated using PSI-BLAST.