TargetPf: A Plasmodium falciparum protein localization predictor

Background: In P. falciparum a similarity between the transit peptides of apicoplast and mitochondrial proteins in the context of net positive charge has previously been observed in few proteins. Existing P. falciparum protein localization prediction tools were leveraged in this study to study this similarity in larger sets of these proteins. Results: The online public-domain malarial repository PlasmoDB was utilized as the source of apicoplast and mitochondrial protein sequences for the similarity study of the two types of transit peptides. It was found that many of the 551 apicoplast-targeted proteins (NEAT proteins) of PlasmoDB may have been wrongly annotated to localize to the apicoplast, as some of these proteins lacked annotations for signal peptides, while others also had annotations for localization to the mitochondrion (NEMT proteins). Also around 50 NEAT proteins could contain signal anchors instead of signal peptides in their N-termini, something that could have an impact on the current theory that explains localization to the apicoplast [1]. The P. falciparum localization prediction tools were then used to study the similarity in net positive charge between the transit peptides of NEAT and NEMT proteins. It was found that NEAT protein prediction tools like PlasmoAP and PATS could be made to recognize NEMT proteins as NEAT proteins, while the NEMT predicting tool PlasMit could be made to recognize a significant number of NEAT proteins as NEMT. Based on these results a conjecture was proposed that a single technique may be sufficient to predict both apicoplast and mitochondrial transit peptides. An implementation in PERL called TargetPf was implemented to test this conjecture (using PlasmoAP rules), and it reported a total of 408 NEAT proteins and 1504 NEMT proteins. This number of predicted NEMT proteins (1504) was significantly higher than the annotated 258 NEMT proteins of plasmoDB, but more in line with the 1200 predictions of the tool PlasMit. Conclusions: Some possible ambiguities in the PlasmoDB annotations related to NEAT protein localization were identified in this study. It was also found that existing P. falciparum localization prediction tools can be made to detect transit peptides for which they have not been trained or built for