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 Online Journal of Bioinformatics  

 Volume 10 (2): 259-279, 2009.

In Silico analysis of translation initiation sites from P. falciparum.


Balakota Reddy Patakottu1, Chandrasekhar Mamidipally2, Swati Patankar1, Santosh Noronha1,2


1Department of Biosciences and Bioengineering, 2Chemical Engineering, Indian Institute of Technology, Mumbai, India.





Patakottu BR, Mamidipally C, Patankar S, Noronha S, In Silico analysis of translation initiation sites from P. falciparum, Onl J Bioinform, 10 (2): 259-279, 2009. The human malaria parasite Plasmodium falciparum has a biased genome composition of 80-90% AT. Due to this bias and the unusually long length of untranslated regions in parasite mRNAs, the number of putative Translation Initiation Sites (TIS) is higher than other eukaryotes and raises the question of which sequence features distinguish true TIS from poorly recognized AUG codons. To address this question we computationally identified sequence features that can predict true TIS in P. falciparum. TIS were predicted using feature generation and standard machine learning classifiers and a dataset containing 61 experimentally well characterized TIS. Eighteen features were identified which classify TIS with an accuracy of 98% and a true positive prediction rate of 87%. These 18 features reflect the parasite genome composition and include bases at the -1,-2, -3, -4 positions, AT-rich features and abundant codons. Annotated genes were analyzed using our TIS prediction model, and these gave high accuracy with reduced true positive rates in different stages of the parasite life cycle. In this report we also predict the experimentally validated alternate translation initiation site of the Pfgrasp gene. This work is the first to use genomic and proteomic data to predict TIS in P. falciparum and has implications for further studies on translation initiation in the malaria parasite.


Key Words: Malaria, Translation, Initiation, P. falciparum.