EMPLOYING COMPUTATIONAL APPROACH TO PREDICT CRITICAL RESIDUES IN PFEMP1(INFORMATION THEORETIC MEASURES)

Abstract

PFEMP1 (Plasmodium falciparum erythrocyte membrane protein) is an important target for defensive immunity and is involve in the pathology of malaria through its ability to adhere to host endothelial receptors. PFEMP1 has specific domains which are essential in its cytoadherence function. PFEMP1 binds to CD36, an 88kDa glycoprotein found in several cell types including platelets, monocytes, dendritic cells, and micro vascular endothelial cells. This cythoadherence of PFEMP1 to CD36 receptor is due to a particular domain called CIDR1α domain. This cytoadherence function of CIDR1α to CD36 receptor is support by various conserved motifs which may be targeted to disrupt the parasite cytoadherence system. The knowledge of these critical residues can lead to the better considerate of the molecular basis of diseases which arise due to modified protein functions. This knowledge also would play a vital role in rational protein engineering and drug designing. So, in-depth knowledge of structure and function of various severely important residues of CIDR1α is necessary for effective drug design and vaccine designing. Herein, we will be employing computational approaches to predict fold and functionally vital residues of CIDR1α domain. Traditional use of conservation scores are enhanced with Information Theoretic scores – the Relative Entropy (RE) and Cumulative Relative Entropy (CRE) calculated from Multiple Sequence Alignment (MSA) have been shown to adversely identify residues important for the fold and specificity of the protein. These methods were enforced to predict residues of CIDR1α with high RE and CRE to be fold and functionally important respectively.