The mannose binding proteins (MBP) also called mannose binding lectin(MBL) play a vital role in living organisms.These MBL mediates innate immune function including activation of lactin complement pathway,by binding to Mannose on the surface of wide range of pathgens(viruses, bacteria, fungi, protozoa).One of the important questions to understand the function of MBL, as "recognition" molecule is how MBP distinguish their target (pathogen)from nontarget in vivo.MBP have some interacting residues termed as Mannose Interacting residues (MIRs),which helps in recognizition of pathogens from their surface sugar like mannose,which are absent from mammalian cell surface. Understanding of mannose binding specificity of an MBP can be another way to identify mannose interacting residues in unknown protein, which helps in recognision of pathogen.Thus, the identification of MIRs is a major challenge in the field of molecular recognition.Thus, the development of computational method for predicting MIR in a protein from its amino acid sequence is important for better understanding the function and mechanism of these MBP.
PreMieR is a web-server specially trained for the identification of mannose interacting residues. The prediction is based on the basis of composition pattern of 23 window motif of amino acid sequence by using support vector machines(SVM). The prediction result will be displayed on web browser.Our model predict mannose interacting residues with very high accuracy. During our study we may achieved maximum accuracy 89% using composition based model. We developed user friendly webserver where user can submit there sequence (directly paste sequence in box ) and select the option for binary pattern,composition pattern, hybrid and threshold. After some time result will dispalyed on the terminal.