• K Veluraja

      Articles written in Journal of Biosciences

    • Studies on the conformations of sialyloligosaccharides and implications

      K Veluraja V S R Rao

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      Theoretical investigations, using semi-empirical potential functions have been carried out to predict the favoured conformations of the terminal dissaccharide fragments of various sialyloligosaccharides. The proposed conformational similarity for these fragments has been correlated to the binding specificity of neuraminidases. These calculations predict that bacterial neuraminidases have a binding site which can accommodate only two sugar residues and virus neuraminidases have a binding site which can accommodate more than two sugar residues.

    • Generation of deviation parameters for amino acid singlets, doublets and triplets from three-dimensional structures of proteins and its implications for secondary structure prediction from amino acid sequences

      S A Mugilan K Veluraja

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      We present a new method, secondary structure prediction by deviation parameter (SSPDP) for predicting the secondary structure of proteins from amino acid sequence. Deviation parameters (DP) for amino acid singlets, doublets and triplets were computed with respect to secondary structural elements of proteins based on the dictionary of secondary structure prediction (DSSP)-generated secondary structure for 408 selected nonhomologous proteins. To the amino acid triplets which are not found in the selected dataset, a DP value of zero is assigned with respect to the secondary structural elements of proteins. The total number of parameters generated is 15,432, in the possible parameters of 25,260. Deviation parameter is complete with respect to amino acid singlets, doublets, and partially complete with respect to amino acid triplets. These generated parameters were used to predict secondary structural elements from amino acid sequence. The secondary structure predicted by our method (SSPDP) was compared with that of single sequence (NNPREDICT) and multiple sequence (PHD) methods. The average value of the percentage of prediction accuracy for αhelix by SSPDP, NNPREDICT and PHD methods was found to be 57%, 44% and 69% respectively for the proteins in the selected dataset. For Β-strand the prediction accuracy is found to be 69%, 21% and 53% respectively by SSPDP, NNPREDICT and PHD methods. This clearly indicates that the secondary structure prediction by our method is as good as PHD method but much better than NNPREDICT method.

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