In silico Platform for Prediction of N-, O- and C-Glycosites in Eukaryotic Protein SequencesReportar como inadecuado




In silico Platform for Prediction of N-, O- and C-Glycosites in Eukaryotic Protein Sequences - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Glycosylation is one of the most abundant and an important post-translational modification of proteins. Glycosylated proteins glycoproteins are involved in various cellular biological functions like protein folding, cell-cell interactions, cell recognition and host-pathogen interactions. A large number of eukaryotic glycoproteins also have therapeutic and potential technology applications. Therefore, characterization and analysis of glycosites glycosylated residues in these proteins is of great interest to biologists. In order to cater these needs a number of in silico tools have been developed over the years, however, a need to get even better prediction tools remains. Therefore, in this study we have developed a new webserver GlycoEP for more accurate prediction of N-linked, O-linked and C-linked glycosites in eukaryotic glycoproteins using two larger datasets, namely, standard and advanced datasets. In case of standard datasets no two glycosylated proteins are more similar than 40%; advanced datasets are highly non-redundant where no two glycosites’ patterns as defined in methods have more than 60% similarity. Further, based on our results with several algorihtms developed using different machine-learning techniques, we found Support Vector Machine SVM as optimum tool to develop glycosite prediction models. Accordingly, using our more stringent and non-redundant advanced datasets, the SVM based models developed in this study achieved a prediction accuracy of 84.26%, 86.87% and 91.43% with corresponding MCC of 0.54, 0.20 and 0.78, for N-, O- and C-linked glycosites, respectively. The best performing models trained on advanced datasets were then implemented as a user-friendly web server GlycoEP http:-www.imtech.res.in-raghava-glycoep-. Additionally, this server provides prediction models developed on standard datasets and allows users to scan sequons in input protein sequences.



Autor: Jagat Singh Chauhan, Alka Rao, Gajendra P. S. Raghava

Fuente: http://plos.srce.hr/



DESCARGAR PDF




Documentos relacionados