Computational prediction of N-linked glycosylation incorporating structural properties and patterns.

ABSTRACT:

Motivation

N-linked glycosylation occurs predominantly at the N-X-T/S motif, where X is any amino acid except proline. Not all N-X-T/S sequons are glycosylated, and a number of web servers for predicting N-linked glycan occupancy using sequence and/or residue pattern information have been developed. None of the currently available servers, however, utilizes protein structural information for the prediction of N-glycan occupancy.

Results

Here, we describe a novel classifier algorithm, NGlycPred, for the prediction of glycan occupancy at the N-X-T/S sequons. The algorithm utilizes both structural as well as residue pattern information and was trained on a set of glycosylated protein structures using the Random Forest algorithm. The best predictor achieved a balanced accuracy o

SUBMITTER: Chuang GY 

PROVIDER: S-EPMC3426846 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature