The classical nuclear export signal (NES), also known as the leucine-rich NES, is a protein localization signal often involved in important processes such as signal transduction and cell cycle regulation. Although 15 years has passed since its discovery, limited structural information and high sequence diversity have hampered understanding of the NES. Several consensus sequences have been proposed to describe it, but they suffer from poor predictive power. On the other hand, the NetNES server provides the only computational method currently available. Although these two methods have been widely used to attempt to find the correct NES position within potential NES-containing proteins, their performance has not yet been evaluated on the basic task of identifying NES-containing proteins. We propose a new predictor, NESsential, which uses sequence derived meta-features, such as predicted disorder and solvent accessibility, in addition to primary sequence. We demonstrate that it can identify promising NES-containing candidate proteins (albeit at low coverage), but other methods cannot. We also quantitatively demonstrate that predicted disorder is a useful feature for prediction and investigate the different features of (predicted) ordered versus disordered NES's. Finally, we list 70 recently discovered NES-containing proteins, doubling the number available to the community.
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