Abstract
We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble machine learning approach with up-sampling of the minor class. It was trained on 53 complexes using various features, based on both protein 3D structure and sequence. The SpotOn web interface is freely available at: http://milou.science.uu.nl/services/SPOTON/.
Cite
CITATION STYLE
Moreira, I. S., Koukos, P. I., Melo, R., Almeida, J. G., Preto, A. J., Schaarschmidt, J., … Bonvin, A. M. J. J. (2017). SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-08321-2
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.