SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots

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 lea...

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Detalles Bibliográficos
Autores principales: Moreira, Irina S., Koukos, Panagiotis I., Melo, Rita, Almeida, Jose G., Preto, Antonio J., Schaarschmidt, Joerg, Trellet, Mikael, Gümüş, Zeynep H., Costa, Joaquim, Bonvin, Alexandre M. J. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5556074/
https://www.ncbi.nlm.nih.gov/pubmed/28808256
http://dx.doi.org/10.1038/s41598-017-08321-2
Descripción
Sumario: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/.

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