Scientific Reports (Aug 2017)

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

  • Irina S. Moreira,
  • Panagiotis I. Koukos,
  • Rita Melo,
  • Jose G. Almeida,
  • Antonio J. Preto,
  • Joerg Schaarschmidt,
  • Mikael Trellet,
  • Zeynep H. Gümüş,
  • Joaquim Costa,
  • Alexandre M. J. J. Bonvin

DOI
https://doi.org/10.1038/s41598-017-08321-2
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 11

Abstract

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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/ .