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:10.1038/s41598-017-08321-2

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

Research output: Contribution to journal › Article › peer-review

81 Scopus citations

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/.

Original language	English
Article number	8007
Journal	Scientific Reports
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41598-017-08321-2
State	Published - 1 Dec 2017

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title = "SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots",

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/.",

author = "Moreira, \{Irina S.\} and Koukos, \{Panagiotis I.\} and Rita Melo and Almeida, \{Jose G.\} and Preto, \{Antonio J.\} and Joerg Schaarschmidt and Mikael Trellet and G{\"u}m{\"u}{\c s}, \{Zeynep H.\} and Joaquim Costa and Bonvin, \{Alexandre M.J.J.\}",

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doi = "10.1038/s41598-017-08321-2",

language = "English",

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T2 - High Accuracy Identification of Protein-Protein Interface Hot-Spots

AU - Moreira, Irina S.

AU - Koukos, Panagiotis I.

AU - Melo, Rita

AU - Almeida, Jose G.

AU - Preto, Antonio J.

AU - Schaarschmidt, Joerg

AU - Trellet, Mikael

AU - Gümüş, Zeynep H.

AU - Costa, Joaquim

AU - Bonvin, Alexandre M.J.J.

PY - 2017/12/1

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AB - 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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SN - 2045-2322

VL - 7

JO - Scientific Reports

JF - Scientific Reports

IS - 1

M1 - 8007

ER -

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

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